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Abstract: We present a joined experimental and theoretical investigation of the TiO2 polymorphism effects on dye-sensitized solar cells (DSSCs) photovoltaic properties. TiO2 nanoparticles of pure anatase, pure rutile and pure brookite stabilized phases with various sizes have been prepared by solution sol–gel approaches in order to evaluate their properties in photovoltaic devices. For a valuable comparison, these various nanoparticles have been used to construct identical solar cells. Their properties have been thoroughly estimated and analysed by J–V curves and impedance spectroscopy measurements along with first-principles calculations based on the density functional theory (DFT) under the B3LYP approximation. In the light of DFT calculations, the open circuit voltage (V oc) behavior of the solar cells is mainly explained by the dependency of the bottom of the conduction band position on the TiO2 phase. Quantifications of electron lifetimes, transfer times, diffusion coefficients (D eff) in the various polymorph TiO2 photoanodes are also of particular importance for explaining the photovoltaic properties of the different DSSCs. We have notably found a conductivity and D eff order being rutile

Abstract: Aim: The aim of this study was to report the feasibility and efficiency of a new approach, called post-RF trans-metastasis hepatectomy (PRFTMH). This technique consists in using RF to first ablate an ill-located liver metastasis (LM) along the planned hepatectomy resection line, the only one possible for volumetric reasons, and then to perform the hepatectomy passing via this initially ablated LM. Material and methods: Twenty-one patients were treated with PRFTMH between January 2000 and May 2004. Thirteen of them had a primary colorectal tumour, four had a primary endocrine tumour and four had miscellaneous primaries. The mean number of LMs per patient was 13.8 (10.7 for primary colorectal tumours and 22.2 for primary endocrine tumours). Pre-operative hypertrophy of the future remaining liver was obtained by selective portal vein embolisation in 11 patients. Results: One patient died post-operatively (4.7%) and five developed complications (24%). No local recurrence has occurred at the site of PRFTMH after a median follow-up of 19.4 months (range: 47–7), demonstrating the efficacy of this technique. All patients, except the patient who died post-operatively, are currently alive, and the median survival rate has not yet been attained, after a median follow-up of 19.4 months. Conclusion: PRFTMH combining RF ablation and trans-metastasis hepatectomy is a new and safe technique, allowing a curative approach to be proposed to some patients with unresectable bilateral LMs. [Copyright &y& Elsevier]

Abstract The electrochemical behaviour of a metal-rubber composite is studied in NaCl-based solutions. The metallic reinforcement is brass-coated pearlitic steel. Electrochemical investigations were performed in 0.01 M NaCl and in a solution containing 0.01 M NaCl with species released from the rubber during immersion. These species were identified using gas chromatography coupled with mass spectrometry. The role as inhibitors of some species (released from the rubber or added in the solution) was evaluated by determining polarisation curves and electrochemical impedance diagrams. In the cathodic domain, no synergistic effect was noticed between 2-aminobenzothiazole (added in the solution) and benzothiazole (released from the rubber in the solution). It was found from EIS diagrams that inhibition is caused by specific adsorption at the specimen surface. In the anodic domain, it was proposed that there is a synergistic effect between 2-aminobenzothiazole and benzothiazole. [ABSTRACT FROM AUTHOR]

Several factors are acting on concrete dams and affect dam displacements: hydrostatic load, thermal effect and irreversible phenomena (creep, swelling …). The different influences need to be quantified for the analysis of monitoring measurements. In most statistical models for the dam behavior analysis, the thermal effect which is often the main contributor to the total displacement is introduced only by means of the dam temperatures. Recently Tatin et al. (2015) have introduced a global gradient across the dam of the temperature bringing an additional bending effect. However, the thermal gradient may be very different, even with opposite sign, from the top to the bottom depending on seasons. In this paper, a statistical model accounting for the water temperature profile is proposed. In this original statistical model, the dam is discretized along its height in n layers on which both mean and gradient of the dam temperature are computed for the evaluation of the thermal effect. It implies 2 · n new explicative variables for the statistical model yielding a reduced dispersion of the residuals. However, statistical compensation occurs from one layer to the next leading to unrealistic influence functions along the height of the dam. In order to reduce this effect, the statistical problem is constrained by imposing a polynomial approximation of influence functions. The parameters of the polynomial may be estimated either beforehand by means of the dam numerical model or directly by the statistical process. The number of additional degrees of freedom of the statistical process is thus reduced but can still describe the effects of both profiles of the water temperature and the dam thickness on dam displacements. For the model construction and validation, an arch dam is modelled by means of the finite element method and serves as a virtual case study. Although results show only a slight reduced residual dispersion, physical meaning of the model to the intermediate quantities is increased. [ABSTRACT FROM AUTHOR]

