Search results for: unsteady shear layer

Authors: Javad Jozaei, Rob G. Bell, Paula Blackett, Scott A. Stephens

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In the last few decades, Social Vulnerability Assessment (SVA) has been a favoured means in evaluating the susceptibility of social systems to drivers of change, including climate change and natural disasters. However, the application of SVA to inform responsive and practical strategies to deal with uncertain climate change impacts has always been challenging, and typically agencies resort back to conventional risk/vulnerability assessment. These challenges include complex nature of social vulnerability concepts which influence its applicability, complications in identifying and measuring social vulnerability determinants, the transitory social dynamics in a changing environment, and unpredictability of the scenarios of change that impacts the regime of vulnerability (including contention of when these impacts might emerge). Research suggests that the conventional quantitative approaches in SVA could not appropriately address these problems; hence, the outcomes could potentially be misleading and not fit for addressing the ongoing uncertain rise in risk. The second phase of New Zealand’s Resilience to Nature’s Challenges (RNC2) is developing a forward-looking vulnerability assessment framework and methodology that informs the decision-making and policy development in dealing with the changing coastal systems and accounts for complex dynamics of New Zealand’s coastal systems (including socio-economic, environmental and cultural). Also, RNC2 requires the new methodology to consider plausible drivers of incremental and unknowable changes, create mechanisms to enhance social and community resilience; and fits the New Zealand’s multi-layer governance system. This paper aims to analyse the conventional approaches and methodologies in SVA and offer recommendations for more responsive approaches that inform adaptive decision-making and policy development in practice. The research adopts a qualitative research design to examine different aspects of the conventional SVA processes, and the methods to achieve the research objectives include a systematic review of the literature and case study methods. We found that the conventional quantitative, reductionist and deterministic mindset in the SVA processes -with a focus the impacts of rapid stressors (i.e. tsunamis, floods)- show some deficiencies to account for complex dynamics of social-ecological systems (SES), and the uncertain, long-term impacts of incremental drivers. The paper will focus on addressing the links between resilience and vulnerability; and suggests how resilience theory and its underpinning notions such as the adaptive cycle, panarchy, and system transformability could address these issues, therefore, influence the perception of vulnerability regime and its assessment processes. In this regard, it will be argued that how a shift of paradigm from ‘specific resilience’, which focuses on adaptive capacity associated with the notion of ‘bouncing back’, to ‘general resilience’, which accounts for system transformability, regime shift, ‘bouncing forward’, can deliver more effective strategies in an era characterised by ongoing change and deep uncertainty.

Keywords: complexity, social vulnerability, resilience, transformation, uncertain risks

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Authors: Natalia C. E. S. Nascimento, Mercia L. Oliveira, Fernando R. A. Lima, Leonardo T. C. do Nascimento, Marina B. Silveira, Brigida G. A. Schirmer, Andrea V. Ferreira, Carlos Malamut, Juliana B. da Silva

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Tissue hypoxia is a common characteristic of solid tumors leading to decreased sensitivity to radiotherapy and chemotherapy. In the clinical context, tumor hypoxia assessment employing the positron emission tomography (PET) tracer ¹⁸F-fluoromisonidazole ([¹⁸F]FMISO) is helpful for physicians for planning and therapy adjusting. The aim of this work was to implement the synthesis of 18F-FMISO in a TRACERlab® MXFDG module and also to establish the quality control procedure. [¹⁸F]FMISO was synthesized at Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN/Brazil) using an automated synthesizer (TRACERlab® MXFDG, GE) adapted for the production of [¹⁸F]FMISO. The FMISO chemical standard was purchased from ABX. 18O- enriched water was acquired from Center of Molecular Research. Reagent kits containing eluent solution, acetonitrile, ethanol, 2.0 M HCl solution, buffer solution, water for injections and [¹⁸F]FMISO precursor (dissolved in 2 ml acetonitrile) were purchased from ABX. The [¹⁸F]FMISO samples were purified by Solid Phase Extraction method. The quality requirements of [¹⁸F]FMISO are established in the European Pharmacopeia. According to that reference, quality control of [¹⁸F]FMISO should include appearance, pH, radionuclidic identity and purity, radiochemical identity and purity, chemical purity, residual solvents, bacterial endotoxins, and sterility. The duration of the synthesis process was 53 min, with radiochemical yield of (37.00 ± 0.01) % and the specific activity was more than 70 GBq/µmol. The syntheses were reproducible and showed satisfactory results. In relation to the quality control analysis, the samples were clear and colorless at pH 6.0. The spectrum emission, measured by using a High-Purity Germanium Detector (HPGe), presented a single peak at 511 keV and the half-life, determined by the decay method in an activimeter, was (111.0 ± 0.5) min, indicating no presence of radioactive contaminants, besides the desirable radionuclide (¹⁸F). The samples showed concentration of tetrabutylammonium (TBA) < 50μg/mL, assessed by visual comparison to TBA standard applied in the same thin layer chromatographic plate. Radiochemical purity was determined by high performance liquid chromatography (HPLC) and the results were 100%. Regarding the residual solvents tested, ethanol and acetonitrile presented concentration lower than 10% and 0.04%, respectively. Healthy female mice were injected via lateral tail vein with [¹⁸F]FMISO, microPET imaging studies (15 min) were performed after 2 h post injection (p.i), and the biodistribution was analyzed in five-time points (30, 60, 90, 120 and 180 min) after injection. Subsequently, organs/tissues were assayed for radioactivity with a gamma counter. All parameters of quality control test were in agreement to quality criteria confirming that [¹⁸F]FMISO was suitable for use in non-clinical and clinical trials, following the legal requirements for the production of new radiopharmaceuticals in Brazil.

Keywords: automatic radiosynthesis, hypoxic tumors, pharmacopeia, positron emitters, quality requirements

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Authors: O. Squillace, R. L. Thompson

