A model for the consolidation of rafted sea ice

Rafting is one of the important deformation mechanisms of sea ice. This process is widespread in the north Caspian Sea, where multiple rafting produces thick sea ice features, which are a hazard to offshore operations. Here we present a one-dimensional, thermal consolidation model for rafted sea ice. We consider the consolidation between the layers of both a two-layer and a three-layer section of rafted sea ice. The rafted ice is assumed to be composed of layers of sea ice of equal thickness, separated by thin layers of ocean water. Results show that the thickness of the liquid layer reduced asymptotically with time, such that there always remained a thin saline liquid layer. We propose that when the liquid layer is equal to the surface roughness the adjacent layers can be considered consolidated. Using parameters representative of the north Caspian, the Arctic, and the Antarctic, our results show that for a choice of standard parameters it took under 15 h for two layers of rafted sea ice to consolidate. Sensitivity studies showed that the consolidation model is highly sensitive to the initial thickness of the liquid layer, the fraction of salt release during freezing, and the height of the surface asperities. We believe that further investigation of these parameters is needed before any concrete conclusions can be drawn about rate of consolidation of rafted sea ice features.

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.

Fast and slow precipitation responses to individual climate forcers: a PDRMIP multi-model study

Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.

Thermal behavior of Cu-Al alloys near the alpha-Cu-Al solubility limit

The thermal behavior of Cu-Al alloys with 17, 19 and 21 at.%Al was examined by differential thermal analysis (DTA), differential scanning calorimetry (DSC), X-ray diffractometry (XRD), optical microscopy (OM) and scanning electron microscopy (SEM). The presence of the gamma phase (Al4Cu9) was clearly detected for the Cu-19 at.%Al alloy and caused the alpha (2) phase disordering process in two stages. The tendency to increase the alpha (2) dissolution precipitates with the increase in the Al content seems to be reverted for compositions at about 21 at.%Al and the heating/cooling ratio seems to influence the thermal response of this process. The presence of the endothermic peak corresponding to the beta (1)--> beta transformation depends on an incomplete beta decomposition reaction. The variation of the heating rate showed that the beta (1)-->(alpha+gamma (1)) decomposition is the dominant reaction for alloys containing 19 and 21 at.%Al.

Dependência térmica da germinação de sementes de Drymaria cordata (L.) Willd. ex Roem. & Schult. (Cariophyllaceae)

A temperatura representa um importante fator ambiental regulador da germinação de sementes. Procurou-se avaliar a resposta de sementes de D. cordata à temperatura, com base no modelo de graus-dia, testando-se assim a eficiência desse modelo em descrever o comportamento germinativo da semente em diferentes regimes térmicos. Testou-se também a resposta das sementes à luz, concluindo-se que a luz branca promove a germinação. As temperaturas mínima, ótima e máxima de germinação foram, respectivamente, 17,1, 26 e 33,4 ºC. Considerando-se que a velocidade de germinação de D. cordata variou com a temperatura numa relação aproximadamente linear, o modelo de graus-dia pode ser uma ferramenta válida para se estudar a dependência da temperatura da germinação dessas sementes. Uma possível aquisição de dormência durante a incubação isotérmica pode exigir a aplicação de outros modelos que descrevam melhor o comportamento germinativo de D. cordata em diferentes regimes térmicos.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

Behavior of the thermal diffusivity of native and oxidized human low-density lipoprotein solutions studied by the Z-scan technique

Modifications in low-density lipoprotein (LDL) have emerged as a major pathogenic factor of atherosclerosis, which is the main cause of morbidity and mortality in the western world. Measurements of the heat diffusivity of human LDL solutions in their native and in vitro oxidized states are presented by using the Z-Scan (ZS) technique. Other complementary techniques were used to obtain the physical parameters necessary to interpret the optical results, e. g., pycnometry, refractometry, calorimetry, and spectrophotometry, and to understand the oxidation phase of LDL particles. To determine the sample's thermal diffusivity using the thermal lens model, an iterative one-parameter fitting method is proposed which takes into account several characteristic ZS time-dependent and the position-dependent transmittance measurements. Results show that the thermal diffusivity increases as a function of the LDL oxidation degree, which can be explained by the increase of the hydroperoxides production due to the oxidation process. The oxidation products go from one LDL to another, disseminating the oxidation process and caring the heat across the sample. This phenomenon leads to a quick thermal homogenization of the sample, avoiding the formation of the thermal lens in highly oxidized LDL solutions. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.JBO.17.10.105003]

