Search results for: inverse synthetic aperture radar

Authors: Osman Acar

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Sun tracking systems are the systems following the sun ray by a right angle or by predetermined certain angle. In this study, we used theoretical trajectory of sun for latitude of central Anatolia in Turkey. A two degree of freedom spherical mechanism was designed to have a large workspace able to follow the sun's theoretical motion by the right angle during the whole year. An inverse kinematic analysis was generated to find the positions of mechanism links for the predicted trajectory. Force and torque analysis were shown for the first day of the year.

Keywords: sun tracking, theoretical sun trajectory, spherical mechanism, inverse kinematic analysis

Procedia PDF Downloads 386

Authors: Zatil Afifah Omar, Siti Nur Izati Azmi, Kathi Swaran, Navin Kumar

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Lost circulation has always been one of the greatest problems faced by drilling companies during drilling operations due to excessive drilling Fluids losses. Loss of circulation leads to Huge cost and non-productive time. The objective of this study is to evaluate the sealing efficiency of a proprietary blend of synthetic rubber as loss circulation material in comparison with a conventional product such as calcium carbonate, graphite, cellulosic, and nutshells. Sand Bed Tester with a different proprietary blend of synthetic rubber compositions has been used to determine the effectiveness of the LCM in preventing drilling fluids losses in a lab scale. Test results show the proprietary blend of synthetic rubber have good bridging properties and sealing Off fractures of various sizes. The finish product is environmentally friendly with lower production lead time and lower production cost compared to current conventional loss circulation materials used in current drilling operations.

Keywords: loss circulation materials, drilling operation, sealing efficiency, LCM

Procedia PDF Downloads 159

Authors: Ashkan Shafee, Ahamd Fahimifar, Sajjad V. Maghvan

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Promotion of the Fiber Reinforced Concrete (FRC) as a construction material for civil engineering projects has invoked numerous researchers to investigate their mechanical behavior. Even though there is satisfactory information about the effects of fiber type and length, concrete mixture, casting type and other variables on the strength and deformability parameters of FRC, the numerical modeling of such materials still needs research attention. The focus of this study is to investigate the feasibility of Concrete Damaged Plasticity (CDP) model in prediction of Macro-synthetic FRC structures behavior. CDP model requires the tensile behavior of concrete to be well characterized. For this purpose, a series of uniaxial direct tension and four point bending tests were conducted on the notched specimens to define bilinear tension softening (post-peak tension stress-strain) behavior. With these parameters obtained, the flexural behavior of macro-synthetic FRC beams were modeled and the results showed a good agreement with the experimental measurements.

Keywords: concrete damaged plasticity, fiber reinforced concrete, finite element modeling, macro-synthetic fibers, uniaxial tensile test

