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Landform detection and analysis from Digital Elevation Models (DEM) of the Earth has been boosted by the availability of high-quality public data sets. Current landform identification methods apply heuristic algorithms based on predefined landform features, fine tuned with parameters that may depend on the region of interest. In this paper, we investigate the use of Deep Learning (DL) models to identify mountain summits based on features learned from data examples. We train DL models with the coordinates of known summits found in public databases and apply the trained models to DEM data obtaining as output the coordinates of candidate summits. We introduce two formulations of summit recognition (as a classification or a segmentation task), describe the respective DL models, compare them with heuristic methods quantitatively, illustrate qualitatively their performances, and discuss the challenges of training DL methods for landform recognition with highly unbalanced and noisy data sets.

The rapid development of remote sensing technologies and the availability of many satellite and aerial sensors have boosted the collection of large volumes of high-resolution images, promoting progress in a wide range of applications. As a consequence, Object detection (OD) in aerial images has gained much interest in the last few years. However, the development of object detectors requires a massive amount of carefully labeled data. Since annotating datasets is very time-consuming and may require expert knowledge, a consistent number of weakly supervised object localization (WSOL) and detection (WSOD) methods have been developed. These approaches exploit only coarse-grained metadata, typically whole image labels, to train object detectors. However, many challenges remain open due to the missing location information in the training process of WSOD approaches and to the complexity of remote sensing images. Furthermore, methods studied for natural images may not be directly applicable to remote sensing images (RSI) and may require carefully designed adaptations. This work provides a comprehensive survey of the recent achievements of remote sensing weakly supervised object detection (RSWSOD). An analysis of the challenges related to RSWSOD is presented, the advanced techniques developed to improve WSOD are summarized, the available benchmarking datasets are described and a discussion of future directions of RSWSOD research is provided.

Thousands of rural houses in developing countries with high seismicity were built without adequate seismic protection due to economical reason. This paper discusses a possibility to improve the seismic protection of typical unreinforced masonry in developing regions using low cost base isolation devices. The proposed isolation system involves fibre reinforced elastomeric isolators (FREIs) having small dimensions and few layers of rubber pads to reduce the fabrication cost. A series of 3D FE simulations are carried out to investigate the performances of the proposed FREIs utilised in the isolation of a one story masonry house prototype. The model is assumed subjected to several accelerograms to have an insight into the sensitivity of the isolation system against different earthquakes. The results reveal that the proposed low cost FREI system provides significant damage mitigation to the masonry house with good applicability of the FREI devices.

Rubber recycling technology has been a popular issue in many research fields considering huge amount rubber waste in the environment. This paper discusses an application of reactivated ethylene propylene diene monomer (EPDM) to fabricate fiber reinforced elastomeric isolators (FREIs), which is considered as a low cost seismic protection device. Two types of regenerated EPDM are considered to be blended with two different virgin rubber, Vistalon 3666 and Dutral 4038. The first is used to produce a compound with the hardness around 30 Shore A, while the latter 60 Shore A. A series of experimental tests are performed including rheometer, shore A hardness, compression set and uniaxial tensile test. The results show that the compounds with reactivated EPDM type B present the most satisfactory performance, before and after ageing. This paper discusses also the method in fabricating FREIs, made of the selected recycled rubber and the glass fiber reinforced polymer (GFRP). The hardness test performed on the sliced FREI specimen indicates that the vulcanization temperature used in the production is roughly suitable to obtain the expected rubber properties.

Iconography studies the visual content of artworks by considering the themes portrayed in them and their representation. Computer Vision has been used to identify iconographic subjects in paintings and Convolutional Neural Networks enabled the effective classification of characters in Christian art paintings. However, it still has to be demonstrated if the classification results obtained by CNNs rely on the same iconographic properties that human experts exploit when studying iconography and if the architecture of a classifier trained on whole artwork images can be exploited to support the much harder task of object detection. A suitable approach for exposing the process of classification by neural models relies on Class Activation Maps, which emphasize the areas of an image contributing the most to the classification. This work compares state-of-the-art algorithms (CAM, Grad-CAM, Grad-CAM++, and Smooth Grad-CAM++) in terms of their capacity of identifying the iconographic attributes that determine the classification of characters in Christian art paintings. Quantitative and qualitative analyses show that Grad-CAM, Grad-CAM++, and Smooth Grad-CAM++ have similar performances while CAM has lower efficacy. Smooth Grad-CAM++ isolates multiple disconnected image regions that identify small iconographic symbols well. Grad-CAM produces wider and more contiguous areas that cover large iconographic symbols better. The salient image areas computed by the CAM algorithms have been used to estimate object-level bounding boxes and a quantitative analysis shows that the boxes estimated with Grad-CAM reach 55% average IoU, 61% GT-known localization and 31% mAP. The obtained results are a step towards the computer-aided study of the variations of iconographic elements positioning and mutual relations in artworks and open the way to the automatic creation of bounding boxes for training detectors of iconographic symbols in Christian art images.

