<p dir="ltr">As aircraft engine manufacturers continue to embark on their pursuit of higher-efficiency, lower-emissions gas turbines, a prevailing theme in the industry has been the increase of the engine bypass ratio. As the optimization space for engine bypass ratios trends towards smaller and smaller engine core sizes, the feasibility of centrifugal compressors as the final stage in an axial-centrifugal compressor becomes apparent due to their performance advantages at smaller scales.</p><p dir="ltr">This study performed an investigation into the aerodynamics of a stationary diffusion system intended for use with a final stage aeroengine centrifugal compressor using experimental and numerical techniques. Experimental work was performed at the Purdue Compressor Research Lab at Purdue University’s Maurice J. Zucrow Laboratories. Data were collected from several iterations of rapidly prototyped, additively manufactured diffuser and deswirl parts with internal instrumentation features. Furthermore, computational work on the stage was conducted using the Ansys Turbosystem.</p><p dir="ltr">The goal of this research is to identify trends in stationary diffusion system designs and the geometric features that cause them. Furthermore, the ability of steady computational fluid dynamics methods to predict these changes was evaluated using two turbulence models to produce a simulation of the compressor flow field. When used in conjunction with one another, the efficient use of computational methods to identify an optimal design and rapid prototyping to validate it leads to the determination of the best diffusion system design at a lower cost and time requirement than what is otherwise currently possible.</p><p dir="ltr">The different geometries which were tested identified the negative effects of spanwise vane contouring on the diffuser performance and the ability of endwall divergence to augment the pressure recovery performance of a design at the expense of increased losses. A full understanding of the effect of each design parameter is enabled by iterative inclusion or exclusion of certain design parameters. Furthermore, the use of computational fluid dynamics showed that the BSLEARSM turbulence model performs reasonably well in predicting the build-to-build performance trends. However, neither the BSLEARSM nor the SST turbulence model were able to accurately identify performance trends for the deswirl. For this reason, additional work is warranted to identify an optimal set of parameters to characterize the high axial and meridional turning present in this component.</p>

<p dir="ltr">With increasing power densities in electronic devices, effective thermal management has become an indispensable aspect of electronic systems design. Although phase change materials (PCMs) have been studied as a potential solution, their integration into microelectronic and high-power devices presents a significant challenge due to low thermal conductivity and lack of effective thermal pathways from the heat source to the heat sink. While much work has focused on integrating thermal storage into heat sinks, this dissertation instead investigates integrating PCMs between the heat source and the heat sink in different configurations. By placing the energy storage closer to the heat source, the thermal resistance is reduced, which improves the overall thermal performance of the device. Specifically, this work explores the efficacy of two approaches: (1) direct embedding of a PCM within the die for mobile electronics applications and (2) integration of an auxiliary composite PCM/copper thermal energy storage (TES) component in combination with active liquid cooling for high-power power electronics modules.</p><p><br></p><p dir="ltr">The first study explores die-level thermal management for microelectronics using PCMs. Silicon chips with PCM embedded within the die are modeled using ParaPower, a fast-analysis tool, and a genetic algorithm is used to efficiently optimize the distribution of high-conductivity silicon pathways and high thermal capacitance PCM zones. A thermal test vehicle (TTV) of a realistic microelectronics form factor with an embedded PCM layer is first designed, and a process is developed to fabricate such a TTV. This study is the first to successfully fabricate a TTV with fully encapsulated PCM and validate its thermal response across various operational scenarios. For temperature cycling tests (where the TTV temperature fluctuates between predetermined hot and cold setpoints), the embedded-PCM TTVs extend the operational time by up to 2.8x compared to a baseline all-silicon TTV. For duty cycling tests (with a fixed duration of the periodic heating pulses and off times), the embedded-PCM TTVs suppress the hotspot temperature rise by up to 14% and stabilize quasi-steady state temperature fluctuations by up to 65% through repeated PCM melting and solidification cycles. Thermal performance enhancements are observed even for high heat fluxes of ~65W/cm² . Specifically, a TTV with an embedded square-shaped PCM reservoir reduces temperature instability by an average of 40% across a range of cycle durations.