Procedia PDF Downloads 387

Authors: Riadh Zorgati, Thomas Triboulet

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In quite diverse application areas such as astronomy, medical imaging, geophysics or nondestructive evaluation, many problems related to calibration, fitting or estimation of a large number of input parameters of a model from a small amount of output noisy data, can be cast as inverse problems. Due to noisy data corruption, insufficient data and model errors, most inverse problems are ill-posed in a Hadamard sense, i.e. existence, uniqueness and stability of the solution are not guaranteed. A wide class of inverse problems in physics relates to the Fredholm equation of the first kind. The ill-posedness of such inverse problem results, after discretization, in a very ill-conditioned linear system of equations, the condition number of the associated matrix can typically range from 109 to 1018. This condition number plays the role of an amplifier of uncertainties on data during inversion and then, renders the inverse problem difficult to handle numerically. Similar problems appear in other areas such as numerical optimization when using interior points algorithms for solving linear programs leads to face ill-conditioned systems of linear equations. Devising efficient solution approaches for such system of equations is therefore of great practical interest. Efficient iterative algorithms are proposed for solving a system of linear equations. The approach is based on a preconditioning of the initial matrix of the system with an approximation of a generalized inverse leading to a stochastic preconditioned matrix. This approach, valid for non-negative matrices, is first extended to hermitian, semi-definite positive matrices and then generalized to any complex rectangular matrices. The main results obtained are as follows: 1) We are able to build a generalized inverse of any complex rectangular matrix which satisfies the convergence condition requested in iterative algorithms for solving a system of linear equations. This completes the (short) list of generalized inverse having this property, after Kaczmarz and Cimmino matrices. Theoretical results on both the characterization of the type of generalized inverse obtained and the convergence are derived. 2) Thanks to its properties, this matrix can be efficiently used in different solving schemes as Richardson-Tanabe or preconditioned conjugate gradients. 3) By using Lp norms, we propose generalized Kaczmarz’s type matrices. We also show how Cimmino's matrix can be considered as a particular case consisting in choosing the Euclidian norm in an asymmetrical structure. 4) Regarding numerical results obtained on some pathological well-known test-cases (Hilbert, Nakasaka, …), some of the proposed algorithms are empirically shown to be more efficient on ill-conditioned problems and more robust to error propagation than the known classical techniques we have tested (Gauss, Moore-Penrose inverse, minimum residue, conjugate gradients, Kaczmarz, Cimmino). We end on a very early prospective application of our approach based on stochastic matrices aiming at computing some parameters (such as the extreme values, the mean, the variance, …) of the solution of a linear system prior to its resolution. Such an approach, if it were to be efficient, would be a source of information on the solution of a system of linear equations.

Keywords: conditioning, generalized inverse, linear system, norms, stochastic matrix

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Authors: Abdel Hadi Ebraheim

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This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

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Authors: George R. Puno, Eric N. Bruno

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The natural landscape of the Philippine archipelago plus the current realities of climate change make the country vulnerable to flood hazards. Flooding becomes the recurring natural disaster in the country resulting to lose of lives and properties. Musimusi is among the rivers which exhibited inundation particularly at the inhabited floodplain portion of its watershed. During the event, rescue operations and distribution of relief goods become a problem due to lack of high resolution flood maps to aid local government unit identify the most affected areas. In the attempt of minimizing impact of flooding, hydrologic modelling with high resolution mapping is becoming more challenging and important. This study focused on the analysis of flood extent as a function of different geomorphologic characteristics of Musimusi watershed. The methods include the delineation of morphometric parameters in the Musimusi watershed using Geographic Information System (GIS) and geometric calculations tools. Digital Terrain Model (DTM) as one of the derivatives of Light Detection and Ranging (LiDAR) technology was used to determine the extent of river inundation involving the application of Hydrologic Engineering Center-River Analysis System (HEC-RAS) and Hydrology Modelling System (HEC-HMS) models. The digital elevation model (DEM) from synthetic Aperture Radar (SAR) was used to delineate watershed boundary and river network. Datasets like mean sea level, river cross section, river stage, discharge and rainfall were also used as input parameters. Curve number (CN), vegetation, and soil properties were calibrated based on the existing condition of the site. Results showed that the drainage density value of the watershed is low which indicates that the basin is highly permeable subsoil and thick vegetative cover. The watershed’s elongation ratio value of 0.9 implies that the floodplain portion of the watershed is susceptible to flooding. The bifurcation ratio value of 2.1 indicates higher risk of flooding in localized areas of the watershed. The circularity ratio value (1.20) indicates that the basin is circular in shape, high discharge of runoff and low permeability of the subsoil condition. The heavy rainfall of 167 mm brought by Typhoon Seniang last December 29, 2014 was characterized as high intensity and long duration, with a return period of 100 years produced 316 m3s-1 outflows. Portion of the floodplain zone (1.52%) suffered inundation with 2.76 m depth at the maximum. The information generated in this study is helpful to the local disaster risk reduction management council in monitoring the affected sites for more appropriate decisions so that cost of rescue operations and relief goods distribution is minimized.