Characterization of geothermal reservoirs’ parameters by inverse problem resolution and geostatistical simulations

BTES (borehole thermal energy storage)systems exchange thermal energy by conduction with the surrounding ground through borehole materials. The spatial variability of the geological properties and the space-time variability of hydrogeological conditions affect the real power rate of heat exchangers and, consequently, the amount of energy extracted from / injected into the ground. For this reason, it is not an easy task to identify the underground thermal properties to use when designing. At the current state of technology, Thermal Response Test (TRT) is the in situ test for the characterization of ground thermal properties with the higher degree of accuracy, but it doesn’t fully solve the problem of characterizing the thermal properties of a shallow geothermal reservoir, simply because it characterizes only the neighborhood of the heat exchanger at hand and only for the test duration. Different analytical and numerical models exist for the characterization of shallow geothermal reservoir, but they are still inadequate and not exhaustive: more sophisticated models must be taken into account and a geostatistical approach is needed to tackle natural variability and estimates uncertainty. The approach adopted for reservoir characterization is the “inverse problem”, typical of oil&gas field analysis. Similarly, we create different realizations of thermal properties by direct sequential simulation and we find the best one fitting real production data (fluid temperature along time). The software used to develop heat production simulation is FEFLOW 5.4 (Finite Element subsurface FLOW system). A geostatistical reservoir model has been set up based on literature thermal properties data and spatial variability hypotheses, and a real TRT has been tested. Then we analyzed and used as well two other codes (SA-Geotherm and FV-Geotherm) which are two implementation of the same numerical model of FEFLOW (Al-Khoury model).