</p><p><br></p><p dir="ltr">The second study investigates the effectiveness of different integration strategies for an auxiliary composite PCM/copper TES block integrated alongside a cold plate, for thermal management of high-power power electronics modules, specifically for electric vehicles. These systems are evaluated for realistic drive cycles of various driving intensities. Computational results indicate that this approach is most effective when the composite TES block is positioned directly above the heat-generating silicon carbide dies. This configuration excels at stabilizing transient temperature fluctuations and absorbing thermal shocks, achieving reductions of up to approximately ~33% compared to current thermal management techniques. This strategy is particularly effective for stop-and-go drive cycles characterized by high rates of acceleration and deceleration, low average driving speeds, and frequent stops, typical of driving schedules for public transport buses and mail delivery vehicles.</p><p><br></p><p dir="ltr">The results from both thermal management approaches demonstrate that the integration of a PCM cooling solution in close proximity to the heat source can significantly enhance its effectiveness by absorbing power bursts and limiting temperature instability via repeated melting and solidification. The contributions of this dissertation include the development of an effective optimization strategy for generating optimized PCM distributions, which reduces the maximum temperature and temperature oscillations in a device with significant computational efficiency. (The same optimization strategy can be applied to other thermal management design challenges.) Notably, TTVs of realistic microelectronics form factors with embedded PCM were designed, modeled, fabricated, and validated. With the PCM thermal buffers, the engineered solution demonstrated superior performance compared to a baseline all-silicon TTV. The second study into the integration of composite PCM/copper TES blocks into high-power power electronics modules established trade-offs between different architectures across various performance metrics, and highlighted its effectiveness for drive cycles with varying intensities. These findings offer an important contribution to the development of embedded thermal management techniques for electronic systems design, which will be critical for the advancement of next-generation microelectronics and high-power devices.</p>

<p dir="ltr">Due to the end of Dennard scaling, electronic devices must consume more electrical power for increased functionality. The increased power consumption, combined with diminishing form factors, results in increased power density within the device, leading to increased heat fluxes at the devices surfaces. Without proper thermal management, the increase in heat fluxes can cause device temperatures to exceed operational limits, ultimately resulting in device failure. However, the dissipation of these high heat fluxes often requires pumping or refrigeration of a coolant, which in turn, increases the total energy usage. Data centers, which form the backbone of the cloud infrastructure and the modern economy, account for ~2% of the total US electricity use, of which up to ~40% is spent on cooling needs alone. Thus, it is necessary to optimize the designs of the cooling systems to be able to dissipate higher heat fluxes, but at lower operating powers.</p><p dir="ltr">The design optimization of various thermal management components such as cold plates, heat sinks, and heat exchangers relies on accurate prediction of flow heat transfer and pressure drop. During the iterative design process, the heat transfer and pressure drop is typically either computed numerically or obtained using geometry-specific correlations for Nusselt number (<i>Nu</i>) and friction factor (<i>f</i>). Numerical approaches are accurate for evaluation of a single design but become computationally expensive if many design iterations are required (such as during formal optimization processes). Moreover, traditional empirical correlations are highly geometry dependent and assume functional forms that could introduce inaccuracies. To overcome these limitations, this thesis introduces accurate and continuous-valued machine-learning (ML)-based surrogate models for predicting Nusselt number and friction factor on various heat exchange surfaces. These surrogate models, which are applicable to more geometries than traditional correlations, enable flexible and computationally inexpensive design optimization. The utility of these surrogate models is first demonstrated through the optimization of single-phase