Keywords: flooding, geomorphology, mapping, watershed

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Authors: Sunil Kumar

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For many years, small organic molecules derived naturally from microbes and plants have delivered a number of expedient therapeutic drug agents. The search for naturally occurring lead compounds has continued in recent years as well, with the constituents of marine flora and fauna along with those of telluric microorganisms and plants being investigated for their anti-bacterial and anti-cancer activities. It has been observed that such promising lead molecules incline to promptly generate substantial attention among scientists like synthetic organic chemists and biologists. Subsequently, the availability of a given precious natural product sample may be enriched, and it may be possible to determine a preliminary idea of structure-activity relationships to develop synthetic analogues. For instance, anti-tumor drug topotecan is a synthetic chemical compound similar in chemical structure to camptothecin which is found in extracts of Camptotheca acuminate. Similarly, researchers at AstraZeneca discovered anti-biotic pyrrolamide through a fragment-based lead generation approach from kibdelomycin, which is isolated from Staphylococcus aureuss.

Keywords: anticancer, antibiotic, lead molecule, natural product, synthetic analogues

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Authors: Ji Hun Choi, Seung Un Chae, Kyeong Suk Cho

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Synthetic resins are widely used in various fields including electricity, engineering, construction and agriculture. Many of interior and exterior finishing materials for buildings are synthetic resin products. In this study, full-scale fire tests were conducted on polyvinyl chloride, polypropylene and urethane in accordance with the “ISO 9705: Fire test - Full-scale room test for surface products” to measure heat release rate, toxic gas emission and smoke production rate. Based on the tests, fire growth pattern and fire risk were analyzed. Findings from the tests conducted on polyvinyl chloride and urethane are as follows. The total heat release rate and total smoke production rate of polyvinyl chloride were 98.89MW and 5284.41m2, respectively and its highest CO2 concentration was 0.149%. The values obtained from the test with urethane were 469.94 MW, 3396.28 m2 and 1.549%. While heat release rate and CO2 concentration were higher in urethane implying its high combustibility, smoke production rate was 1.5 times higher in polyvinyl chloride. Follow-up tests are planned to be conducted to accumulate data for the evaluation of heat emission and fire risk associated with synthetic resins.

Keywords: synthetic resins, fire test, full-scale test, heat release rate, smoke production rate, polyvinyl chloride, polypropylene, urethane

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Authors: Ogunrinde Roseline Bosede

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This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.

Keywords: differential equations, numerical, polynomial, initial value problem, differential equation

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Authors: Baltazar Ndakidemi

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The resource-constrained farmers, especially those in sub-Saharan Africa, encounter significant challenges related to agriculture, notably diseases and pests. The sustainable means of pest management are not well known to farmers. As a result, some farmers use synthetic pesticides whose environmental impacts, ill health, and other negative impacts of synthetic pesticides on natural enemies have posed a great need for more sustainable means of pest management. Pesticidal plant resources can replace synthetic pesticides because their secondary metabolites can exhibit insecticidal activities such as deterrence, repellence, and pests' mortality. Additionally, the volatiles from these plants can have positive effects of attracting populations of natural enemies. Pesticidal plants can be grown as field margin plants or in strips for supporting natural enemies' populations. However, this is practically undetermined. Hence, there is a need to investigate the roles played by pesticidal plants in supporting natural enemies of pests and their applications in different cropping systems such as legumes. This study investigates different pesticidal plants with a high potential for pest control in agricultural fields. The information sheds light on potential plants that can be used for different crop pests.

Keywords: natural enemies, biological control, synthetic pesticides, pesticidal plants, predators, parasitoids

Procedia PDF Downloads 35

Authors: A. Altomi, A. Alhebshi, M. Rasm, B. Osman

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This study explored the application of chitin nanocrystals (ChiNCs), derived from a renewable and environmentally friendly material, as stabilizers for oil-in-water (O/W) emulsions. O/W emulsions are commonly used in various applications but are prone to instability and degradation over time. Instability can occur due to factors such as flocculation, coalescence, and gravitational separation, including creaming and sedimentation, either independently or simultaneously. To produce ChiNCs, chitin powder underwent acid hydrolysis. Transmission electron microscopy (TEM) analysis revealed that ChiNCs exhibited a needle-like morphology, with lengths ranging from 200 to 800 nm and widths ranging from 20 to 80 nm. The surface charge of ChiNCs was negative at pH values above 7 and positive at pH values below 7. The rheological properties of O/W emulsions stabilized by ChiNCs were compared to those stabilized by synthetic surfactants, namely Tween 80 and CTAB. The emulsions stabilized by ChiNCs demonstrated higher yield stress and lower shear viscosity compared to those stabilized by synthetic surfactants. This indicates that ChiNC-stabilized emulsions are more stable and less prone to breakdown. Based on these findings, ChiNCs show promise as an alternative to synthetic surfactants for stabilizing O/W emulsions.