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Migration of small molecules to, and across the surface of polymer matrices is a little-studied problem with important industrial applications. Tackifiers in adhesives, flavors in foods and binding agents in paints all present situations where the function of a product depends on the ability of small molecules to migrate through a polymer matrix to achieve the desired properties such as softness, dispersion of fillers, and to deliver an effect that is felt (or tasted) on a surface. It’s been shown that the chemical and molecular structure, surface free energies, phase behavior, close environment and compatibility of the system, influence the migrants’ motion. When differences in behavior, such as occurrence of segregation to the surface or not, are observed it is then of crucial importance to identify and get a better understanding of the driving forces involved in the process of molecular migration. In this aim, experience is meant to be allied with theory in order to deliver a validated theoretical and computational toolkit to describe and predict these phenomena. The systems that have been chosen for this study aim to address the effect of polarity mismatch between the migrants and the polymer matrix and that of a second migrant over the first one. As a non-polar resin polymer, polyvinyl acetate is used as the material to which more or less polar migrants (sorbitol, carvone, octanoic acid (OA), triacetin) are to be added. Through contact angle measurement a surface excess is seen for sorbitol (polar) mixed with PVAc as the surface energy is lowered compare to the one of pure PVAc. This effect is increased upon the addition of carvon or triacetin (non-polars). Surface micro-structures are also evidenced by atomic force microscopy (AFM). Ion beam analysis (Nuclear Reaction Analysis), supplemented by neutron reflectometry can accurately characterize the self-organization of surfactants, oligomers, aromatic molecules in polymer films in order to relate the macroscopic behavior to the length scales that are amenable to simulation. The nuclear reaction analysis (NRA) data for deuterated OA 20% shows the evidence of a surface excess which is enhanced after annealing. The addition of 10% triacetin, as a second migrant, results in the formation of an underlying layer enriched in triacetin below the surface excess of OA. The results show that molecules in polarity mismatch with the matrix tend to segregate to the surface, and this is favored by the addition of a second migrant of the same polarity than the matrix. As studies have been restricted to materials that are model supported films under static conditions in a first step, it is also wished to address the more challenging conditions of materials under controlled stress or strain. To achieve this, a simple rig and PDMS cell have been designed to stretch the material to a defined strain and to probe these mechanical effects by ion beam analysis and atomic force microscopy. This will make a significant step towards exploring the influence of extensional strain on surface segregation, flavor release in cross-linked rubbers.

Keywords: polymers, surface segregation, thin films, molecular migration

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Authors: S. A. Krutovertsev, A. E. Tarasova, L. S. Krutovertseva, O. M. Ivanova

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The aim of the work was to get stable sensitive films with good sensitivity to ethanolamine (C2H7NO) in air. Ethanolamine is used as adsorbent in different processes of gas purification and separation. Besides it has wide industrial application. Chemical sensors of sorption type are widely used for gas analysis. Their behavior is determined by sensor characteristics of sensitive sorption layer. Forming conditions and characteristics of chemical gas sensors based on nanostructured modified silica films activated by different admixtures have been studied. As additives molybdenum containing polyoxometalates of the eighteen series were incorporated in silica films. The method of hydrolythic polycondensation from tetraethyl orthosilicate solutions was used for forming such films in this work. The method’s advantage is a possibility to introduce active additives directly into an initial solution. This method enables to obtain sensitive thin films with high specific surface at room temperature. Particular properties make polyoxometalates attractive as active additives for forming of gas-sensitive films. As catalyst of different redox processes, they can either accelerate the reaction of the matrix with analyzed gas or interact with it, and it results in changes of matrix’s electrical properties Polyoxometalates based films were deposited on the test structures manufactured by microelectronic planar technology with interdigitated electrodes. Modified silica films were deposited by a casting method from solutions based on tetraethyl orthosilicate and polyoxometalates. Polyoxometalates were directly incorporated into initial solutions. Composite nanostructured films were deposited by drop casting method on test structures with a pair of interdigital metal electrodes formed at their surface. The sensor’s active area was 4.0 x 4.0 mm, and electrode gap was egual 0.08 mm. Morphology of the layers surface were studied with Solver-P47 scanning probe microscope (NT-MDT, Russia), the infrared spectra were investigated by a Bruker EQUINOX 55 (Germany). The conditions of film formation varied during the tests. Electrical parameters of the sensors were measured electronically in real-time mode. Films had highly developed surface with value of 450 m2/g and nanoscale pores. Thickness of them was 0,2-0,3 µm. The study shows that the conditions of the environment affect markedly the sensors characteristics, which can be improved by choosing of the right procedure of forming and processing. Addition of polyoxometalate into silica film resulted in stabilization of film mass and changed markedly of electrophysical characteristics. Availability of Mn3P2Mo18O62 into silica film resulted in good sensitivity and selectivity to ethanolamine. Sensitivity maximum was observed at weight content of doping additive in range of 30–50% in matrix. With ethanolamine concentration changing from 0 to 100 ppm films’ conductivity increased by 10-12 times. The increase of sensor’s sensitivity was received owing to complexing reaction of tested substance with cationic part of polyoxometalate. This fact results in intramolecular redox reaction which sharply change electrophysical properties of polyoxometalate. This process is reversible and takes place at room temperature.

Keywords: ethanolamine, gas analysis, polyoxometalate, silica film

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Authors: Lucas M. Furlan, Cesar A. Moreira, Jepherson F. Sales, Guilherme T. Bueno, Manuel E. Ferreira, Carla V. S. Coelho, Vania Rosolen

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Located in the western part of the State of Minas Gerais, Brazil, the study area consists of a savanna environment, represented by sedimentary plateau and a soil cover composed by lateritic and hydromorphic soils - in the latter, occurring the deferruginization and concentration of high-alumina clays, exploited as refractory material. In the hydromorphic topographic depressions (wetlands) the hydropedogical relationships are little known, but it is observed that in times of rainfall, the depressed region behaves like a natural seasonal reservoir - which suggests that the wetlands on the surface of the plateau are places of recharge of the aquifer. The aquifer recharge areas are extremely important for the sustainable social, economic and environmental development of societies. The understanding of hydrodynamics in relation to the functioning of the ferruginous and hydromorphic lateritic soils system in the savanna environment is a subject rarely explored in the literature, especially its understanding through the joint application of geoprocessing by UAV (Unmanned Aerial Vehicle) and electrical tomography. The objective of this work is to understand the hydrogeological dynamics in a wetland (with an area of 426.064 m²), in the Brazilian savanna,as well as the understanding of the subsurface architecture of hydromorphic depressions in relation to the recharge of aquifers. The wetland was compartmentalized in three different regions, according to the geoprocessing. Hydraulic conductivity studies were performed in each of these three portions. Electrical tomography was performed on 9 lines of 80 meters in length and spaced 10 meters apart (direction N45), and a line with 80 meters perpendicular to all others. With the data, it was possible to generate a 3D cube. The integrated analysis showed that the area behaves like a natural seasonal reservoir in the months of greater precipitation (December – 289mm; January – 277,9mm; February – 213,2mm), because the hydraulic conductivity is very low in all areas. In the aerial images, geotag correction of the images was performed, that is, the correction of the coordinates of the images by means of the corrected coordinates of the Positioning by Precision Point of the Brazilian Institute of Geography and Statistics (IBGE-PPP). Later, the orthomosaic and the digital surface model (DSM) were generated, which with specific geoprocessing generated the volume of water that the wetland can contain - 780,922m³ in total, 265,205m³ in the region with intermediate flooding and 49,140m³ in the central region, where a greater accumulation of water was observed. Through the electrical tomography it was possible to identify that up to the depth of 6 meters the water infiltrates vertically in the central region. From the 8 meters depth, the water encounters a more resistive layer and the infiltration begins to occur horizontally - tending to concentrate the recharge of the aquifer to the northeast and southwest of the wetland. The hydrodynamics of the area is complex and has many challenges in its understanding. The next step is to relate hydrodynamics to the evolution of the landscape, with the enrichment of high-alumina clays, and to propose a management model for the seasonal reservoir.