liquid cold plates under specific boundary conditions. Subsequently, their effectiveness is further showcased in the more practical challenge of designing liquid-to-liquid heat exchangers by integrating the surrogate models with a homogenization-based topology optimization framework. As topology optimization relies heavily on accurate predictions of pressure drop and heat transfer at every point in the domain during each iteration, using ML-based surrogate models greatly reduces the computational cost while enabling the development of high-performance, customized heat exchange surfaces. Thus, this work contributes to the advancement of thermal management by leveraging machine learning techniques for efficient and flexible design optimization processes.</p><p dir="ltr">First, artificial neural network (ANN)-based surrogate correlations are developed to predict <i>f</i> and <i>Nu</i> for fully developed internal flow in channels of arbitrary cross section. This effectively collapses all known correlations for channels of different cross section shapes into one correlation for <i>f</i> and one for <i>Nu</i>. The predictive performance and generality of the ANN-based surrogate models is verified on various shapes outside the training dataset, and then the models are used in the design optimization of flow cross sections based on performance metrics that weigh both heat transfer and pressure drop. The optimization process leads to novel shapes outside the training data, the performance of which is validated through numerical simulations. Although the ML model predictions lose accuracy outside the training set for these novel shapes, the predictions are shown to follow the correct trends with parametric variations of the shape and therefore successfully direct the search toward optimized shapes.</p><p dir="ltr">The success of ANN-aided shape optimization of constant cross-section internal flow channels serves as a compelling proof-of-concept, highlighting the potential of ML-aided optimization in thermal-fluid applications. However, to address the complexities of widely used thermal management devices such as cold plates and heat exchangers, known for their intricate surface geometries beyond constant cross-section channels, a strategic shift is imperative. With the goal of crafting ML models specifically tailored for practical design optimization algorithms like topology optimization, the thesis next delves into diverse micro-pin fin arrangements commonly employed in applications like cold plates and heat exchangers. This study on pin fins includes the exploration of hydrodynamic and thermal developing effects, as well as the impact of pin fin cross section shape and orientation. The ML-based predictive models are trained on numerically simulated synthetic data. The large amounts of accurate synthetic data required to train machine learning models are generated using a custom-developed simulation automation framework. With this framework, numerical flow and heat transfer simulations can be run on thousands of geometries and boundary conditions with minimal user intervention. The proposed models provide accurate predictions of <i>f</i> and <i>Nu</i>, with a near exact match to the training data as well as on unseen testing data. Furthermore, the outputs of the ANNs are inspected to propose new analytical correlations to estimate the hydrodynamic and thermal entrance lengths for flow through square pin fin arrays. The ML models are also shown to be useable for fluids other than water, employing physics-based, Prandtl-number-dependent scaling relations.</p><p dir="ltr">The thesis further demonstrates the utility of the ML surrogate models to facilitate the design optimization of thermal management components through their integration in the topology optimization (TO) framework for heat exchanger design. Topology optimization is a computational design methodology for determining the optimal material distribution within a design space based on given constraints. The use of topology optimization in the design of heat exchangers and other thermal management devices has been gaining significant attention in recent years, particularly with the widespread availability of additive manufacturing techniques that offer geometric design flexibility. Particularly advantageous for heat exchanger design is the homogenization approach to topology optimization, which represents partial densities in the design domain using a physical unit cell structure to achieve sub-grid resolution features. This approach requires geometry-specific, correlations for <i>f</i> and <i>Nu</i> to simulate the performance of designs and evaluate the objective function during the optimization process. Topology optimized pin fin-based component designs rely on additive manufacturing, posing production scalability challenges with current technologies. Furthermore, the demand for flow and thermal