Keywords: chitin nanocrystals, colloidal pickering, emulsion rheology, oil-in-water, synthetic surfactant

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Authors: E. Farg, M. M. El-Sharkawy, M. S. Mostafa, S. M. Arafat

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Mapping water stress provides important baseline data for sustainable agriculture. Recent developments in the new Sentinel-1 data which allow the acquisition of high resolution images and varied polarization capabilities. This study was conducted to detect and quantify vegetation water content from canopy backscatter for extracting spatial information to encourage drought mapping activities throughout new reclaimed sandy soils in western Nile delta, Egypt. The performance of radar imagery in agriculture strongly depends on the sensor polarization capability. The dual mode capabilities of Sentinel-1 improve the ability to detect water stress and the backscatter from the structure components improves the identification and separation of vegetation types with various canopy structures from other features. The fieldwork data allowed identifying of water stress zones based on land cover structure; those classes were used for producing harmonious water stress map. The used analysis techniques and results show high capability of active sensors data in water stress mapping and monitoring especially when integrated with multi-spectral medium resolution images. Also sub soil drip irrigation systems cropped areas have lower drought and water stress than center pivot sprinkler irrigation systems. That refers to high level of evaporation from soil surface in initial growth stages. Results show that high relationship between vegetation indices such as Normalized Difference Vegetation Index NDVI the observed radar backscattering. In addition to observational evidence showed that the radar backscatter is highly sensitive to vegetation water stress, and essentially potential to monitor and detect vegetative cover drought.

Keywords: canopy backscatter, drought, polarization, NDVI

Procedia PDF Downloads 115

Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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Authors: Naime Boudemagh

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In this work, we aim to improve the detection performances of radar systems. To this end, we propose and analyze a novel censoring technique of undesirable samples, of priori unknown positions, that may be present in the environment under investigation. Therefore, we consider heterogeneous backgrounds characterized by the presence of some irregularities such that clutter edge transitions and/or interfering targets. The proposed detector, termed automatic censoring constant false alarm (AC-CFAR), operates exclusively in a Gaussian background. It is built to allow the segmentation of the environment to regions and switch automatically to the appropriate detector; namely, the cell averaging CFAR (CA-CFAR), the censored mean level CFAR (CMLD-CFAR) or the order statistic CFAR (OS-CFAR). Monte Carlo simulations show that the AC-CFAR detector performs like the CA-CFAR in a homogeneous background. Moreover, the proposed processor exhibits considerable robustness in a heterogeneous background.

Keywords: CFAR, automatic censoring, heterogeneous environments, radar systems

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Authors: Weihao Wang, Zhulin Zong

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Two-dimensional ordered statistical constant false alarm detection is a widely used method for detecting weak target signals in radar signal processing applications. The method is based on analyzing the statistical characteristics of the noise and clutter present in the radar signal and then using this information to set an appropriate detection threshold. In this approach, the reference cell of the unit to be detected is divided into several reference subunits. These subunits are used to estimate the noise level and adjust the detection threshold, with the aim of minimizing the false alarm rate. By using an ordered statistical approach, the method is able to effectively suppress the influence of clutter and noise, resulting in a low false alarm rate. The detection process involves a number of steps, including filtering the input radar signal to remove any noise or clutter, estimating the noise level based on the statistical characteristics of the reference subunits, and finally, setting the detection threshold based on the estimated noise level. One of the main advantages of two-dimensional ordered statistical constant false alarm detection is its ability to detect weak target signals in the presence of strong clutter and noise. This is achieved by carefully analyzing the statistical properties of the signal and using an ordered statistical approach to estimate the noise level and adjust the detection threshold. In conclusion, two-dimensional ordered statistical constant false alarm detection is a powerful technique for detecting weak target signals in radar signal processing applications. By dividing the reference cell into several subunits and using an ordered statistical approach to estimate the noise level and adjust the detection threshold, this method is able to effectively suppress the influence of clutter and noise and maintain a low false alarm rate.