Functional polymer coatings — My-Patterning and My-Analysis

In dieser Arbeit werden Strukturen beschrieben, die mit Polymeren auf Oberflächen erzeugt wurden. Die Anwendungen reichen von PMMA und PNIPAM Polymerbürsten, über die Restrukturierung von Polystyrol durch Lösemittel bis zu 3D-Strukturen, die aus PAH/ PSS Polyelektrolytmultischichten bestehen. Im ersten Teil werden Polymethylmethacrylat (PMMA) Bürsten in der ionischen Flüssigkeit 1-Butyl-3-Methylimidazolium Hexafluorophospat ([Bmim][PF6]) durch kontrollierte radikalische Polymerisation (ATRP) hergestellt. Kinetische Untersuchungen zeigten ein lineares und dichtes Bürstenwachstum mit einer Wachstumsrate von 4600 g/mol pro nm. Die durchschnittliche Pfropfdichte betrug 0.36 µmol/m2. Als Anwendung wurden Mikrotropfen bestehend aus der ionischen Flüssigkeit, Dimethylformamid und dem ATRP-Katalysator benutzt, um in einer definierten Geometrie Polymerbürsten auf Silizium aufzubringen. Auf diese Weise lässt sich eine bis zu 13 nm dicke Beschichtung erzeugen. Dieses Konzept ist durch die Verdampfung des Monomers Methylmethacrylat (MMA) limitiert. Aus einem 1 µl großen Tropfen aus ionischer Flüssigkeit und MMA (1:1) verdampft MMA innerhalb von 100 s. Daher wurde das Monomer sequentiell zugegeben. Der zweite Teil konzentriert sich auf die Strukturierung von Oberflächen mit Hilfe einer neuen Methode: Tintendruck. Ein piezoelektrisch betriebenes „Drop-on-Demand“ Drucksystem wurde verwendet, um Polystyrol mit 0,4 nl Tropfen aus Toluol zu strukturieren. Die auf diese Art und Weise gebildeten Mikrokrater können Anwendung als Mikrolinsen finden. Die Brennweite der Mikrolinsen kann über die Anzahl an Tropfen, die für die Strukturierung verwendet werden, eingestellt werden. Theoretisch und experimentell wurde die Brennweite im Bereich von 4,5 mm bis 0,21 mm ermittelt. Der zweite Strukturierungsprozess nutzt die Polyelektrolyte Polyvinylamin-Hydrochlorid (PAH) und Polystyrolsulfonat (PSS), um 3D-Strukturen wie z.B. Linien, Schachbretter, Ringe, Stapel mit einer Schicht für Schicht Methode herzustellen. Die Schichtdicke für eine Doppelschicht (DS) liegt im Bereich von 0.6 bis 1.1 nm, wenn NaCl als Elektrolyt mit einer Konzentration von 0,5 mol/l eingesetzt wird. Die Breite der Strukturen beträgt im Mittel 230 µm. Der Prozess wurde erweitert, um Nanomechanische Cantilever Sensoren (NCS) zu beschichten. Auf einem Array bestehend aus acht Cantilevern wurden je zwei Cantilever mit fünf Doppelschichten PAH/ PSS und je zwei Cantilever mit zehn Doppelschichten PAH/ PSS schnell und reproduzierbar beschichtet. Die Massenänderung für die individuellen Cantilever war 0,55 ng für fünf Doppelschichten und 1,08 ng für zehn Doppelschichten. Der daraus resultierende Sensor wurde einer Umgebung mit definierter Luftfeuchtigkeit ausgesetzt. Die Cantilever verbiegen sich durch die Ausdehnung der Beschichtung, da Wasser in das Polymer diffundiert. Eine maximale Verbiegung von 442 nm bei 80% Luftfeuchtigkeit wurde für die mit zehn Doppelschichten beschichteten Cantilever gefunden. Dies entspricht einer Wasseraufnahme von 35%. Zusätzlich konnte aus den Verbiegungsdaten geschlossen werden, dass die Elastizität der Polyelektrolytmultischichten zunimmt, wenn das Polymer gequollen ist. Das thermische Verhalten in Wasser wurde im nächsten Teil an nanomechanischen Cantilever Sensoren, die mit Poly(N-isopropylacrylamid)bürsten (PNIPAM) und plasmapolymerisiertem N,N-Diethylacrylamid beschichtet waren, untersucht. Die Verbiegung des Cantilevers zeigte zwei Bereiche: Bei Temperaturen kleiner der niedrigsten kritischen Temperatur (LCST) ist die Verbiegung durch die Dehydration der Polymerschicht dominiert und bei Temperaturen größer der niedrigsten kritischen Temperatur (LCST) reagiert der Cantilever Sensor überwiegend auf Relaxationsprozesse innerhalb der kollabierten Polymerschicht. Es wurde gefunden, dass das Minimum in der differentiellen Verbiegung mit der niedrigsten kritischen Temperatur von 32°C und 44°C der ausgewählten Polymeren übereinstimmt. Im letzten Teil der Arbeit wurden µ-Reflektivitäts- und µ-GISAXS Experimente eingeführt als neue Methoden, um mikrostrukturierte Proben wie NCS oder PEM Linien mit Röntgenstreuung zu untersuchen. Die Dicke von jedem individuell mit PMMA Bürsten beschichtetem NCS ist im Bereich von 32,9 bis 35,2 nm, was mit Hilfe von µ-Reflektivitätsmessungen bestimmt wurde. Dieses Ergebnis kann mit abbildender Ellipsometrie als komplementäre Methode mit einer maximalen Abweichung von 7% bestätigt werden. Als zweites Beispiel wurde eine gedruckte Polyelektrolytmultischicht aus PAH/PSS untersucht. Die Herstellungsprozedur wurde so modifiziert, dass Goldnanopartikel in die Schichtstruktur eingebracht wurden. Durch Auswertung eines µ-GISAXS Experiments konnte der Einbau der Partikel identifiziert werden. Durch eine Anpassung mit einem Unified Fit Modell wurde herausgefunden, dass die Partikel nicht agglomeriert sind und von einer Polymermatrix umgeben sind.