anisotropy in several applications adds complexity to the design requirements. To address these challenges, the focus is shifted to traditional heat exchanger surface geometries that can be manufactured using conventional techniques, and which also exhibit pronounced anisotropy in flow and heat transfer characteristics. Traditionally, these geometries are distributed uniformly across heat exchange surfaces. However, incorporating such geometries into the topology optimization framework merges the strengths of both approaches, yielding mathematically optimized heat exchange surfaces with conventionally manufacturable designs. Offset strip fins, one such commonly used geometry, is chosen to be the physical unit cell structure to demonstrate the integration of ML-based surrogate models into the topology optimization framework. The large amount of data required to develop robust machine learning-based surrogate <i>f</i> and <i>Nu</i> models for axial and cross flow of water through offset strip fins are generated through numerical simulations performed for convective flows through these geometries. The data generated are compared against in-house-measured experimental data as well as against data from literature. To facilitate the integration of ML models into topology optimization, a discrete adjoint method was developed to calculate the sensitivities during topology optimization, to circumvent the absence of the analytical gradients.</p><p dir="ltr">Successful integration of the machine learning-based surrogate models into the topology optimization framework was demonstrated through the design optimization of a counterflow heat exchanger. The topology optimized design outperformed the benchmarks that used uniform, parametrically optimized offset strip fin arrays. The topology optimized design exhibited domain-specific enhancements such as peripheral flow paths for enhanced heat transfer and open channels to minimize pressure drops. This integration showcases the potential of combining ML models with topology optimization, providing a flexible framework that can be extended to a wide range of enhanced surface structure types and geometric configurations for which ML models can be trained. Thus, by enabling spatially localized optimization of enhanced surface structures using ML models, and consequently offering a pathway for expanding the design space to include many more surface structures in the topology optimization framework than previously possible, this thesis lays the foundation for advancing design optimization of thermal-fluid components and systems, using both additively and conventionally manufacturable geometries.</p>

Thesis (MScEng (Process Engineering))--University of Stellenbosch, 2011. / Please refer to full text to view abstract.

Heterogeneous photocatalysis is an advanced oxidation technology widely applied in environmental remediation processes. It is a relatively safe and affordable technology with a low impact on the environment and has found applications in a number of fields from chemical engineering, construction and microbiology to medicine. It is not catalysis in the real sense of the word as the photons which initiate the desired photocatalytic reaction are consumed in the process. The cost of these photons is by far the limiting economic factor in its application. From a technical standpoint, the inefficient use of the aforementioned photons during the photocatalytic reaction is responsible for the limited adoption of its application in industry. This inefficiency is characterised by low quantum yields or photonic efficiencies during its application. The mechanism of the technique of controlled periodic illumination which was previously proposed as a way of enhancing the low photonic efficiency of TiO2 photocatalysis has been investigated using a novel controlled experimental approach; the results showed no advantage of periodic illumination over continuous illumination at equivalent photon flux. When the technique of controlled periodic illumination is applied in a photocatalytic reaction where attraction between substrate molecules and catalyst surface is maximum and photo-oxidation by surface-trapped holes, {TiIVOH•}+ ads is predominant, photonic efficiency is significantly improved. For immobilized reactors which usually have a lower illuminated surface area per unit volume compared to suspended catalyst and mass transfer limitations, the photonic efficiency is even lower. A novel photocatalytic impeller reactor was designed to investigate photonic efficiency in gas–solid photocatalysis of aromatic volatile organic compounds. The results indicate photonic efficiency is a function of mass transfer and catalyst deactivation rate. The development of future reactors which can optimise the use of photons and maximize photonic efficiency is important for the widespread adoption of heterogeneous photocatalysis by industry.