Keywords: electrical tomography, hydropedology, unmanned aerial vehicle, water resources management

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Authors: Sonika Sharma, Mohan G. Vairale, Sibnarayan Datta, Soumya Chatterjee, Dharmendra Dubey, Rajesh Prasad, Raghvendra Budhauliya, Bidisha Das, Vijay Veer

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Bacteriophages are viruses that parasitize specific bacteria and multiply in metabolising host bacteria. Bacteriophages hunt for a single or a subset of bacterial species, making them potential antibacterial agents. Utilizing the ability of phages to control bacterial populations has several applications from medical to the fields of agriculture, aquaculture and the food industry. However, harnessing phage based techniques in wastewater treatments to improve quality of effluent and sludge release into the environment is a potential area for R&D application. Phage mediated bactericidal effect in any wastewater treatment process has many controlling factors that lead to treatment performance. In laboratory conditions, titer of bacteriophages (coliphages) isolated from effluent water of a specially designed anaerobic digester of human night soil (DRDO Biotoilet) was successfully increased with a modified protocol of the classical double layer agar technique. Enrichment of the same was carried out and efficacy of the phage enriched medium was evaluated at different conditions (specific media, temperature, storage conditions). Growth optimization study was carried out on different media like soybean casein digest medium (Tryptone soya medium), Luria-Bertani medium, phage deca broth medium and MNA medium (Modified nutrient medium). Further, temperature-phage yield relationship was also observed at three different temperatures 27˚C, 37˚C and 44˚C at laboratory condition. Results showed the higher activity of coliphage 27˚C and at 37˚C. Further, addition of divalent ions (10mM MgCl2, 5mM CaCl2) and 5% glycerol resulted in a significant increase in phage titer. Besides this, effect of antibiotics addition like ampicillin and kanamycin at different concentration on plaque formation was analysed and reported that ampicillin at a concentration of 1mg/ml ampicillin stimulates phage infection and results in more number of plaques. Experiments to test viability of phage showed that it can remain active for 6 months at 4˚C in fresh tryptone soya broth supplemented with fresh culture of coliforms (early log phase). The application of bacteriophages (especially coliphages) for treatment of effluent of human faecal matter contaminated effluent water is unique. This environment-friendly treatment system not only reduces the pathogenic coliforms, but also decreases the competition between nuisance bacteria and functionally important microbial populations. Therefore, the phage based cocktail to treat fecal pathogenic bacteria present in black water has many implication in wastewater treatment processes including ‘DRDO Biotoilet’, which is an ecofriendly appropriate and affordable human faecal matter treatment technology for different climates and situations.

Keywords: wastewater, microbes, virus, biotoilet, phage viability

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Authors: Alaa Fezai, Anuj Sharma, Wolfgang Mueller-Hirsch, André Zimmermann

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Viscoelastic materials have been widely used in the automotive industry over the last few decades with different functionalities. Besides their main application as a simple and efficient surface damping treatment, they may ensure optimal operating conditions for on-board electronics as thermal interface or sealing layers. The dynamic behavior of viscoelastic materials is generally dependent on many environmental factors, the most important being temperature and strain rate or frequency. Prior to the reliability analysis of systems including viscoelastic layers, it is, therefore, crucial to accurately predict the dynamic and lifetime behavior of these materials. This includes the identification of the dynamic material parameters under critical temperature and frequency conditions along with a precise damage localization and identification methodology. The goal of this work is twofold. The first part aims at applying an inverse viscoelastic material-characterization approach for a wide frequency range and under different temperature conditions. For this sake, dynamic measurements are carried on a single lap joint specimen using an electrodynamic shaker and an environmental chamber. The specimen consists of aluminum beams assembled to adapter plates through a viscoelastic adhesive layer. The experimental setup is reproduced in finite element (FE) simulations, and frequency response functions (FRF) are calculated. The parameters of both the generalized Maxwell model and the fractional derivatives model are identified through an optimization algorithm minimizing the difference between the simulated and the measured FRFs. The second goal of the current work is to guarantee an on-line detection of the damage, i.e., delamination in the viscoelastic bonding of the described specimen during frequency monitored end-of-life testing. For this purpose, an inverse technique, which determines the damage location and size based on the modal frequency shift and on the change of the mode shapes, is presented. This includes a preliminary FE model-based study correlating the delamination location and size to the change in the modal parameters and a subsequent experimental validation achieved through dynamic measurements of specimen with different, pre-generated crack scenarios and comparing it to the virgin specimen. The main advantage of the inverse characterization approach presented in the first part resides in the ability of adequately identifying the material damping and stiffness behavior of soft viscoelastic materials over a wide frequency range and under critical temperature conditions. Classic forward characterization techniques such as dynamic mechanical analysis are usually linked to limitations under critical temperature and frequency conditions due to the material behavior of soft viscoelastic materials. Furthermore, the inverse damage detection described in the second part guarantees an accurate prediction of not only the damage size but also its location using a simple test setup and outlines; therefore, the significance of inverse numerical-experimental approaches in predicting the dynamic behavior of soft bonding layers applied in automotive electronics.

Keywords: damage detection, dynamic characterization, inverse approaches, vibration testing, viscoelastic layers

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Authors: Mark McGuire, Eric Shannon, John Parmigiani