Iconography in art is the discipline that studies the visual content of artworks to determine their motifs and themes andto characterize the way these are represented. It is a subject of active research for a variety of purposes, including the interpretation of meaning, the investigation of the origin and diffusion in time and space of representations, and the study of influences across artists and art works. With the proliferation of digital archives of art images, the possibility arises of applying Computer Vision techniques to the analysis of art images at an unprecedented scale, which may support iconography research and education. In this paper we introduce a novel paintings data set for iconography classification and present the quantitativeand qualitative results of applying a Convolutional Neural Network (CNN) classifier to the recognition of the iconography of artworks. The proposed classifier achieves good performances (71.17% Precision, 70.89% Recall, 70.25% F1-Score and 72.73% Average Precision) in the task of identifying saints in Christian religious paintings, a task made difficult by the presence of classes with very similar visual features. Qualitative analysis of the results shows that the CNN focuses on the traditional iconic motifs that characterize the representation of each saint and exploits such hints to attain correct identification. The ultimate goal of our work is to enable the automatic extraction, decomposition, and comparison of iconography elements to support iconographic studies and automatic art work annotation., Published at ACM Journal on Computing and Cultural Heritage (JOCCH) https://doi.org/10.1145/3458885

The vulcanization process of a low cost parallelepiped seismic rubber isolation device is studied from a numerical standpoint. The seismic isolator is constituted by few rubber pads made by regenerated rubbed and EPDM and -instead of steel laminas-GFRP sheets are utilized to reduce further the production cost. Such cheap device, assuming also its installation without head and foot connecting steel plates, is particularly suited for the isolation of low rise masonry buildings in developing countries. A refined FE discretization is utilized to predict the temperature-time histories that each point of the device exhibits during a standard vulcanization in an industrial oven. The knowledge of the temperature profiles is mandatory to predict the local final vulcanization degree, once that a suitable vulcanization model is at disposal. From simulations results, it is found how the utilization of steel laminas-thanks to their high thermal conductivity-allows a much faster and homogeneous vulcanization inside the bulk, whereas the introduction of pultruded GFRP sheets is equivalent to the vulcanization of a single thick rubber pad. As a consequence, in this latter case there is the need to extend curing to long vulcanization times, always associated to over-vulcanization of the skin and under-vulcanization of the core.

Introduction:An advanced Finite Element model is presented to examine the performance of a low-cost friction based-isolation system in reducing the seismic vulnerability of low-class rural housings. This study, which is mainly numerical, adopts as benchmark an experimental investigation on a single story masonry system eventually isolated at the base and tested on a shaking table in India.Methods:Four friction isolation interfaces, namely, marble-marble, marble-high-density polyethylene, marble-rubber sheet, and marble-geosynthetic were involved. Those interfaces differ for the friction coefficient, which was experimentally obtained through the aforementioned research. The FE model adopted here is based on a macroscopic approach for masonry, which is assumed as an isotropic material exhibiting damage and softening. The Concrete damage plasticity (CDP) model, that is available in standard package of ABAQUS finite element software, is used to determine the non-linear behavior of the house under non-linear dynamic excitation.Results and Conclusion:The results of FE analyses show that the utilization of friction isolation systems could much decrease the acceleration response at roof level, with a very good agreement with the experimental data. It is also found that systems with marble-marble and marble-geosynthetic interfaces reduce the roof acceleration up to 50% comparing to the system without isolation. Another interesting result is that there was little damage appearing in systems with frictional isolation during numerical simulations. Meanwhile, a severe state of damage was clearly visible for the system without isolation.