Keywords: two-dimensional, ordered statistical, constant false alarm, detection, weak target signals

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Authors: Adnan A. Y. Mustafa

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Image matching is a fundamental problem that arises frequently in many aspects of robot and computer vision. It can become a time-consuming process when matching images to a database consisting of hundreds of images, especially if the images are big. One approach to reducing the time complexity of the matching process is to reduce the search space in a pre-matching stage, by simply removing dissimilar images quickly. The Probabilistic Matching Model for Binary Images (PMMBI) showed that dissimilarity detection between binary images can be accomplished quickly by random pixel mapping and is size invariant. The model is based on the gamma binary similarity distance that recognizes an image and its inverse as containing the same scene and hence considers them to be the same image. However, in many applications, an image and its inverse are not treated as being the same but rather dissimilar. In this paper, we present a comparative analysis of dissimilarity detection between PMMBI based on the gamma binary similarity distance and a modified PMMBI model based on a similarity distance that does distinguish between an image and its inverse as being dissimilar.

Keywords: binary image, dissimilarity detection, probabilistic matching model for binary images, image mapping

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Authors: Fatemah A. Alqallaf, Debasis Kundu

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The aim of this paper is to introduce a bivariate inverse generalized exponential distribution which has a singular component. The proposed bivariate distribution can be used when the marginals have heavy-tailed distributions, and they have non-monotone hazard functions. Due to the presence of the singular component, it can be used quite effectively when there are ties in the data. Since it has four parameters, it is a very flexible bivariate distribution, and it can be used quite effectively for analyzing various bivariate data sets. Several dependency properties and dependency measures have been obtained. The maximum likelihood estimators cannot be obtained in closed form, and it involves solving a four-dimensional optimization problem. To avoid that, we have proposed to use an EM algorithm, and it involves solving only one non-linear equation at each `E'-step. Hence, the implementation of the proposed EM algorithm is very straight forward in practice. Extensive simulation experiments and the analysis of one data set have been performed. We have observed that the proposed bivariate inverse generalized exponential distribution can be used for modeling dependent competing risks data. One data set has been analyzed to show the effectiveness of the proposed model.

Keywords: Block and Basu bivariate distributions, competing risks, EM algorithm, Marshall-Olkin bivariate exponential distribution, maximum likelihood estimators

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Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 183

Authors: Iram Siddique

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Synthetic seed technology is an alternative to traditional micropropagation for production and delivery of cloned plantlets. Synthetic seeds were produced by encapsulating nodal segments of C. angustifolia in calcium alginate gel. 3% (w/v) sodium alginate and 100 mM CaCl2. 2H2O were found most suitable for encapsulation of nodal segments. Synthetic seeds cultured on half strength Murashige and Skoog (MS) medium supplemented with thidiazuron (5.0 µM) + indole -3- acetic acid (1.0 µM) produced maximum number of shoots (10.9 ± 0.78) after 8 weeks of culture exhibiting (78%) in vitro conversion response. Encapsulated nodal segments demonstrated successful regeneration after different period (1-6 weeks) of cold storage at 4 °C. The synthetic seeds stored at 4 °C for a period of 4 weeks resulted in maximum conversion frequency (93%) after 8 weeks when placed back to regeneration medium. The isolated shoots when cultured on half strength MS medium supplemented with 1.0 µM indole -3- butyric acid (IBA), produced healthy roots and plantlets with well developed shoot and roots were successfully hardened off in plastic pots containing sterile soilrite inside the growth chamber and gradually transferred to greenhouse where they grew well with 85% survival rate. Changes in the content of photosynthetic pigments, net photosynthetic rate (PN), superoxide dismutase (SOD) and catalase (CAT) activity in C. angustifolia indicated the adaptation of micropropagated plants to ex vitro conditions.