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Timber harvesting increasingly involves mechanized equipment. This has increased the efficiency of harvesting, but has also introduced worker-safety concerns. One such concern arises from the use of harvesters. During operation, harvesters subject saw chain to large dynamic mechanical stresses. These stresses can, under certain conditions, cause the saw chain to fracture. The high speed of harvester saw chain can cause the resulting open chain loop to fracture a second time due to the dynamic loads placed upon it as it travels through space. If a second fracture occurs, it can result in a projectile consisting of one-to-several chain links. This projectile is referred to as a chain shot. It has speeds similar to a bullet but typically has greater mass and is a significant safety concern. Numerous examples exist of chain shots penetrating bullet-proof barriers and causing severe injury and death. Improved harvester-cab barriers can help prevent injury however a comprehensive scientific understanding of chain shot is required to consistently reduce or prevent it. Obtaining this understanding requires a test machine with the capability to cause chain shot to occur under carefully controlled conditions and accurately measure the response. Worldwide few such test machine exist. Those that do focus on validating the ability of barriers to withstand a chain shot impact rather than obtaining a scientific understanding of the chain shot event itself. The purpose of this paper is to describe the design, fabrication, and use of a test machine capable of a comprehensive scientific investigation of chain shot. The capabilities of this machine are to test all commercially-available saw chains and bars at chain tensions and speeds meeting and exceeding those typically encountered in harvester use and accurately measure the corresponding key technical parameters. The test machine was constructed inside of a standard shipping container. This provides space for both an operator station and a test chamber. In order to contain the chain shot under any possible test conditions, the test chamber was lined with a base layer of AR500 steel followed by an overlay of HDPE. To accommodate varying bar orientations and fracture-initiation sites, the entire saw chain drive unit and bar mounting system is modular and capable of being located anywhere in the test chamber. The drive unit consists of a high-speed electric motor with a flywheel. Standard Ponsse harvester head components are used to bar mounting and chain tensioning. Chain lubrication is provided by a separate peristaltic pump. Chain fracture is initiated through ISO standard 11837. Measure parameters include shaft speed, motor vibration, bearing temperatures, motor temperature, motor current draw, hydraulic fluid pressure, chain force at fracture, and high-speed camera images. Results show that the machine is capable of consistently causing chain shot. Measurement output shows fracture location and the force associated with fracture as a function of saw chain speed and tension. Use of this machine will result in a scientific understanding of chain shot and consequently improved products and greater harvester operator safety.

Keywords: chain shot, safety, testing, timber harvesters

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Authors: Jhovana Silvia Escobar Ortega, Ines Eugenia Garcia De Salamone

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Cover crops are an agri-technological alternative to improve all properties of soils. Cover crops such as oats and rye could be used to reduce erosion and favor system sustainability when they are grown in the same agricultural cycle of the soybean crop. This crop is very profitable but its low contribution of easily decomposable residues, due to its low C/N ratio, leaves the soil exposed to erosive action and raises the need to reduce its monoculture. Furthermore, inoculation with the plant growth promoting rhizobacteria contributes to the implementation, development and production of several cereal crops. However, there is little information on its effects on forage crops which are often used as cover crops to improve soil quality. In order to evaluate the effect of combined inoculation with Azospirillum brasilense and Pseudomonas fluorescens on rhizosphere microbial communities, field experiments were conducted in the west of Buenos Aires province, Argentina, with a split-split plot randomized complete block factorial design with three replicates. The factors were: type of cover crop, inoculation and fertilization. In the main plot two levels of fertilization 0 and 7 40-0-5 (NPKS) were established at sowing. Rye (Secale cereale cultivar Quehué) and oats (Avena sativa var Aurora.) were sown in the subplots. In the sub-subplots two inoculation treatments are applied without and with application of a combined inoculant with A. brasilense and P. fluorescens. Due to the growth of cover crops has to be stopped usually with the herbicide glyphosate, rhizosphere soil of 0-20 and 20-40 cm layers was sampled at three sampling times which were: before glyphosate application (BG), a month after glyphosate application (AG) and at soybean harvest (SH). Community level of physiological profiles (CLPP) and Shannon index of microbial diversity (H) were obtained by multivariate analysis of Principal Components. Also, the most probable number (MPN) of nitrifiers and cellulolytics were determined using selective liquid media for each functional group. The CLPP of rhizosphere microbial communities showed significant differences between sampling times. There was not interaction between sampling times and both, types of cover crops and inoculation. Rhizosphere microbial communities of samples obtained BG had different CLPP with respect to the samples obtained in the sampling times AG and SH. Fertilizer and depth of sampling also caused changes in the CLPP. The H diversity index of rhizosphere microbial communities of rye in the sampling time BG were higher than those associated with oats. The MPN of both microbial functional types was lower in the deeper layer since these microorganisms are mostly aerobic. The MPN of nitrifiers decreased in rhizosphere of both cover crops only AG. At the sampling time BG, the NMP of both microbial types were larger than those obtained for AG and SH. This may mean that the glyphosate application could cause fairly permanent changes in these microbial communities which can be considered bio-indicators of soil quality. Inoculation and fertilizer inputs could be included to improve management of these cover crops because they can have a significant positive effect on the sustainability of the agro-ecosystem.

Keywords: community level of physiological profiles, microbial diversity, plant growth promoting rhizobacteria, rhizosphere microbial communities, soil quality, system sustainability

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Authors: Trevor C. Brown, David J. Miron

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Gas-solid physical adsorption methods are central to the characterization and optimization of the effective surface area, pore size and porosity for applications such as heterogeneous catalysis, and gas separation and storage. Properties such as adsorption uptake, capacity, equilibrium constants and Gibbs free energy are dependent on the composition and structure of both the gas and the adsorbent. However, challenges remain, in accurately calculating these properties from experimental data. Gas adsorption experiments involve measuring the amounts of gas adsorbed over a range of pressures under isothermal conditions. Various constant-parameter models, such as Langmuir and Brunauer-Emmett-Teller (BET) theories are used to provide information on adsorbate and adsorbent properties from the isotherm data. These models typically do not provide accurate interpretations across the full range of pressures and temperatures. The Langmuir adsorption isotherm is a simple approximation for modelling equilibrium adsorption data and has been effective in estimating surface areas and catalytic rate laws, particularly for high surface area solids. The Langmuir isotherm assumes the systematic filling of identical adsorption sites to a monolayer coverage. The BET model is based on the Langmuir isotherm and allows for the formation of multiple layers. These additional layers do not interact with the first layer and the energetics are equal to the adsorbate as a bulk liquid. This BET method is widely used to measure the specific surface area of materials. Both Langmuir and BET models assume that the affinity of the gas for all adsorption sites are identical and so the calculated adsorbent uptake at the monolayer and equilibrium constant are independent of coverage and pressure. Accurate representations of adsorption data have been achieved by extending the Langmuir and BET models to include pressure-varying uptake capacities and equilibrium constants. These parameters are determined using a novel regression technique called flexible least squares for time-varying linear regression. For isothermal adsorption the adsorption parameters are assumed to vary slowly and smoothly with increasing pressure. The flexible least squares for pressure-varying linear regression (FLS-PVLR) approach assumes two distinct types of discrepancy terms, dynamic and measurement for all parameters in the linear equation used to simulate the data. Dynamic terms account for pressure variation in successive parameter vectors, and measurement terms account for differences between observed and theoretically predicted outcomes via linear regression. The resultant pressure-varying parameters are optimized by minimizing both dynamic and measurement residual squared errors. Validation of this methodology has been achieved by simulating adsorption data for n-butane and isobutane on activated carbon at 298 K, 323 K and 348 K and for nitrogen on mesoporous alumina at 77 K with pressure-varying Langmuir and BET adsorption parameters (equilibrium constants and uptake capacities). This modeling provides information on the adsorbent (accessible surface area and micropore volume), adsorbate (molecular areas and volumes) and thermodynamic (Gibbs free energies) variations of the adsorption sites.