Measurements of concrete dam displacements are influenced by various factors such as hydrostatic load, thermal effect and irreversible phenomena (creep, swelling, etc.). To interpret measurements and improve the assessment of irreversible effects, splitting the different influences is necessary. For this purpose, models based on statistics and physics are commonly employed in engineering studies. Although they are efficient in most cases to analyse the displacement of concrete dams, these models are built on a certain number of hypotheses, necessary to write “simple” mathematical relationships, but leading to uncertainties. To evaluate the suitability of these physico-statistical models (importance of the hypotheses) and to improve it, a 2D finite element (FE) model has been developed as a heuristic case. This study shows the importance of water temperature and temperature gradient in the assessment of the thermal displacements. So, a new physico-statistical model is proposed to account for these phenomena. The evaluation of its performance on both the FE heuristic case and real cases shows that the improved assessment of thermal effects on reversible phenomena leads to a reduced uncertainty on residuals. Thus, the proposed approach yields to a better assessment of irreversible trends. [ABSTRACT FROM AUTHOR]

• Hierarchized Local Sensitivity Analysis & Polynomial Chaos Expansion for structural modelling. • Application and validation based on an experimental Nuclear Containment Building. • Classification of influential parameters and phenomena affecting ageing structures. • Blind prediction of the structural behavior within a probabilistic framework at low cost. This work proposes a global Stochastic Finite Element Method (SFEM) to model the effects of concrete ageing uncertainties on the serviceability and durability of large reinforced and prestressed structures with a containment role. As their modelling requires strongly non-linear, coupled and expensive calculations with a large number of parameters, adapted and efficient probabilistic strategies need to be defined aiming at a stochastic analysis within a reasonable cost and a physically admissible representativeness. In this contribution, this is achieved through four steps: (a) the definition of a well-established physical framework based on a staggered Thermo-Hydro-Mechanical + Leakage (THM-L) model; (b) the limitation of random inputs for uncertainty propagation to the most influential ones using a variance-based Hierarchized and Local Sensitivity Analysis (HLSA); (c) the construction of a THM-L response metamodel using Polynomial Chaos Expansion (PCE); (d) the reliability analysis of serviceability criteria using Crude Monte Carlo Method (CMCM) applied to the developed metamodel. For validation purposes and demonstration of achievability within a complex industrial framework, this global methodology is applied to an experimental 1:3 scaled Containment Building of a nuclear reactor. Eventually, it is shown that a complete probabilistic analysis of a physically admissible total dry air leakage rate (indicative of a nuclear containment structure's performance) and its evolution in time are obtained within a computational time of tens of days only. Such result can provide insights and help during the decision-making process for the design, maintenance and risk assessment of large structures. For Nuclear Containment Buildings (NCB), a direct application would be the evaluation of lifespan extension based on a leakage-rate-defined criterion under operational loads. [ABSTRACT FROM AUTHOR]

The prediction of large concrete structures behavior such as bridges, dams and Nuclear Containment Buildings (NCB) is a key issue with regards to the evaluation of their durability, safety and the safety of their surrounding environment. In this work, a weakly coupled Thermo-Hydro-Mechanical (THM) modeling strategy is presented within the serviceability state of large structures. It aims at (a) defining and predicting the temperature, the relative humidity, the strains and the stresses in ageing concrete structures under variable and realistic THM loads and (b) qualitatively assessing the damage risk using a stress-based criterion. With that aim in view, the effect of concrete drying on its long term behavior is highlighted by using a revisited description of drying creep adapted to variable hydric conditions. The concrete’s response to variable THM boundaries is also compared to the one where mean and constant ones are considered in the case of NCBs. Two concrete types and three scales are considered for the THM study: the specimen scale for concrete properties identification, the 1:3 and 1:1 (full) scales of Representative Structural Volumes (RSV) for predictive and structural analyses. Through the FE sensitivity analysis, it is shown that the spatial variation of the temperature along the NCB’s height has more effect on the concrete’s ageing than its variation in time. Whereas, the temporal variation of hydric boundaries has a negligible effect away from the drying-exposed surfaces. Finally, it is demonstrated that, due to initial prestressing loads, the ageing kinetic within the NCB’s wall is heterogeneous and cannot be described using constant prestressing loads. Therefore, it is recommended to account for the spatial THM boundaries’ variation when predicting the global concrete ageing in large concrete structures. [ABSTRACT FROM AUTHOR]