A very simple kinetic model for natural rubber (NR) and polybutadiene (PB) blends is presented. The model is characterized by a completely uncoupled curing between NR and PB, NR being modeled with a primary vulcanization and a subsequent de-vulcanization and PB only by a simple first order model of vulcanization. The assumptions made are roughly in agreement with the actual experimental behavior of the constituent materials in a rheometer chamber, where PB exhibits a quite stable behavior even at high curing temperatures and long vulcanization times. As a result of the simplifications assumed into the curing model adopted, the numerical approach uses only on three kinetic constants, two for NR and one for PB. Such assumptions allow for a quite straightforward determination of the kinetic constants by means of a simple semi-analytical approach. The reliability of the procedure proposed is benchmarked on some 70% NR- 30% PB blends with two different accelerants (N-terbutyl, 2-benzothiazylsulfenamide TBBS and N,N-diphenylguanidine DPG) in different concentrations tested experimentally on a standard rheometer chamber at 170 and 180 °C. Quite good match is found between numerical predictions and normalized rheometer curves, with a clear practical impact into the Finite Element FE modelling of vulcanization of real items.

Analyzing digital data to identify and classify landforms is an important task, which can contribute to improve the availability and quality of public open source cartography and to develop novel applications for tourism and environment monitoring. In the literature, several heuristic algorithms are documented for identifying the features of mountain regions, most notably the coordinates of summits, from input data set, such as the Digital Elevation Model (DEM) of the Earth. Choosing the method to use for mountain peaks detection depends on the requirements of the application at hand, but the decision is helped also by the availability of rigorous comparison among the different methods. In this paper, we propose an approach for such a comparison and present the results obtained evaluating the best known methods form the literature in an area of Switzerland.

A simple and versatile numerical approach of experimental data regularization plus a kinetic model to predict the vulcanization behavior in a rheometer for natural rubber (NR) and poly-butadiene (PB) blends is presented. The numerical model proposed uses generic rheometer experimental curves to estimate kinetic constants of the cure reactions, preliminarily regularizing input data through Cn continuous polynomial splines of degree n, with spline knots equally spaced or placed at user’s discretion. Splines coefficients are efficiently evaluated through a standard non-linear least squares optimization procedure. In this way a set of meta-data fitting optimally experimental values is obtained, with a smooth prediction of the local curing rate. The kinetic approach adopted is classic but adaptable to a wide class of cases and characterized by only three kinetic constants, describing two reactions occurring in parallel and two in series (reversion phenomenon). The determination of the three kinetic constants characterizing the model is performed graphically in quasi analytical form. The model is benchmarked by means of an ad-hoc conducted experimental campaign carried out with different typologies of rubber blends constituted by NR and PB at 70–30% and 50–50% concentrations, with sulfur at 1 phr and two accelerants (TBSS and DPG) at 1 and 3 phr, under standard vulcanization conditions (rheometer) at 150 °C, 170 °C and 180 °C.

This paper presents a series of experimentations and numerical modeling to evaluate the damping of rubber for seismic isolation purposes. A cyclic shear test is considered as a standard procedure to evaluate the damping of rubber materials. However, there is another method to evaluate the viscous damping of rubber by means of relaxation test that requires only small dumb-bell specimens of rubber, using a uniaxial tensile test device. This method allows an efficient procedure in examining the mechanical characteristic of rubber for seismic isolation purposes. This paper evaluates such a procedure to characterize the mechanical properties of a low damping rubber. The result shows that the proposed procedure presents a good prediction of the mechanical properties of the rubber.

A novel mathematical approach to predict the vulcanization degree of high-cis polybutadiene rubber vulcanized with sulphur is presented. The model has kinetic base, it is constituted by four reactions occurring in series and parallel and takes contemporarily into consideration, within a simplified but reliable scheme, the actual reactions occurring during polybutadiene sulphur curing, namely primary crosslinking and possible de-vulcanization. The first order differential equation system obtained is suitably rearranged and a closed form expression for the vulcanization degree is derived, depending the four kinetic constants characterizing the chemistry describing reactions. Instead of using classic least-squares optimization routines to characterize kinetic constants on experimental data, a simplified but reliable approach is proposed, where a system of four non-linear equations is solved with a recursive strategy, allowing estimating kinetic constants that proved to fit well normalized experimental data. The procedure is fast and its reliability is tested on a number of experimental data available, relying into a high-cis polybutadiene rubber cured under different temperatures and accelerators concentrations. Very good approximations of experimental data are obtained, also in comparison with a heuristic numerical approach where optimization is obtained interactively.