Keywords: Langmuir adsorption isotherm, BET adsorption isotherm, pressure-varying adsorption parameters, adsorbate and adsorbent properties and energetics

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Amesh P, Suneesh A S, Venkatesan K A

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The magnetic solid-phase extraction is a relatively new method among the other solid-phase extraction techniques for the separating of metal ions from aqueous solutions, such as mine water and groundwater, contaminated wastes, etc. However, the bare magnetic particles (Fe3O4) exhibit poor selectivity due to the absence of target-specific functional groups for sequestering the metal ions. The selectivity of these magnetic particles can be remarkably improved by covalently tethering the task-specific ligands on magnetic surfaces. The magnetic particles offer a number of advantages such as quick phase separation aided by the external magnetic field. As a result, the solid adsorbent can be prepared with the particle size ranging from a few micrometers to the nanometer, which again offers the advantages such as enhanced kinetics of extraction, higher extraction capacity, etc. Conventionally, the magnetite (Fe3O4) particles were prepared by the hydrolysis and co-precipitation of ferrous and ferric salts in aqueous ammonia solution. Since the covalent linking of task-specific functionalities on Fe3O4 was difficult, and it is also susceptible to redox reaction in the presence of acid or alkali, it is necessary to modify the surface of Fe3O4 by silica coating. This silica coating is usually carried out by hydrolysis and condensation of tetraethyl orthosilicate over the surface of magnetite to yield a thin layer of silica-coated magnetite particles. Since the silica-coated magnetite particles amenable for further surface modification, it can be reacted with task-specific functional groups to obtain the functionalized magnetic particles. The surface area exhibited by such magnetic particles usually falls in the range of 50 to 150 m2.g-1, which offer advantage such as quick phase separation, as compared to the other solid-phase extraction systems. In addition, the magnetic (Fe3O4) particles covalently linked on mesoporous silica matrix (MCM-41) and task-specific ligands offer further advantages in terms of extraction kinetics, high stability, longer reusable cycles, and metal extraction capacity, due to the large surface area, ample porosity and enhanced number of functional groups per unit area on these adsorbents. In view of this, the present paper deals with the synthesis of uranium specific diethylenetriamine ligand (DETA) ligand anchored on silica-coated magnetite (Fe-DETA) as well as on magnetic mesoporous silica (MCM-Fe-DETA) and studies on the extraction of uranium from aqueous solution spiked with uranium to mimic the mine water or groundwater contaminated with uranium. The synthesized solid-phase adsorbents were characterized by FT-IR, Raman, TG-DTA, XRD, and SEM. The extraction behavior of uranium on the solid-phase was studied under several conditions like the effect of pH, initial concentration of uranium, rate of extraction and its variation with pH and initial concentration of uranium, effect of interference ions like CO32-, Na+, Fe+2, Ni+2, and Cr+3, etc. The maximum extraction capacity of 233 mg.g-1 was obtained for Fe-DETA, and a huge capacity of 1047 mg.g-1 was obtained for MCM-Fe-DETA. The mechanism of extraction, speciation of uranium, extraction studies, reusability, and the other results obtained in the present study suggests Fe-DETA and MCM-Fe-DETA are the potential candidates for the extraction of uranium from mine water, and groundwater.

Keywords: diethylenetriamine, magnetic mesoporous silica, magnetic solid-phase extraction, uranium extraction, wastewater treatment

Procedia PDF Downloads 168

Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Leinig Antônio Perazolli, Maria Aparecida Zaghete

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SnO2 has electrical conductivity due to the excess of electrons and structural defects, being its electrical behavior highly dependent on sintering temperature and chemical composition. The addition of metals modifiers into the crystalline structure can improve and controlling the behavior of some semiconductor oxides that can therefore develop different applications such as varistors (ceramic with non-ohmic behavior between current and voltage, i.e. conductive during normal operation and resistive during overvoltage). The polymeric precursor method, based on the complexation reaction between metal ion and policarboxylic acid and then polymerized with ethylene glycol, was used to obtain nanopowders ceramic. The metal immobilization reduces its segregation during the decomposition of the polyester resulting in a crystalline oxide with high chemical homogeneity. The preparation of films from ceramics nanoparticles using electrophoretic deposition method (EPD) brings prospects for a new generation of smaller size devices with easy integration technology. EPD allows to control time and current and therefore it can have control of the thickness, surface roughness and the film density, quickly and with low production costs. The sintering process is key to control size and grain boundary density of the film. In this step, there is the diffusion of metals that promote densification and control of intrinsic defects or change these defects which will form and modify the potential barrier in the grain boundary. The use of microwave oven for sintering is an advantageous process due to the fast and homogeneous heating rate, promoting the diffusion and densification without irregular grain growth. This research was done a comparative study of sintering temperature by use of zinc as modifier agent to verify the influence on sintering step aiming to promote densification and grain growth, which influences the potential barrier formation and then changed the electrical behavior. SnO2-nanoparticles were obtained with 1 %mol of ZnO + 0.05 %mol of Nb2O5 (SZN), deposited as film through EPD (voltage 2 kV, time of 10 min) on Si/Pt substrate. Sintering was made in a microwave oven at 800, 900 and 1000 °C. For complete coverage of the substrate by nanoparticles with low surface roughness and uniform thickness was added 0.02 g of solid iodine in alcoholic suspension SnO2 to increase particle surface charge. They were also used magneto in EPD system that improved the deposition rate forming a compact film. Using a scanning electron microscope of high resolution (SEM_FEG) it was observed nanoparticles with average size between 10-20 nm, after sintering the average size was 150 to 200 nm and thickness of 5 µm. Also, it was verified that the temperature at 1000 °C was the most efficient in sintering. The best sintering time was also recorded and determined as 40 minutes. After sintering, the films were recovered with Cr3+ ions layer by EPD, then the films were again thermally treated. The electrical characterizations (nonlinear coefficient of 11.4, voltage rupture of ~60 V and leakage current = 4.8x10−6 A), allow considering the new methodology suitable for prepare SnO2-based varistor applied for development of electrical protection devices for low voltage.