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

IMPROVING QUANTITATIVE TREATMENT RESPONSE MONITORING WITH DEFORMABLE IMAGE REGISTRATION

Quantitative imaging with 18F-FDG PET/CT has the potential to provide an in vivo assessment of response to radiotherapy (RT). However, comparing tissue tracer uptake in longitudinal studies is often confounded by variations in patient setup and potential treatment induced gross anatomic changes. These variations make true response monitoring for the same anatomic volume a challenge, not only for tumors, but also for normal organs-at-risk (OAR). The central hypothesis of this study is that more accurate image registration will lead to improved quantitation of tissue response to RT with 18F-FDG PET/CT. Employing an in-house developed “demons” based deformable image registration algorithm, pre-RT tumor and parotid gland volumes can be more accurately mapped to serial functional images. To test the hypothesis, specific aim 1 was designed to analyze whether deformably mapping tumor volumes rather than aligning to bony structures leads to superior tumor response assessment. We found that deformable mapping of the most metabolically avid regions improved response prediction (P<0.05). The positive predictive power for residual disease was 63% compared to 50% for contrast enhanced post-RT CT. Specific aim 2 was designed to use parotid gland standardized uptake value (SUV) as an objective imaging biomarker for salivary toxicity. We found that relative change in parotid gland SUV correlated strongly with salivary toxicity as defined by the RTOG/EORTC late effects analytic scale (Spearman’s ρ = -0.96, P<0.01). Finally, the goal of specific aim 3 was to create a phenomenological dose-SUV response model for the human parotid glands. Utilizing only baseline metabolic function and the planned dose distribution, predicting parotid SUV change or salivary toxicity, based upon specific aim 2, became possible. We found that the predicted and observed parotid SUV relative changes were significantly correlated (Spearman’s ρ = 0.94, P<0.01). The application of deformable image registration to quantitative treatment response monitoring with 18F-FDG PET/CT could have a profound impact on patient management. Accurate and early identification of residual disease may allow for more timely intervention, while the ability to quantify and predict toxicity of normal OAR might permit individualized refinement of radiation treatment plan designs.

Design of long-term animal bioassay for low-dose extrapolation using a multistage model

Conventional designs of animal bioassays allocate the same number of animals into control and dose groups to explore the spontaneous and induced tumor incidence rates, respectively. The purpose of such bioassays are (a) to determine whether or not the substance exhibits carcinogenic properties, and (b) if so, to estimate the human response at relatively low doses. In this study, it has been found that the optimal allocation to the experimental groups which, in some sense, minimize the error of the estimated response for low dose extrapolation is associated with the dose level and tumor risk. The number of dose levels has been investigated at the affordable experimental cost. The pattern of the administered dose, 1 MTD, 1/2 MTD, 1/4 MTD,....., etc. plus control, gives the most reasonable arrangement for the low dose extrapolation purpose. The arrangement of five dose groups may make the highest dose trivial. A four-dose design can circumvent this problem and has also one degree of freedom for testing the goodness-of-fit of the response model.^ An example using the data on liver tumors induced in mice in a lifetime study of feeding dieldrin (Walker et al., 1973) is implemented with the methodology. The results are compared with conclusions drawn from other studies. ^

Thermal behaviour of Sunrise, a balloon-borne solar Telescope

Sunrise is a solar telescope, successfully flown in June 2009 with a long duration balloon from the Swedish Space Corporation Esrange launch site. The design of the thermal control of SUNRISE was quite critical because of the sensitivity to temperature of the optomechanical devices and the electronics. These problems got more complicated due the size and high power dissipation of the system. A detailed thermal mathematical model of SUNRISE was set up to predict temperatures. In this communication the thermal behaviour of SUNRISE during flight is presented. Flight temperatures of some devices are presented and analysed. The measured data have been compared with the predictions given by the thermal mathematical models. The main discrepancies between flight data and the temperatures predicted by the models have been identified. This allows thermal engineers to improve the knowledge of the thermal behaviour of the system for future missions.