• Air leakage estimation from in situ measurement and stochastic finite element modelling. • Parameters of Klinkenberg's law evaluated from measurements under vacuum. • Consideration of the variability of drying parameters for a reliable quantification. • Estimation of an accurate mean response of the diffuse air leakage under pressure. • Estimation of the quantification of uncertainties over time. This work estimates air leakage through concrete porosity for structures by using data obtained in field combined with stochastic finite element (SFE) modelling. For this purpose, a methodology is proposed to evaluate permeability under representative over-pressurization conditions based on in-field measurements under vacuum. This makes it possible to investigate the air leakage through the inner wall of a 1:3 scaled nuclear vessel named the VeRCoRs mock-up. Measurements are made for over 80 points scattered on the external face of the inner wall of the structure. Based on the data collected, a statistical analysis quantifies the spatial variation of permeability and contributes to the building of an SFE model of air leakage at the structural scale. Measured and predicted data are in good agreement on the service life of the structure. This shows the relevance of combining in-field measurements during an operational phase and the SFE modelling for better evaluation of the structural performance. The lessons learnt from the present work could be useful for the assessment of all structures with durability or mechanical issues that induce a continuous loss of tightness. [ABSTRACT FROM AUTHOR]

Drying and creep are mainly driving the continuous strain evolution in time of aging large prestressed concrete structures, and may jeopardize the safety of their environment. Therefore, it is crucial to dispose of an accurate assessment of structures' long-term strain level so as to evaluate their integrity. In the framework of probabilistic modeling of the delayed mechanical analysis of aging concrete structures, Bayesian inference allows to update uncertainties related to input parameters of computational models through the assimilation of noisy monitoring data. In this paper, a Bayesian inference methodology aiming at updating uncertain parameters of computational models for large concrete structures is proposed. This methodology combines a powerful surrogate modeling technique named PC-PCE (Principal Component Polynomial Chaos Expansions) with the so-called BUS (Bayesian Updating with Structural reliability methods) framework, in order to efficiently draw samples from posterior distributions for a sensibly reduced computational cost. In particular, the methodology is based on a framework to account for model uncertainties and biases, which are usually disregarded in the existing literature related to large concrete structures, and it enables correction predictions through Bayesian inference. The proposed approach is illustrated through an application to a large aging prestressed concrete structure, namely a 1:3 scale mock-up of a Nuclear Containment Building. In this context, a thermo-hydro-mechanical computational model with uncertain parameters is adopted to model the time evolution of strains of the structure. Results emphasize that the proposed approach performs Bayesian updating for a reduced computational cost. The proposed Bayesian inference approach also enables the identification of model biases, and correction of strain predictions. • Bayesian inference with correction of model bias and global variance-based sensitivity analysis for aging large containment structures. • Bayesian computations are performed with the Subset Simulation (SuS) algorithm. • Principal component polynomial chaos expansions are used to accelerate the SuS algorithm and computing Sobol' sensitivity indices. • A case study of a 1:3 scale nuclear containment building is presented. [ABSTRACT FROM AUTHOR]