Keywords: chemical synthesis, electrophoretic deposition, microwave sintering, tin dioxide

Procedia PDF Downloads 271

Authors: Joana Pimenta, Lorena Coelho, José Silva, Vanessa Miranda, Jorge Laranjeira, Rui Soares

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In this paper, the results of R&D on an innovative food package for increased shelf-life are presented. SAP4MA aims at the development of a printed active device that enables smart packaging solutions for food preservation, targeting the extension of the shelf-life of the packed food through the controlled release of active natural antioxidant agents at the onset of the food degradation process. To do so, SAP4MA focuses on the development of active devices such as printed heaters and batteries/supercapacitors in a label format to be integrated on packaging lids during its injection molding process, promoting the passive release of natural antioxidants after the product is packed, during transportation and in the shelves, and actively when the end-user activates the package, just prior to consuming the product at home. When the active device present on the lid is activated, the release of the natural antioxidants embedded in the inner layer of the packaging lid in direct contact with the headspace atmosphere of the food package starts. This approach is based on the use of active functional coatings composed of nano encapsulated active agents (natural antioxidants species) in the prevention of the oxidation of lipid compounds in food by agents such as oxygen. Thus keeping the product quality during the shelf-life, not only when the user opens the packaging, but also during the period from food packaging up until the purchase by the consumer. The active systems that make up the printed smart label, heating circuit, and battery were developed using screen-printing technology. These systems must operate under the working conditions associated with this application. The printed heating circuit was studied using three different substrates and two different conductive inks. Inks were selected, taking into consideration that the printed circuits will be subjected to high pressures and temperatures during the injection molding process. The circuit must reach a homogeneous temperature of 40ºC in the entire area of the lid of the food tub, promoting a gradual and controlled release of the antioxidant agents. In addition, the circuit design involves a high level of study in order to guarantee maximum performance after the injection process and meet the specifications required by the control electronics component. Furthermore, to characterize the different heating circuits, the electrical resistance promoted by the conductive ink and the circuit design, as well as the thermal behavior of printed circuits on different substrates, were evaluated. In the injection molding process, the serpentine-shaped design developed for the heating circuit was able to resolve the issues connected to the injection point; in addition, the materials used in the support and printing had high mechanical resistance against the pressure and temperature inherent to the injection process. Acknowledgment: This research has been carried out within the Project “Smart and Active Packing for Margarine Product” (SAP4MA) running under the EURIPIDES Program being co-financed by COMPETE 2020 – the Operational Programme for Competitiveness and Internationalization and under Portugal 2020 through the European Regional Development Fund (ERDF).

Keywords: smart package, printed heat circuits, printed batteries, flexible and printed electronic

Procedia PDF Downloads 109

Authors: Mirosław Krzemieniewski, Marcin Zieliński, Marcin Dębowski

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Electrokinetic disintegration is one of the high-voltage electric methods. The design of systems is exceptionally simple. Biomass flows through a system of pipes with alongside mounted electrodes that generate an electric field. Discharges in the electric field deform cell walls and lead to their successive perforation, thereby making their contents easily available to bacteria. The spark-over occurs between electrode surface and pipe jacket which is the second pole and closes the circuit. The value of voltage ranges from 10 to 100kV. Electrodes are supplied by normal “power grid” monophase electric current (230V, 50Hz). Next, the electric current changes into direct current of 24V in modules serving for particular electrodes, and this current directly feeds the electrodes. The installation is completely safe because the value of generated current does not exceed 250mA and because conductors are grounded. Therefore, there is no risk of electric shock posed to the personnel, even in the case of failure or incorrect connection. Low values of the electric current mean small energy consumption by the electrode which is extremely low – only 35W per electrode – compared to other methods of disintegration. Pipes with electrodes with diameter of DN150 are made of acid-proof steel and connected from both sides with 90º elbows ended with flanges. The available S and U types of pipes enable very convenient fitting with system construction in the existing installations and rooms or facilitate space management in new applications. The system of pipes for electrokinetic disintegration may be installed horizontally, vertically, askew, on special stands or also directly on the wall of a room. The number of pipes and electrodes is determined by operating conditions as well as the quantity of substrate, type of biomass, content of dry matter, method of disintegration (single or circulatory), mounting site etc. The most effective method involves pre-treatment of substrate that may be pumped through the disintegration system on the way to the fermentation tank or recirculated in a buffered intermediate tank (substrate mixing tank). Biomass structure destruction in the process of electrokinetic disintegration causes shortening of substrate retention time in the tank and acceleration of biogas production. A significant intensification of the fermentation process was observed in the systems operating in the technical scale, with the greatest increase in biogas production reaching 18%. The secondary, but highly significant for the energetic balance, effect is a tangible decrease of energy input by agitators in tanks. It is due to reduced viscosity of the biomass after disintegration, and may result in energy savings reaching even 20-30% of the earlier noted consumption. Other observed phenomena include reduction in the layer of surface scum, reduced sewage capability for foaming and successive decrease in the quantity of bottom sludge banks. Considering the above, the system for electrokinetic disintegration seems a very interesting and valuable solutions meeting the offer of specialist equipment for the processing of plant biomass, including Virginia fanpetals, before the process of methane fermentation.

Keywords: electrokinetic disintegration, biomass, biogas production, fermentation, Virginia fanpetals

Procedia PDF Downloads 377

Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

Procedia PDF Downloads 241

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

Procedia PDF Downloads 339

Authors: Inna Kornienko, Svetlana Guryeva, Anatoly Shekhter, Elena Petersen

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Transplantation is an effective treatment option for patients suffering from different end-stage diseases. However, it is plagued by a constant shortage of donor organs and the subsequent need of a lifelong immunosuppressive therapy for the patient. Currently some researchers look towards using of pig organs to replace human organs for transplantation since the matrix derived from porcine organs is a convenient substitute for the human matrix. As an initial step to create a new ex vivo tissue engineered model, optimized protocols have been created to obtain organ-specific acellular matrices and evaluated their potential as tissue engineered scaffolds for culture of normal cells and tumor cell lines. These protocols include decellularization by perfusion in a bioreactor system and immersion-agitation on an orbital shaker with use of various detergents (SDS, Triton X-100) and freezing. Complete decellularization – in terms of residual DNA amount – is an important predictor of probability of immune rejection of materials of natural origin. However, the signs of cellular material may still remain within the matrix even after harsh decellularization protocols. In this regard, the matrices obtained from tissues of low-immunogenic pigs with α3Galactosyl-tranferase gene knock out (GalT-KO) may be a promising alternative to native animal sources. The research included a study of induced effect of frozen and fresh fragments of GalT-KO skin on healing of full-thickness plane wounds in 80 rats. Commercially available wound dressings (Ksenoderm, Hyamatrix and Alloderm) as well as allogenic skin were used as a positive control and untreated wounds were analyzed as a negative control. The results were evaluated on the 4th day after grafting, which corresponds to the time of start of normal wound epithelization. It has been shown that a non-specific immune response in models treated with GalT-Ko pig skin was milder than in all the control groups. Research has been performed to measure technical skin characteristics: stiffness and elasticity properties, corneometry, tevametry, and cutometry. These metrics enabled the evaluation of hydratation level, corneous layer husking level, as well as skin elasticity and micro- and macro-landscape. These preliminary data may contribute to development of personalized transplantable organs from GalT-Ko pigs with significantly limited potential of immune rejection. By applying growth factors to a decellularized skin sample it is possible to achieve various regenerative effects based on the particular situation. In this particular research BMP2 and Heparin-binding EGF-like growth factor have been used. Ideally, a bioengineered organ must be biocompatible, non-immunogenic and support cell growth. Porcine organs are attractive for xenotransplantation if severe immunologic concerns can be bypassed. The results indicate that genetically modified pig tissues with knock-outed α3Galactosyl-tranferase gene may be used for production of low-immunogenic matrix suitable for transplantation.