Due to the need for seismic protection in developing countries, some investigations on low-cost seismic isolators have been performed. One of them is an unbonded fiber reinforced elastomeric isolator (UFREI), in which the bearing is not bonded to the supports. This type allows the application of base isolation without any expensive thick-steel plate for supports. The UFREI is considerably effective for utilization on low-rise buildings, even masonry housings. Advantageous features of the UFREI are the roll-over and full-contact deformations. The former can decrease the effective stiffness of the isolation system, lowering the seismic force demand. Meanwhile, the latter plays a role in generating a hardening effect, limiting the shear displacement of the base isolation under a maximum earthquake. Those remarkable advantages reveal a great potency of world-wide application of UFREIs. However, there is no representative model of UFREI in the various software of structural analyses. In this work, a comprehensive but simple model of UFREI is implemented in an ABAQUS user element (UEL), taking into account the softening, hardening, and hysteresis effects of the bearing. In addition, multiple DOFs are considered to characterize the complex 3D behavior of a UFREI in lateral, axial, rotations, and torsion. The results show that the UEL model can reasonably fit the finite element model of a referenced UFREI. The proposed UEL model is helpful in 3D analyses of isolated structures using UFREIs.

An integrated simulation tool for the optimal vulcanization of tires is presented. Three are the main issues discussed on the optimal vulcanization of 3D items with complex geometry, namely: (i) the results of a preliminary realistic experimental campaign on rubber blends constituted by NR and PB in two different proportions and cured with different accelerators; (ii) a phenomenological numerical smoothing and kinetic model of interpretation of the rheometer curves experimentally obtained; (iii) the implementation of the numerical model into a commercial FE software to simulate the optimal vulcanization of car tires industrially produced. The experimental campaign is carried out on different typologies of rubber blends constituted by NR and PB at 70-30% and 50-50% concentrations, with sulfur at 1 phr and two accelerants (TBSS and DPG) at 1 and 3 phr, under standard vulcanization conditions (rheometer) at 150°, 170° and 180 °C. The numerical kinetic model uses such rheometer experimental curves to estimate kinetic constants of the cure reactions, preliminarily smoothing input data through four C1 cubic splines, with spline knots interactively selected by the user with a mouse click. Position of knots and vulcanization rates in correspondence of knots are then adjusted automatically by means of a non-linear least squares optimization procedure. In this way a set of meta-data (fitting optimally experimental values) is obtained, with a smooth prediction of the local curing rate. The kinetic approach used is characterized by three kinetic constants, describing two reactions occurring in parallel and in series and suitably accounting for possible reversion. The determination of the three kinetic constants characterizing the model is performed graphically in a quasi-analytical form. The numerical model is then nested into a Finite Element FE commercial code, to predict the crosslinking degree in real curing conditions, i.e. where the temperature is not constant. A real tire is finally analyzed during the curing process and useful indications are provided on the optimal curing temperature and time to adopt.

Seismic isolation is an effective technical solution to reduce the vulnerability of new and existing structures. It can mitigate the negative impact of an earthquake by shifting the period of the structure in that range of the spectrum where the spectral acceleration is low. A well known and relatively cheap seismic isolation device is the so-called elastomeric isolator. The fabrication cost of such isolator can be reduced by the utilization of fiber lamina instead of steel. In this work, finite element (FE) modeling of fiber reinforced elastomeric isolators is discussed. In numerical modelling, the main characteristic of elastomeric materials is the hyperelasticity, which can be taken into account in the commercial FE code that was used in the present study (namely ABAQUS). In this paper, an interesting issue highlighted is the mesh verification on FE models of an elastomeric material embedded into a seismic isolator.Seismic isolation is an effective technical solution to reduce the vulnerability of new and existing structures. It can mitigate the negative impact of an earthquake by shifting the period of the structure in that range of the spectrum where the spectral acceleration is low. A well known and relatively cheap seismic isolation device is the so-called elastomeric isolator. The fabrication cost of such isolator can be reduced by the utilization of fiber lamina instead of steel. In this work, finite element (FE) modeling of fiber reinforced elastomeric isolators is discussed. In numerical modelling, the main characteristic of elastomeric materials is the hyperelasticity, which can be taken into account in the commercial FE code that was used in the present study (namely ABAQUS). In this paper, an interesting issue highlighted is the mesh verification on FE models of an elastomeric material embedded into a seismic isolator.