Implementation of the Heated Pulsed Theory using actively heated fiber optics: measurements of soil volumetric water content and soil volumetric heat capacity

Existe una creciente necesidad de hacer el mejor uso del agua para regadío. Una alternativa eficiente consiste en la monitorización del contenido volumétrico de agua (θ), utilizando sensores de humedad. A pesar de existir una gran diversidad de sensores y tecnologías disponibles, actualmente ninguna de ellas permite obtener medidas distribuidas en perfiles verticales de un metro y en escalas laterales de 0.1-1,000 m. En este sentido, es necesario buscar tecnologías alternativas que sirvan de puente entre las medidas puntuales y las escalas intermedias. Esta tesis doctoral se basa en el uso de Fibra Óptica (FO) con sistema de medida de temperatura distribuida (DTS), una tecnología alternativa de reciente creación que ha levantado gran expectación en las últimas dos décadas. Específicamente utilizamos el método de fibra calentada, en inglés Actively Heated Fiber Optic (AHFO), en la cual los cables de Fibra Óptica se utilizan como sondas de calor mediante la aplicación de corriente eléctrica a través de la camisa de acero inoxidable, o de un conductor eléctrico simétricamente posicionado, envuelto, alrededor del haz de fibra óptica. El uso de fibra calentada se basa en la utilización de la teoría de los pulsos de calor, en inglés Heated Pulsed Theory (HPP), por la cual el conductor se aproxima a una fuente de calor lineal e infinitesimal que introduce calor en el suelo. Mediante el análisis del tiempo de ocurrencia y magnitud de la respuesta térmica ante un pulso de calor, es posible estimar algunas propiedades específicas del suelo, tales como el contenido de humedad, calor específico (C) y conductividad térmica. Estos parámetros pueden ser estimados utilizando un sensor de temperatura adyacente a la sonda de calor [método simple, en inglés single heated pulsed probes (SHPP)], ó a una distancia radial r [método doble, en inglés dual heated pulsed probes (DHPP)]. Esta tesis doctoral pretende probar la idoneidad de los sistemas de fibra óptica calentada para la aplicación de la teoría clásica de sondas calentadas. Para ello, se desarrollarán dos sistemas FO-DTS. El primero se sitúa en un campo agrícola de La Nava de Arévalo (Ávila, España), en el cual se aplica la teoría SHPP para estimar θ. El segundo sistema se desarrolla en laboratorio y emplea la teoría DHPP para medir tanto θ como C. La teoría SHPP puede ser implementada con fibra óptica calentada para obtener medidas distribuidas de θ, mediante la utilización de sistemas FO-DTS y el uso de curvas de calibración específicas para cada suelo. Sin embargo, la mayoría de aplicaciones AHFO se han desarrollado exclusivamente en laboratorio utilizando medios porosos homogéneos. En esta tesis se utiliza el programa Hydrus 2D/3D para definir tales curvas de calibración. El modelo propuesto es validado en un segmento de cable enterrado en una instalación de fibra óptica y es capaz de predecir la respuesta térmica del suelo en puntos concretos de la instalación una vez que las propiedades físicas y térmicas de éste son definidas. La exactitud de la metodología para predecir θ frente a medidas puntuales tomadas con sensores de humedad comerciales fue de 0.001 a 0.022 m3 m-3 La implementación de la teoría DHPP con AHFO para medir C y θ suponen una oportunidad sin precedentes para aplicaciones medioambientales. En esta tesis se emplean diferentes combinaciones de cables y fuentes emisoras de calor, que se colocan en paralelo y utilizan un rango variado de espaciamientos, todo ello en el laboratorio. La amplitud de la señal y el tiempo de llegada se han observado como funciones del calor específico del suelo. Medidas de C, utilizando esta metodología y ante un rango variado de contenidos de humedad, sugirieron la idoneidad del método, aunque también se observaron importantes errores en contenidos bajos de humedad de hasta un 22%. La mejora del método requerirá otros modelos más precisos que tengan en cuenta el diámetro del cable, así como la posible influencia térmica del mismo. ABSTRACT There is an increasing need to make the most efficient use of water for irrigation. A good approach to make irrigation