Keywords: decellularization, low-immunogenic, matrix, scaffolds, transplants

Procedia PDF Downloads 275

Authors: Slawomir Wnuk

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Due to widespread implementation of the renewable energy development programs the, solar energy use increasing constantlyacross the world. Accordingly to REN21, in 2020, both on-grid and off-grid solar photovoltaic systems installed capacity reached 760 GWDCand increased by 139 GWDC compared to previous year capacity. However, the photovoltaic solar cells used for primary solar energy conversion into electrical energy has exhibited significant drawbacks. The fundamentaldownside is unstable andlow efficiencythe energy conversion being negatively affected by a rangeof factors. To neutralise or minimise the impact of those factors causing energy losses, researchers have come out withvariedideas. One ofpromising technological solutionsoffered by researchers is PV-MTEG multilayer hybrid system combiningboth photovoltaic cells and thermoelectric generators advantages. A series of experiments was performed on Glasgow Caledonian University laboratory to investigate such a system in operation. In the experiments, the solar simulator Sol3A series was employed as a stable solar irradiation source, and multichannel voltage and temperature data loggers were utilised for measurements. The two layer proposed hybrid systemsimulation model was built up and tested for its energy conversion capability under a variety of the exposure angles to the solar irradiation with a concurrent examination of the temperature distribution inside proposed PV-MTEG structure. The same series of laboratory tests were carried out for a range of various loads, with the temperature and voltage generated being measured and recordedfor each exposure angle and load combination. It was found that increase of the exposure angle of the PV-MTEG structure to an irradiation source causes the decrease of the temperature gradient ΔT between the system layers as well as reduces overall system heating. The temperature gradient’s reduction influences negatively the voltage generation process. The experiments showed that for the exposureangles in the range from 0° to 45°, the ‘generated voltage – exposure angle’ dependence is reflected closely by the linear characteristics. It was also found that the voltage generated by MTEG structures working with the optimal load determined and applied would drop by approximately 0.82% per each 1° degree of the exposure angle increase. This voltage drop occurs at the higher loads applied, getting more steep with increasing the load over the optimal value, however, the difference isn’t significant. Despite of linear character of the generated by MTEG voltage-angle dependence, the temperature reduction between the system structure layers andat tested points on its surface was not linear. In conclusion, the PV-MTEG exposure angle appears to be important parameter affecting efficiency of the energy generation by thermo-electrical generators incorporated inside those hybrid structures. The research revealedgreat potential of the proposed hybrid system. The experiments indicated interesting behaviour of the tested structures, and the results appear to provide valuable contribution into thedevelopment and technological design process for large energy conversion systems utilising similar structural solutions.

Keywords: photovoltaic solar systems, hybrid systems, thermo-electrical generators, renewable energy

Procedia PDF Downloads 89

Authors: Mikaela Kutrolli, Noah S. Pereira, Vanessa Scanlon, Mohamadmahdi Samandari, Ali Tamayol

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Bone tissue engineering has drawn significant attention and various biomaterials have been tested. Polymers such as polycaprolactone (PCL) offer excellent biocompatibility, reasonable mechanical properties, and biodegradability. However, PCL scaffolds suffer a critical drawback: a lack of micro/mesoporosity, affecting cell attachment, tissue integration, and mineralization. It also results in a slow degradation rate. While 3D-printing has addressed the issue of macroporosity through CAD-guided fabrication, PCL scaffolds still exhibit poor smaller-scale porosity. To overcome this, we generated composites of PCL, hydroxyapatite (HA), and powdered sucrose (PS). The latter serves as a sacrificial material to generate porous particles after sucrose dissolution. Additionally, we have incorporated dexamethasone (DEX) to boost the PCL osteogenic properties. The resulting scaffolds maintain controlled macroporosity from the lattice print structure but also develop micro/mesoporosity within PCL fibers when exposed to aqueous environments. The study involved mixing PS into solvent-dissolved PCL in different weight ratios of PS to PCL (70:30, 50:50, and 30:70 wt%). The resulting composite was used for 3D printing of scaffolds at room temperature. Printability was optimized by adjusting pressure, speed, and layer height through filament collapse and fusion test. Enzymatic degradation, porogen leaching, and DEX release profiles were characterized. Physical properties were assessed using wettability, SEM, and micro-CT to quantify the porosity (percentage, pore size, and interconnectivity). Raman spectroscopy was used to verify the absence of sugar after leaching. Mechanical characteristics were evaluated via compression testing before and after porogen leaching. Bone marrow stromal cells (BMSCs) behavior in the printed scaffolds was studied by assessing viability, metabolic activity, osteo-differentiation, and mineralization. The scaffolds with a 70% sugar concentration exhibited superior printability and reached the highest porosity of 80%, but performed poorly during mechanical testing. A 50% PS concentration demonstrated a 70% porosity, with an average pore size of 25 µm, favoring cell attachment. No trace of sucrose was found in Raman after leaching the sugar for 8 hours. Water contact angle results show improved hydrophilicity as the sugar concentration increased, making the scaffolds more conductive to cell adhesion. The behavior of bone marrow stromal cells (BMSCs) showed positive viability and proliferation results with an increasing trend of mineralization and osteo-differentiation as the sucrose concentration increased. The addition of HA and DEX also promoted mineralization and osteo-differentiation in the cultures. The integration of PS as porogen at a concentration of 50%wt within PCL scaffolds presents a promising approach to address the poor cell attachment and tissue integration issues of PCL in bone tissue engineering. The method allows for the fabrication of scaffolds with tunable porosity and mechanical properties, suitable for various applications. The addition of HA and DEX further enhanced the scaffolds. Future studies will apply the scaffolds in an in-vivo model to thoroughly investigate their performance.