A robust kinetic numerical model for natural rubber NR–poly-butadiene PB blends vulcanized with sulfur is presented. For a preliminary experimental insight used then as benchmark, a 70% NR with 30% high-cis PB blend vulcanized in presence of sulfur and two accelerants (TBSS and DPG) in different concentrations is tested under standard vulcanization conditions (rheometer) at three different vulcanization temperatures, namely 150, 170 and 180 °C. The numerical model reproduces normalized experimental rheometer curves using a Han’s kinetic model for NR and a modification of the Han’s model proposed recently by the authors for PB. The model bases therefore on existing kinetic approaches that proved to be effective for NR and PB separately, but merging them linearly to cope with NR–PB peculiar reactions occurring in a blend. Han’s model depends on three rate constants, whereas the approach used for PB is characterized by four kinetic parameters. The linear interaction between PB and NR (with amount of rubber involved not a priori known) is again assumed ruled by a Han’s model. The mathematical approach proposed is therefore characterized by 10 rate constants plus an additional parameter represented by NR–PB concentration involved by the interaction. Such constants are estimated by standard best fitting against experimental data. Quite good match is found, showing that the procedure may be useful for practical purposes in all those cases where expensive experimental investigations are not possible.

New residential buildings in developing countries often have inadequate seismic protection, particularly for masonry. Such material is widely preferred because the cost and application are relatively cheap. To decrease the vulnerability, an interesting option is represented by seismic isolation, but the cost should remain relatively low, and this is the reason why rubber isolation with few pads remains the most suitable technical solution to adopt. In this study, we deal with a newly conceived low-cost seismic isolation system for masonry buildings relying on elastomeric bearings. The elastomeric isolator here proposed consists of few layers of rubber pads and fiber lamina, making it cheaper comparing to the conventional isolators. A detailed 3D finite element (FE) analysis to predict the behavior of the low-cost rubber isolator undergoing moderate deformations is carried out. A Yeoh hyperelasticity model with coefficients estimated through available experimental data is assumed for rubber pads. Having so derived the shear behavior, such isolation system is implemented at a structural level into a two stories masonry house prototype, identifying the 3D model with a damped nonlinear spring model, so making the FE analysis computationally inexpensive. For masonry, a concrete damage plasticity (CDP) model available in the commercial FE code Abaqus is adopted. A nonlinear static-pushover analysis is conducted to assess the performance of the isolated building. To simulate a realistic condition under seismic event, a ground motion data is applied to observe the dynamic behavior of the building by monitoring the damage level of masonry. Through a-posterior estimation, it is also possible to monitor the deformation of the isolators during the seismic excitation, to determine whether the isolator is capable of resisting shear deformations in different angles. According to the results obtained, quite good isolation is obtained with the system proposed, with immediate applicability at a structural level.

The paper presents a novel efficient closed form approach to determine the degree of vulcanization of natural rubber (NR) vulcanized with sulphur in presence of different accelerators. The general reaction scheme proposed by Han and co-workers for vulcanized sulphur NR is re-adapted and suitably modified taking into account the single contributions of the different accelerators, focusing in particular on some experimental data, where NR was vulcanized at different temperatures (from 150 to $$180\, ^{\circ }\hbox {C}$$ ) and concentrations of sulphur, using TBBS and DPG in the mixture as co-agents at variable concentrations. In the model, chain reactions initiated by the formation of macro-compounds responsible for the formation of the unmatured crosslinked polymer are accounted for. It is assumed that such reactions depend on the reciprocal concentrations of all components and their chemical nature. In presence of two accelerators, reactions are assumed to proceed in parallel, making the assumption that there is no interaction between the two accelerators. Despite there is experimental evidence that a weak process by which each accelerator affects the other, the reaction chemistry is still not well understood and therefore its effect cannot be translated into any mathematical model. In any case, even disregarding such interaction, good approximations of the rheometer curves are obtained. From the simplified kinetic scheme adopted, a closed form solution is found for the crosslink density, with the only limitation that the induction period is excluded from computations. The main capability of the model stands however in the closed form determination of kinetic constants representing the velocities of single reactions in the kinetic scheme adopted, which allows avoiding a numerically demanding least-squares best fitting on rheometer experimental data. Two series of experiments available, relying into rheometer curves at different temperatures and different concentrations of sulphur and accelerators, are utilized to evaluate the fitting capabilities of the mathematical model. Very good agreement between numerical output and experimental data is experienced in all cases analyzed.