as efficient as possible is to monitor soil water content (θ) using soil moisture sensors. Although, there is a broad range of different sensors and technologies, currently, none of them can practically and accurately provide vertical and lateral moisture profiles spanning 0-1 m depth and 0.1-1,000 m lateral scales. In this regard, further research to fulfill the intermediate scale and to bridge single-point measurement with the broaden scales is still needed. This dissertation is based on the use of Fiber Optics with Distributed Temperature Sensing (FO-DTS), a novel approach which has been receiving growing interest in the last two decades. Specifically, we employ the so called Actively Heated Fiber Optic (AHFO) method, in which FO cables are employed as heat probe conductors by applying electricity to the stainless steel armoring jacket or an added conductor symmetrically positioned (wrapped) about the FO cable. AHFO is based on the classic Heated Pulsed Theory (HPP) which usually employs a heat probe conductor that approximates to an infinite line heat source which injects heat into the soil. Observation of the timing and magnitude of the thermal response to the energy input provide enough information to derive certain specific soil thermal characteristics such as the soil heat capacity, soil thermal conductivity or soil water content. These parameters can be estimated by capturing the soil thermal response (using a thermal sensor) adjacent to the heat source (the heating and the thermal sources are mounted together in the so called single heated pulsed probe (SHPP)), or separated at a certain distance, r (dual heated pulsed method (DHPP) This dissertation aims to test the feasibility of heated fiber optics to implement the HPP theory. Specifically, we focus on measuring soil water content (θ) and soil heat capacity (C) by employing two types of FO-DTS systems. The first one is located in an agricultural field in La Nava de Arévalo (Ávila, Spain) and employ the SHPP theory to estimate θ. The second one is developed in the laboratory using the procedures described in the DHPP theory, and focuses on estimating both C and θ. The SHPP theory can be implemented with actively heated fiber optics (AHFO) to obtain distributed measurements of soil water content (θ) by using reported soil thermal responses in Distributed Temperature Sensing (DTS) and with a soil-specific calibration relationship. However, most reported AHFO applications have been calibrated under laboratory homogeneous soil conditions, while inexpensive efficient calibration procedures useful in heterogeneous soils are lacking. In this PhD thesis, we employ the Hydrus 2D/3D code to define these soil-specific calibration curves. The model is then validated at a selected FO transect of the DTS installation. The model was able to predict the soil thermal response at specific locations of the fiber optic cable once the surrounding soil hydraulic and thermal properties were known. Results using electromagnetic moisture sensors at the same specific locations demonstrate the feasibility of the model to detect θ within an accuracy of 0.001 to 0.022 m3 m-3. Implementation of the Dual Heated Pulsed Probe (DPHP) theory for measurement of volumetric heat capacity (C) and water content (θ) with Distributed Temperature Sensing (DTS) heated fiber optic (FO) systems presents an unprecedented opportunity for environmental monitoring. We test the method using different combinations of FO cables and heat sources at a range of spacings in a laboratory setting. The amplitude and phase-shift in the heat signal with distance was found to be a function of the soil volumetric heat capacity (referred, here, to as Cs). Estimations of Cs at a range of θ suggest feasibility via responsiveness to the changes in θ (we observed a linear relationship in all FO combinations), though observed bias with decreasing soil water contents (up to 22%) was also reported. Optimization will require further models to account for the finite radius and thermal influence of the FO cables, employed here as “needle probes”. Also, consideration of the range of soil conditions and cable spacing and jacket configurations, suggested here to be valuable subjects of further study and development.