The microstructure and corrosion behaviour in 0.1 M NaCl of the brass coating and solid brass are first determined. Obtained results indicate that their microstructure plays a significant role in dezincification and in the kinetics of the oxygen reduction. The results suggest that the coating is significantly affected by plastic deformation (microstructure, thickness). The corrosion behaviour of the pearlitic steel and the brass-coated pearlitic steel is then investigated after plastic deformation. The coating breakdown happens at a critical concentration of vacancies generated by dezincification in the ultra-thin parts of the coating. The substrate is then exposed to the solution. Hydrolysis of Fe 2+ induces a pH decrease, which can promote dezincification and then dissolution of the coating. Plastic deformation increases sharply the corrosion susceptibility of the pearlitic steel. [ABSTRACT FROM AUTHOR]

The influence of the grain tolerance angle (GTA) on the microstructural parameters of pearlitic steel is investigated using electron backscattered diffraction. The corrosion behavior of this alloy is then evaluated from local polarisation curves (electrochemical microcell technique) and potentiostatic pulse testing. These results are analyzed according to the specimen microstructure (grain boundaries and grain orientation spread, GOS). It is shown that there is a critical value of the GOS (around 10°) leading to significant decrease of the pitting potential. The influence of the GTA value on the analysis of electrochemical results is also discussed. [ABSTRACT FROM AUTHOR]

Leak tightness of concrete containment structures such as Nuclear Containment Buildings (NCB) plays a key role in their serviceability and the safety of their surrounding environment. Under the action of operating loads and aging process, leak tightness may evolve over time, which makes numerical forecasting strategies a crucial tool for improving anticipation of overpassing threshold limits, as well as decision aid in the framework of containment structures maintenance. In this paper, a Bayesian updating framework for NCB under serviceability loads is presented. Based on the Bayesian inference process, it allows to incorporate both mechanical and hydraulic NCB monitoring data to numerical predictions in a probabilistic framework, for updating a prior into a posterior state of knowledge related to model parameters. For computational purposes, the approach uses a Transitional Markov Chain Monte Carlo (TMCMC) algorithm for estimating the posterior distribution of model parameters. In order to provide a suitable approach for engineering practice in terms of computational cost, sparse Polynomial Chaos Expansions (PCE) are used for accelerating the TMCMC algorithm. The information gain resulting from Bayesian updating is quantified using a measure taken from information theory, namely the Kullback–Leibler Divergence (KLD). The proposed approach is illustrated through an application to a 1:3 scale NCB. By extracting information from various auscultation data of the structure, the knowledge on uncertain parameters of a complex finite element model is updated throughout the structure operational phase, and new predictions of the structure's strains and leakage responses are subsequently performed. • A Bayesian updating framework for nuclear containment buildings is presented. • Predictions are updated using both mechanical and leakage monitoring data. • A Transitional MCMC algorithm is used for Bayesian updating. • Sparse Polynomial Chaos Expansions are used to accelerate the TMCMC algorithm. • A case study of a 1:3 scale nuclear containment building is presented. [ABSTRACT FROM AUTHOR]

• Bayesian updating methodology for Thermo-Hydro-Mechanical-Leakage modeling strategies. • Coupling of Bayesian updating with a scale reduction method allowing 1D calculations. • Application to a 1:3 nuclear containment building. • Use of Polynomial Chaos Expansions coupled with a Markov Chain Monte Carlo method. • Sequential updating of leakage forecasts along the structure operational phase. The forecast of large concrete structures behavior such as Nuclear Containment Buildings (NCB) is a critical safety issue, whether for the structure itself or for its surrounding environment. Over the past few decades, complex finite element models have been developed for assessing the mechanical behavior and the leak tightness of large concrete structures. These models involve numerous parameters known with uncertainties, which importance could jeopardize the reliability of forecasts. Therefore, this contribution aims to present a weakly coupled Thermo-Hydro-Mechanical-Leakage methodology to forecast the evolution of dry air tightness of large concrete structures. The proposed approach is based on a Bayesian updating strategy aiming to reduce uncertainties on forecasts by combining information provided by both a physical model and in situ observations acquired up to date. The Bayesian strategy is coupled with a scale reduction method for ensuring applicability at the scale of large structures. The methodology is applied to a 1:3 scale NCB, in order to improve confidence level of leakage rate forecasts by taking advantage of monitoring measurements. The forecasted leakage rates are in good agreement with the measurements, and the proposed methodology enables to significantly reduce the uncertainty throughout the operational phase of the structure, even with a limited amount of monitoring data. [ABSTRACT FROM AUTHOR]