Keywords: biochemical studies, nodal segments, rooting, synthetic seeds, thidiazuron

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Authors: C. Paglia, C. Mosca

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Synthetic resin floorsare often used in sport infrastructure. These organic materials are often in contact with a bituminous substrate, which in turn is placed on the ground. In this work, the damage of a basket resin field surface was characterized by means of visual inspection, optical microscopy, resin thickness measurements, adhesion strength, water vapor transmission capacity, capillary water adsorption, granulometry of the bituminous conglomerate, the surface properties, and the water ground infiltration speed. The infiltration speed indicates water pemeability. This was due to its composition: clean sand mixed with gravel. Relatively good adhesion was present between the synthetic resin and the bituminous layer. The adhesion resistance of the bituminous layer was relatively low. According to the required bitumoniousasphalt-concrete mixes AC 11 S, the placed material was more porous. Insufficient constipation was present. The spaces values were above the standard limits, while the apparent densities were lower compared to the conventional AC 11 mixtures. The microstructure outlines the high permeability and porosity of the bituminous layer. The synthetic resin wasvapourproof and did not exhibit capillary adsorption. It exhibited a lower thickness as required, and no multiple placing steps were observed. Multiple cavities were detected along with the interface between the bituminous layer and the resin coating with no intermediate layers. The layer for the pore filling in the bituminous surface was not properly applied. The swelling bubbles on the synthetic pavement were caused by the humidity in the bituminous layer. Water or humidity were present prior to the application of the resin, and the effect was worsened by the upward movement of the water from the ground.

Keywords: resin, floor, damage, durability

Procedia PDF Downloads 135

Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: Nguyen Van Loi, Le Thanh Son, Tran Trung Kien

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The paper deals with the problem of the formation of range profiles (RPs) for an X-band coastal surveillance radar. Two popular methods, the difference operator method, and the window-based method, are reviewed and analyzed via two tests with different datasets. The test results show that although the original window-based method achieves a better performance than the difference operator method, it has three main drawbacks that are the use of 3 or 4 peaks of an RP for creating the windows, the extension of the window size using the power sum of three adjacent cells in the left and the right sides of the windows and the same threshold applied for all types of vessels to finish the formation process of RPs. These drawbacks lead to inaccurate RPs due to the low signal-to-clutter ratio. Therefore, some suggestions are proposed to improve the original window-based method.

Keywords: range profile, difference operator method, window-based method, automatic target recognition

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Authors: Boudemagh Naime

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Automatic radar detection requires some methods of adapting to variations in the background clutter in order to control their false alarm rate. The problem becomes more complicated in non-Gaussian environment. In fact, the conventional approach in real time applications requires a complex statistical modeling and much computational operations. To overcome these constraints, we propose another approach based on artificial neural network (ANN-CMLD-CFAR) using a Back Propagation (BP) training algorithm. The considered environment follows a log-normal distribution in the presence of multiple Rayleigh-targets. To evaluate the performances of the considered detector, several situations, such as scale parameter and the number of interferes targets, have been investigated. The simulation results show that the ANN-CMLD-CFAR processor outperforms the conventional statistical one.

Keywords: radat detection, ANN-CMLD-CFAR, log-normal clutter, statistical modelling

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Authors: Udit Mohanty, Mari Lundstrom

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Electrochemical investigation by cyclic voltammetry was conducted to explore the polarization behavior of reactions occurring in nickel electrowinning in presence of cationic impurities such as Ca2+ (0-100 mg/L), Na+ (1-10 g/L) and Mg2+ (10-100 mg/L). A comparative study was devised between industrial and synthetic electrolytes to observe the shift in the nucleation overpotentials of nickel deposition, dissolution and hydrogen evolution reactions at the cathode and anode respectively. Significant polarization of cathodic reactions were observed with concentrations of Na ≥ 8g /L and Ca ≤ 40 mg /L in the synthetic electrolytes. Nevertheless, a progressive increase in the concentration of Ca, Mg and Na in the industrial electrolyte demonstrated a depolarization behavior in the cathodic reactions related to nickel deposition and/or hydrogen evolution. Synergistic effect of Ca with Mg and Na in both the industrial and synthetic electrolytes induced a notable depolarization effect, also reflected in the peak currents.