Rubber isolators are used widely in constructions which require a vibration or seismic isolation. It consists of rubber layers and reinforcements that can be steel or fiber lamina. The fiber reinforced isolator results in a lower cost of production and application than that of steel. Using fiber reinforced isolator allows us to make an unbonded model of rubber bearing. This model leads to a smaller horizontal stiffness and larger displacement of isolators. Researchers consider the Unbonded Fiber Reinforced Elastomeric Isolator (U-FREI) as a low-cost form of rubber bearings. U-FREIs are suitable to isolate seismically a masonry building, which is a common type of housing in developing countries. In this work, we present a finite element model (FEM) to predict the behavior of the U-FREIs undergoing moderate deformations. We adopt a Yeoh hyperelasticity model which is available in the standard package of Abaqus FE software and estimate its coefficients through the available experimental data. Then, we apply that isolation system onto masonry housing with some simplified methods. We also observe the horizontal behaviors of U-FREIs under different vertical loads and consider a critical condition when the isolators start to be unstable. In parallel, we perform an analytical model to predict the shear behavior and the deformation limit of isolators. Finally, the results show that the analytical model is sufficiently accurate compared to the FE analyses.Rubber isolators are used widely in constructions which require a vibration or seismic isolation. It consists of rubber layers and reinforcements that can be steel or fiber lamina. The fiber reinforced isolator results in a lower cost of production and application than that of steel. Using fiber reinforced isolator allows us to make an unbonded model of rubber bearing. This model leads to a smaller horizontal stiffness and larger displacement of isolators. Researchers consider the Unbonded Fiber Reinforced Elastomeric Isolator (U-FREI) as a low-cost form of rubber bearings. U-FREIs are suitable to isolate seismically a masonry building, which is a common type of housing in developing countries. In this work, we present a finite element model (FEM) to predict the behavior of the U-FREIs undergoing moderate deformations. We adopt a Yeoh hyperelasticity model which is available in the standard package of Abaqus FE software and estimate its coefficients through the available experimental data. Then, we apply ...

A Parabola-Hyperbola (P-H) kinetic model for NR sulphur vulcanization is presented. The idea originates from the fitting composite Parabola-Parabola-Hyperbola (P-P-H) function used by the authors in [1,2] to approximate experimental rheometer curves with the knowledge of a few key parameters of vulcanization, such as the scorch point, initial vulcanization rate, 90% of vulcanization, maximum point and reversion percentage. After proper normalization of experimental data (i.e. excluding induction and normalizing against maximum torque), the P-P-H model reduces to the discussed P-H composite function, which is linked to the kinetic scheme originally proposed by Han and co-workers [3]. Typically, it is characterized by three kinetic constants, where classically the first two describe incipient curing and stable/instable crosslinks and the last reproduces reversion. The powerfulness of the proposed approach stands into the very reduced number of input parameters required to accurately fit normalized experimental data (i.e. rate of vulcanization at scorch, vulcanization at 90%, maximum point and reversion percentage), and the translation of a mere geometric data-fitting into a kinetic model. Kinetic constants knowledge from simple geometric fitting allows characterizing rubber curing also at temperature different from those experimentally tested. The P-H model can be applied also in the so-called backward direction, i.e. assuming Han's kinetic constants known from other models and deriving the geometric fitting parameters as result. Some existing experimental data available, relying into rheometer curves conducted at 5 different temperatures on the same rubber blend are used to benchmark the P-H kinetic approach proposed, in both backward and forward direction. Very good agreement with previously presented kinetic approaches and experimental data is observed.

A Finite element model was established to examine performance of a low-cost friction base-isolation system in reducing seismic vulnerability of rural buildings. This study adopts an experimental investigation of the isolation system which was conducted in India. Four friction isolation interfaces, namely, marble-marble, marble-high-density polyethylene, marble-rubber sheet, and marble-geosynthetic were involved. Those interfaces differ in static and dynamic friction coefficient obtained through previous research. The FE model was performed based on a macroscopic approach and the masonry wall is assumed as an isotropic element. In order to observe structural response of the masonry house, elastic and plastic parameters of the brick wall were studied. Concrete damage plasticity (CDP) model was adopted to determine non-linear behavior of the brick wall. The results of FE model shows that involving these friction isolation systems could much decrease response acceleration at roof level. It was found that systems with marble-marble and marble-geosynthetic interfaces reduce the roof acceleration up to 50% comparing to the system without isolation. Another interesting result is there was no damage appearing in systems with friction isolation during the test. Meanwhile a severe failure was clearly visible for a system without isolation.A Finite element model was established to examine performance of a low-cost friction base-isolation system in reducing seismic vulnerability of rural buildings. This study adopts an experimental investigation of the isolation system which was conducted in India. Four friction isolation interfaces, namely, marble-marble, marble-high-density polyethylene, marble-rubber sheet, and marble-geosynthetic were involved. Those interfaces differ in static and dynamic friction coefficient obtained through previous research. The FE model was performed based on a macroscopic approach and the masonry wall is assumed as an isotropic element. In order to observe structural response of the masonry house, elastic and plastic parameters of the brick wall were studied. Concrete damage plasticity (CDP) model was adopted to determine non-linear behavior of the brick wall. The results of FE model shows that involving these friction isolation systems could much decrease response acceleration at roof level. It was found that syst...