Les procédés électrochimiques présentent beaucoup d’avantages dans le domaine du traitement et de la récupération de matière d’effluents industriels. Cependant, dans le cas de solutions diluées en ions métalliques, les électrodes classiques sont fortement limitées par leur efficacité ainsi que par leur taille. Dès lors, les électrodes poreuses, de par leur surface spécifique importante et de par leur structure particulière qui améliore le transport de matière et donc l’efficacité de l’électrode, représentent une alternative très intéressante aux électrodes classiques. Parmi les électrodes poreuses, celles constituées de fibres métalliques semblent les plus prometteuses. L’objectif de ce travail est de donner les relations utiles pour dimensionner une cellule contenant ce type d’électrodes en vue du traitement d’effluents industriels contenant des ions métalliques. Les électrodes étudiées ont été caractérisées par différentes techniques : microscopie électronique, méthode électrochimique, mesure de la perte de charge, conductimétrie, porosimétrie,… Cette caractérisation a permis de connaître la porosité, les surfaces spécifiques (géométrique, dynamique et électrochimique) et la tortuosité des électrodes. Ensuite, le coefficient de transport de matière moyen a été étudié par une nouvelle méthode basée sur la mesure d’un rendement électrochimique. Cette méthode présente l’avantage de pouvoir travailler avec des vitesses de circulation de l’électrolyte compatibles avec celles utilisées industriellement. Pour cela, une cellule d’électrolyse à circulation forcée a été mise au point. Afin de comprendre comment la géométrie d’une électrode poreuse de ce type influence le transport de matière local et la densité de courant et donc l’efficacité de l’électrode, le transport de matière et la densité de courant locale ont été modélisés autour d’un cylindre (représentatif d’une fibre) et validés par des mesures expérimentales. La modélisation s’est ensuite étendue à un réseau de fibres cylindriques représentatif des électrodes poreuses étudiées. Cette modélisation a permis d’obtenir une relation générale liant les nombres de Sherwood, de Reynolds et de Schmidt à des nombres sans dimension caractérisant la géométrie du réseau de fibres. Cette relation donne des résultats concordants avec ceux obtenus expérimentalement pour les électrodes poreuses étudiées. Le volume utile d’une électrode poreuse dépend fortement des conditions expérimentales (concentration de l’électrolyte, vitesse de circulation, intensité du courant appliquée,…) et de la structure de l’électrode (porosité, surface spécifique,…). Ces paramètres influencent la distribution du potentiel et de la densité de courant dans l’électrode. Différents modèles de distribution sont comparés et appliqués aux électrodes poreuses étudiées. Cette distribution de courant influence le colmatage progressif de l’électrode poreuse en cours d’électrolyse. Il s’avère que l’électrode en contrôle diffusionnel (avec un rendement électrochimique faible) optimise la distribution du courant dans l’électrode et, de ce fait, ralenti son colmatage. De plus, travailler avec une solution diluée et une vitesse de circulation de l’électrolyte importante améliore la distribution du courant. Il en est de même si l’électrode poreuse présente une grande porosité et une faible surface spécifique. Ce travail aura donc permis de proposer des relations indispensables pour le dimensionnement d’une cellule à électrodes poreuses (constituées de fibres métalliques) ainsi que les conditions opératoires idéales dans le cas du traitement d’effluents industriels contenant des ions métalliques./ Electrochemical techniques offer many advantages for the prevention of pollution problems in the industrial processes. However, flat electrodes are not ideal to treat dilute solutions containing metallic ions. With their high specific surface and open structure, which enhance mass transfer, porous electrodes are a good alternative for the treatment this kind of effluent. Fibre materials are particularly well suited as material for the production of porous electrodes. The aim of this thesis is to study an electrochemical cell with a porous electrode in order to treat dilute metallic ions solutions and to provide dimensionless equations suited to scale-up the electrode for industrial application. The porous electrodes, used in this thesis, are made of a stainless steel fibre network. The main properties and characteristics of these electrodes are studied