Keywords: cationic impurities, cyclic voltammetry, electrowinning, nickel, polarization

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Authors: Muhammad Hassan Khalil, Xu Jiadong

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Early detection through screening is the best tool short of a perfect treatment against the malignant tumor inside the breast of a woman. By detecting cancer in its early stages, it can be recognized and treated before it has the opportunity to spread and change into potentially dangerous. Microwave tomography is a new imaging method based on contrast in dielectric properties of materials. The mathematical theory of microwave tomography involves solving an inverse problem for Maxwell’s equations. In this paper, we present designed antenna for breast cancer detection, which will use in microwave tomography configuration.

Keywords: microwave imaging, inverse scattering, breast cancer, malignant tumor detection

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Authors: Md Omar Faruq Howlader, Tariq Pervez Sattar, Sandra Dudley

Abstract:

This paper describes the design process of a 200 MHz Ground Penetrating Radar (GPR) and a battery powered concrete vertical concrete surface climbing mobile robot. The key design feature is a miniaturized 200 MHz dipole antenna using additional radiating arms and procedure records a reduction of 40% in length compared to a conventional antenna. The antenna set is mounted in front of the robot using a servo mechanism for folding and unfolding purposes. The robot’s adhesion mechanism to climb the reinforced concrete wall is based on neodymium permanent magnets arranged in a unique combination to concentrate and maximize the magnetic flux to provide sufficient adhesion force for GPR installation. The experiments demonstrated the robot’s capability of climbing reinforced concrete wall carrying the attached prototype GPR system and perform floor-to-wall transition and vice versa. The developed GPR’s performance is validated by its capability of detecting and localizing an aluminium sheet and a reinforcement bar (rebar) of 12 mm diameter buried under a test rig built of wood to mimic the concrete structure environment. The present robotic GPR system proves the concept of feasibility of undertaking inspection procedure on large concrete structures in hazardous environments that may not be accessible to human inspectors.

Keywords: climbing robot, dipole antenna, ground penetrating radar (GPR), mobile robots, robotic GPR

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Authors: Davide D’Aria, Paolo Falcone, Luigi Maggi, Aldo Cero, Giovanni Amoroso

Abstract:

The paper presents a methodology for real-time structural health monitoring and geophysical applications. The key elements of the system are a high performance MIMO RADAR sensor, an optical camera and a dedicated set of software algorithms encompassing interferometry, tomography and photogrammetry. The MIMO Radar sensor proposed in this work, provides an extremely high sensitivity to displacements making the system able to react to tiny deformations (up to tens of microns) with a time scale which spans from milliseconds to hours. The MIMO feature of the system makes the system capable of providing a set of two-dimensional images of the observed scene, each mapped on the azimuth-range directions with noticeably resolution in both the dimensions and with an outstanding repetition rate. The back-scattered energy, which is distributed in the 3D space, is projected on a 2D plane, where each pixel has as coordinates the Line-Of-Sight distance and the cross-range azimuthal angle. At the same time, the high performing processing unit allows to sense the observed scene with remarkable refresh periods (up to milliseconds), thus opening the way for combined static and dynamic structural health monitoring. Thanks to the smart TX/RX antenna array layout, the MIMO data can be processed through a tomographic approach to reconstruct the three-dimensional map of the observed scene. This 3D point cloud is then accurately mapped on a 2D digital optical image through photogrammetric techniques, allowing for easy and straightforward interpretations of the measurements. Once the three-dimensional image is reconstructed, a 'repeat-pass' interferometric approach is exploited to provide the user of the system with high frequency three-dimensional motion/vibration estimation of each point of the reconstructed image. At this stage, the methodology leverages consolidated atmospheric correction algorithms to provide reliable displacement and vibration measurements.