A fast and reliable meta-model for NR vulcanized with sulphur in standard rheometer chambers is presented. The model requires only very little input information at a fixed vulcanization temperature, as for instance scorch time, t 90 and percentage reversion. It provides kinetic constants of the single reactions occurring during the curing process as output, within the assumptions of a suitable mechanistic model. The meta-model is subdivided into two phases, the first characterized by construction of experimental meta-data from limited rheometer information, and the second by the determination of partial reaction kinetic constants characterizing the vulcanization process, assuming those obtained in the previous phase with the meta-model as experimental data to fit. Meta-data are obtained using a very straightforward C 2 natural cubic spline interpolation of the rheometer curve, which is shown to fit the experimental data well. Both the presence and absence of reversion are discussed and how they are reflected in the model calculations. In step two, a simple new closed form equation representing the degree of vulcanization of NR cured with sulphur is deduced, where kinetic parameters are numerically determined through non-linear least squares fitting of meta-data determined previously. The closed form solution is derived from a set of first order differential equations representing the partial reactions occurring during curing. To assess the results obtained with the model proposed, several examples of the same blend in the presence of different accelerators, for which minimal experimental information was available from the literature, are analysed. In some cases, moderate to strong reversion was present. The procedure proved to be very fast and reliable and has the advantage of providing, for the single cases analysed, partial reaction kinetic constants.

A novel kinetic model of natural rubber sulphur vulcanization is proposed. The modeling approach takes into account current knowledge on the different polysulfidic structures present during vulcanization, and the associated individual reactions. A simplified scheme is proposed, giving a mechanistic view of the reversion phenomenon, which results in a decrease of the elastic modulus (related to the sulphur crosslink density) for long vulcanization times at high temperature. The resulting set of differential equations is solved by an appropriate numerical method to predict the evolution of the degree of vulcanization for isothermal cure conditions. The vulcanization kinetics of a model natural rubber compound was characterized experimentally by rheological measurements, in order to test the proposed kinetic model. A remarkable agreement between model predictions and experimental data is observed. The identified kinetic parameters corresponding to the individual reactions taken into account by the mechanistic model are consistent with those of an existing, less refined, pseudo-mechanistic model. The proposed model thus allows bridging the gap between the prediction of macroscopic variations of the elastic modulus and the evolution of molecular scale structure during vulcanization when the reversion phenomenon is present.

This work presents a comprehensive numerical model to optimize mechanical properties of thick rubber vulcanized items, comprising medium and high voltage electric cables and three-dimensional devices. Several vulcanization systems are considered, including peroxides and accelerated sulfur. For peroxides, both a genetic algorithm (GA) and an alternating tangent (AT) approach are adopted to determine the optimal final mechanical properties (tensile strength) of rubber items. The use of a mixture of peroxides is also considered, demonstrating that balanced mixtures may help in reducing the curing time and/or in increasing the optimal tensile strength in both core and skin of thick devices. For sulfur vulcanization, a mathematical kinetic model is presented to predict the cross-linking density of vulcanized rubber. The model is conceived to fit experimental rheometer data, and it is suitable to have an estimate of cross-linking degree at fixed temperature. The model requires a parametric calibration by means of only three kinetic constants, successively implemented in Finite Element (FE) software, specifically developed to perform thermal analyses on two-dimensional geometries. As an example, an extruded cylindrical thick EPDM item is considered and meshed through four-noded isoparametric plane elements. Several FE simulations are repeated changing both exposition time, tc, and external curing temperature, Tc, to evaluate for each (tc, Tc) couple the corresponding mechanical properties of the item at the end of the thermal treatment.