by means of several techniques : electron microscopy, electrochemical methods (voltammetry, limiting current density measurerment), conductivity measurement, porosimetry, pressure drop measurement,… The obtained parameters are : porosity, specific surfaces (geometric, dynamic and electrochemical), fibres' diameter, tortuosity and the geometric disposition of the fibres in the electrodes. Mass transfer inside the porous electrodes is studied experimentally by a new developed method, linked to the measurement of the faradic yield as a function of different electrolysis parameters. For these measurements, an experimental electrolysis cell with high electrolyte flow rate has been designed and builds. To understand how the geometry of the porous electrode influences the local and mean mass transfer coefficients and current densities, numerical studies and simulations have been performed. The first type of simulation deals with a single wire (representative of a fibre from the porous electrode). The second type of simulation deals with the integration of individual fibres in a fibre network. A correlation between dimensionless numbers such as Sherwood's, Reynolds' and Schmidt's numbers together with numbers characteristic of the electrode’s geometry has been established for Reynolds’s numbers ranging from 0,02 to 1,4. A good agreement between simulation and experimental measurements of mass transfer is observed. The real effective electrochemical volume of the porous electrode depends on experimental conditions (current, concentration, flow velocity…) and electrode’s geometry (porosity, specific surface,…). These parameters influence the potential and current distribution inside the porous electrode. Several models of current distribution are applied to these electrodes and the theoretical simulations are compared with experimental measures. As a result of these simulations, an electrode under diffusion control with a small faradic yield appears to be the best choice in order to homogenise the current density inside the porous electrodes. Dilute solutions, high flow velocity and electrodes with high porosity improve also the current density penetration inside the electrode. These observations are confirmed by an electrode’s plugging study. In conclusion, this thesis provides mathematical relationships to scale-up a cell with porous electrodes of metallic fibre, and provides guidelines to treat, in an efficient manner industrial effluents containing metallic ions.

To meet the growing energy world demands, and in conjunction, lower CO2 production levels, near zero emission energy sources must be pushed to the forefront as alternatives to fossil fuels. Photoelectrochemical (PEC) cells are a potential alternative to fossil fuels and have recently generated much interest because of their potential to electrolyze water into hydrogen fuel from sunlight. But in order to be competitive with fossil fuels, understanding the mass-transfer limitations in PEC systems is critical. This work focuses on the addressing the mass-transfer limitations in a conceptually novel PEC cell reactor, the Dual Bed Colloidal Suspension Reactor (DBCSR). Mass-transfer correlations for the DBCSR are presented. The correlations are based on experimental data obtained using two fabricated diffusion cells. The working correlation representative of both cells is given. An analysis of the orientation of the gas sparger suggests that the transport phenomena in both cells is not the same, and therefore using two correlations to represent similar systems is justified. An energy analysis is presented that shows that gas sparging is a low energy consumption option to mitigate mass-transfer limitations. Future work is suggested for better understanding the mass-transfer behavior in the DBCSR.

The limiting current technique has widely been used to study liquid-solid mass transfer in various reactor configurations. In the present contribution several underlying physical aspects have been investigated in order to improve the design of mass transfer experiments. Experimentally, the significant influence of electrolyte composition and hydrodynamic conditions have been studied and quantified to ensure conditions of high reproducibility. In the course of single phase COMSOL simulations, different electrode configurations have been examined with emphasis on concentration fields and electric current distribution showing a large sensitivity of the experimental configuration on the absolute current values.