Keywords: interferometry, MIMO RADAR, SAR, tomography

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Authors: Ashis Mallick, Rajeev Ranjan

Abstract:

The closed form solution for thermal stresses in an annular fin with hyperbolic profile is derived using Adomian decomposition method (ADM). The conductive-convective fin with variable thermal conductivity is considered in the analysis. The nonlinear heat transfer equation is efficiently solved by ADM considering insulated convective boundary conditions at the tip of fin. The constant of integration in the solution is to be estimated using minimum decomposition error method. The solution of temperature field is represented in a polynomial form for convenience to use in thermo-elasticity equation. The non-dimensional thermal stress fields are obtained using the ADM solution of temperature field coupled with the thermo-elasticity solution. The influence of the various thermal parameters in temperature field and stress fields are presented. In order to show the accuracy of the ADM solution, the present results are compared with the results available in literature. The stress fields in fin with hyperbolic profile are compared with those of uniform thickness profile. Result shows that hyperbolic fin profile is better choice for enhancing heat transfer. Moreover, less thermal stresses are developed in hyperbolic profile as compared to rectangular profile. Next, Nelder-Mead based simplex search method is employed for the inverse estimation of unknown non-dimensional thermal parameters in a given stress fields. Owing to the correlated nature of the unknowns, the best combinations of the model parameters which are satisfying the predefined stress field are to be estimated. The stress fields calculated using the inverse parameters give a very good agreement with the stress fields obtained from the forward solution. The estimated parameters are suitable to use for efficient and cost effective fin designing.

Keywords: Adomian decomposition, inverse analysis, hyperbolic fin, variable thermal conductivity

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Authors: Minho Kwon, Seonghyeok Lee, Wooyoung Jung

Abstract:

In recent years, with increase of construction of skyscraper structures, the study of concrete materials to improve their weight and performance has been emerging as a key of research area. Typically, the concrete structures has disadvantage of increasing the weight due to its mass in comparison to the strength of the materials. Therefore, in order to improve such problems, the light-weight aggregate concrete and high strength concrete materials have been studied during the past decades. On the other hand, the study of light-weight aggregate concrete materials has lack of data in comparison to the concrete structure using high strength materials, relatively. Consequently, this study presents the performance characteristics of light-weight aggregate concrete materials due to the material properties and strength. Also, this study conducted the experimental tests with respect to normal and lightweight aggregate materials, in order to indentify the tensile crack failure of the concrete structures. As a result, the Crack Mouth Opening Displacement (CMOD) from the experimental tests was constructed and the fracture energy using inverse problem analysis was developed from the force-CMOD relationship in this study, respectively.

Keywords: lightweight aggregate concrete, crack mouth opening displacement, inverse analysis, fracture energy

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Authors: Turan Çalban, Oral Laçin, Abdüsselam Kurtbaş

Abstract:

The experimental production methods Chevreul’s salt being a intermediate stage product for copper recovery were investigated by dealing with the articles written on this topic. Chevreul’s salt, Cu2SO3.CuSO3.2H2O, being a mixed valence copper sulphite compound has been obtained by using different methods and reagents. Chevreul’s salt has a intense brick-red color. It is a highly stable and expensive salt. The production of Chevreul’s salt plays a key role in hiydrometallurgy. In recent years, researchs on this compound have been intensified. Silva et al. reported that this salt is thermally stable up to 200oC. Çolak et al. precipitated the Chevreul’s salt by using ammonia and sulphur dioxide. Çalban et al. obtained at the optimum conditions by passing SO2 from leach solutions with NH3-(NH4)2SO4. Yeşiryurt and Çalban investigated the optimum precipitation conditions of Chevreul’s salt from synthetic CuSO4 solutions including Na2SO3. Çalban et al. achieved the precipitation of Chevreul’s salt at the optimum conditions by passing SO2 from synthetic CuSO4 solutions. Çalban et al. examined the precipitation conditions of Chevreul’s salt using (NH4)2SO3 from synthetic aqueous CuSO4 solutions. In light of these studies, it can be said that Chevreul’s salt can be produced practically from both a leach solutions including copper and synthetic CuSO4 solutions.

Keywords: Chevreul’s salt, ammonia, copper sulpfite, sodium sülfite, optimum conditions

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