L'acrylamide, connu comme étant une molécule cancérigène, apparait lors de traitement thermique à haute température (>120°C) d'aliments riches en asparagine et en sucre. La friture profonde génère ce composé à des teneurs proche de 0,44 ppm pour les chips de plantain. Or les aliments à base de plantain sont largement consommés dans les pays du sud. Ces travaux de recherche ont pour objectif de mieux comprendre l'accumulation de l'acrylamide lors de l'élaboration de produits frits à base de plantain. Pour y parvenir la teneur en précurseurs (asparagine) a d'abord été obtenue dans différentes variétés de bananes, mais aussi durant le mûrissage d'une variété de plantain d'exportation (Harton). Ces résultats ont permis d'identifier l'asparagine comme étant limitant pour la formation d'acrylamide dans le plantain. Ensuite, une étude cinétique du couplage entre la température et l'activité en eau a été entreprise en système fermé. Le domaine d'étude consistait en 4 températures de traitement (140, 160, 180 et 200°C) et 3 activités en eau (0,43 ; 0,9 ; 0,97). La cinétique de formation et d'élimination de l'acrylamide a été traduite par la somme de 2 cinétiques d'ordre 1. Les paramètres cinétiques ont été identifiés et montrent que la température est le paramètre qui influence le plus la cinétique de l'acrylamide. Le modèle cinétique a dans une autre étape été couplé à un modèle traduisant les transferts d'énergie et de vapeur durant la friture. Le modèle a bien simulé les teneurs en eau et en acrylamide de deux produits frits à base de plantain « tajadas » (produit épais) et « tostones » (produit mince). Les coulages entre transfert et réaction sont discutés en vue d'imaginer des stratégies de réduction de l'acrylamide. Il a été démontré que la formation de l'acrylamide se fait presque exclusivement dans la zone hygroscopique périphérique (croûte). De ce fait, la conduite de la friture en températures variables est recommandée et permet de réduire d'au moins 50% la teneur en acrylamide. La sélection variétale et l'état de maturité du plantain sont les moyens en amont les plus souples pour contrôler la teneur en acrylamide dans le produit final. Des prétraitements par immersion se sont avérés efficaces induisant une réduction significative de l'acrylamide. En revanche, la formulation de molécules antioxydantes ne semble pas avoir d'effet réducteur. / Acrylamide, a molecule known as a carcinogen, appears during heat treatment of asparagine and sugars rich foods at high temperature (> 120 ° C). Deep frying produces this compound at levels close to 0.44 ppm for plantain chips, these foods being widely consumed in developing countries. The aim of the present work is to better understand the accumulation of acrylamide during the process of plantain-based products. In this context, the level of precursors (asparagine) was obtained firstly in different varieties of bananas and also during ripening of an export plantain variety (Harton). These results allowed identifying asparagine as a limiting factor of acrylamide formation in plantain. Afterwards, a kinetic study of the coupling between temperature and water activity was undertaken in a closed system. The field of study consisted of four temperatures of treatment (140, 160, 180 and 200 ° C) and three water activities (0.43, 0.9, 0.97). The kin etics of formation and elimination of acrylamide was translated by the sum of 2 order 1 kinetics. The kinetic parameters were identified and showed that temperature is the parameter that influences the most acrylamide kinetic. The kinetic model, in a further step, was coupled to a model describing energy and steam transfers during frying. The model simulated well water and acrylamide content in two plantain-based fried products: "Tajada" (produced thick) and "tostones" (thin product). The coupling between transfers and reaction were discussed in order to identify strategies to reduce acrylamide. It was demonstrated that acrylamide formation occurs almost exclusively in the hygroscopic and peripheral area (crust). Thus, conducting frying process at varying temperatures is recommended and can reduce by at least 50% the acrylamide content. The varietal selection and the ripeness degree of plantain are more flexible ways to control upstream the levels of acrylamide in the final product. Immersion pretreatments were also effective to reduce significantly acrylamide. However, the formulation of antioxidant molecules did not appear to have reduction effect.

Cable ampacity analysis is generally performed assuming constant worst-state environmental conditions, which often correspond to a dry soil condition or to a condition with uniform ambient soil moisture content. The characteristic time scale of thermal variation in the soil is large, on the order of several weeks, and is similar to the time scale between rainfall events in many geographic locations. Intermittent rainfall events introduce significant transient fluctuations that influence the thermal conditions and moisture content around a buried cable both by increasing thermal conductivity of the soil and by increasing the moisture exposure of the cable insulation. This paper reports on a computational study of the effect of rainfall events on the thermal and moisture transients surrounding a buried cable. The computations were performed with a finite-difference method using an overset grid approach, with an inner polar grid surrounding the cable and an outer Cartesian grid. The thermal and moisture transients observed in computations with periodic rainfall events were compared to control computations with a steady uniform rainfall. Under periodic rainfall conditions, the temperature and moisture fields are observed to approach a limit-cycle condition in which the cable surface temperature and moisture content oscillate in time, but with mean values that are significantly different than the steady-state values.