Keywords: bone, PCL, 3D printing, tissue engineering

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Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

Procedia PDF Downloads 134

Authors: Prachi Buche Marathe

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Karanja Laad is a city located in the Vidarbha region in the state of Maharashtra, India. It has a huge amount of tangible and intangible heritage in the form of monuments, precincts, a group of structures, festivals and procession route, which is neglected and lost with time. Three different religions Hinduism, Islam and Jainism along with associations of being a birthplace of Swami Nrusinha Saraswati, an exponent of Datta Sampradaya sect and the British colonial layer have shaped the culture and society of the place over the period. The architecture of the town Karanja Laad has enhanced its unique historic and cultural value with a combination of all these historic layers. Karanja Laad is also a traditional trading historic town with unique hybrid architectural style and has a good potential for developing as a tourist place along with the present image of a pilgrim destination of Datta Sampradaya. The aim of the research is to prepare a conservation proposal for the historic town along with the management framework. Objectives of the research are to study the evolution of Karanja town, to identify the cultural resources along with issues of the historic core of the city, to understand Datta sampradaya, and contribution of Saint Nrusinha Saraswati in the religious sect and his association as an important personality with Karanja. The methodology of the research is site visits to the Karanja city, making field surveys for documentation and discussions and questionnaires with the residents to establish heritage and identify potential and issues within the historic core thereby establishing a case for conservation. Field surveys are conducted for town level study of land use, open spaces, occupancy, ownership, traditional commodity and community, infrastructure, streetscapes, and precinct activities during the festival and non-festival period. Building level study includes establishing various typologies like residential, institutional commercial, religious, and traditional infrastructure from the mythological references like waterbodies (kund), lake and wells. One of the main issues is that the loss of the traditional footprint as well as the traditional open spaces which are getting lost due to the new illegal encroachments and lack of guidelines for the new additions to conserve the original fabric of the structures. Traditional commodities are getting lost since there is no promotion of these skills like pottery and painting. Lavish bungalows like Kannava mansion, main temple Wada (birthplace of the saint) have a huge potential to be developed as a museum by adaptive re-use which will, in turn, attract many visitors during festivals which will boost the economy. Festival procession routes can be identified and a heritage walk can be developed so as to highlight the traditional features of the town. Overall study has resulted in establishing a heritage map with 137 heritage structures identified as potential. Conservation proposal is worked out on the town level, precinct level and building level with interventions such as developing construction guidelines for further development and establishing a heritage cell consisting architects and engineers for the upliftment of the existing rich heritage of the Karanja city.

Keywords: built heritage, conservation, Datta Sampradaya, Karanja Laad, Swami Nrusinha Saraswati, procession route

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Authors: Sugandha Gupta, Arun Kumar Jha

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A large number of ferroelectric materials have been intensely investigated for applications in non-volatile ferroelectric random access memories (FeRAMs), piezoelectric transducers, actuators, pyroelectric sensors, high dielectric constant capacitors, etc. Bismuth layered ferroelectric materials such as Strontium Bismuth Tantalate (SBT) has attracted a lot of attention due to low leakage current, high remnant polarization and high fatigue endurance up to 1012 switching cycles. However, pure SBT suffers from various major limitations such as high dielectric loss, low remnant polarization values, high processing temperature, bismuth volatilization, etc. Significant efforts have been made to improve the dielectric and ferroelectric properties of this compound. Firstly, it has been reported that electrical properties vary with the Sr/ Bi content ratio in the SrBi2Ta2O9 compsition i.e. non-stoichiometric compositions with Sr-deficient / Bi excess content have higher remnant polarization values than stoichiometic SBT compositions. With the objective to improve structural, dielectric, ferroelectric and piezoelectric properties of SBT compound, rare earth holmium (Ho3+) was chosen as a donor cation for substitution onto the Bi2O2 layer. Moreover, hardly any report on holmium substitution in stoichiometric SrBi2Ta2O9 and non-stoichiometric Sr0.8Bi2.2Ta2O9 compositions were available in the literature. The holmium substituted SrBi2-xHoxTa2O9 (x= 0.00-2.0) and Sr0.8Bi2.2Ta2O9 (x=0.0 and 0.01) compositions were synthesized by the solid state reaction method. The synthesized specimens were characterized for their structural and electrical properties. X-ray diffractograms reveal single phase layered perovskite structure formation for holmium content in stoichiometric SBT samples up to x ≤ 0.1. The granular morphology of the samples was investigated using scanning electron microscope (Hitachi, S-3700 N). The dielectric measurements were carried out using a precision LCR meter (Agilent 4284A) operating at oscillation amplitude of 1V. The variation of dielectric constant with temperature shows that the Curie temperature (Tc) decreases on increasing the holmium content. The specimen with x=2.0 i.e. the bismuth free specimen, has very low dielectric constant and does not show any appreciable variation with temperature. The dielectric loss reduces significantly with holmium substitution. The polarization–electric field (P–E) hysteresis loops were recorded using a P–E loop tracer based on Sawyer–Tower circuit. It is observed that the ferroelectric property improve with Ho substitution. Holmium substituted specimen exhibits enhanced value of remnant polarization (Pr= 9.22 μC/cm²) as compared to holmium free specimen (Pr= 2.55 μC/cm²). Piezoelectric co-efficient (d33 values) was measured using a piezo meter system (Piezo Test PM300). It is observed that holmium substitution enhances piezoelectric coefficient. Further, the optimized holmium content (x=0.01) in stoichiometric SrBi2-xHoxTa2O9 composition has been substituted in non-stoichiometric Sr0.8Bi2.2Ta2O9 composition to obtain further enhanced structural and electrical characteristics. It is expected that a new class of ferroelectric materials i.e. Rare Earth Layered Structured Ferroelectrics (RLSF) derived from Bismuth Layered Structured Ferroelectrics (BLSF) will generate which can be used to replace static (SRAM) and dynamic (DRAM) random access memories with ferroelectric random access memories (FeRAMS).

Keywords: dielectrics, ferroelectrics, piezoelectrics, strontium bismuth tantalate

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Authors: Alper T. Celebi, Ali Beskok

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Electroosmotic (EO) slip flows in nanochannels are investigated using non-equilibrium molecular dynamics (MD) simulations, and the results are compared with analytical solution of Poisson-Boltzmann and Stokes (PB-S) equations with slip contribution. The ultimate objective of this study is to show that well-known continuum flow model can accurately predict the EO velocity profiles in nanochannels using the slip lengths and apparent viscosities obtained from force-driven flow simulations performed at various liquid-wall interaction strengths. EO flow of aqueous NaCl solution in silicon nanochannels are simulated under realistic electrochemical conditions within the validity region of Poisson-Boltzmann theory. A physical surface charge density is determined for nanochannels based on dissociations of silanol functional groups on channel surfaces at known salt concentration, temperature and local pH. First, we present results of density profiles and ion distributions by equilibrium MD simulations, ensuring that the desired thermodynamic state and ionic conditions are satisfied. Next, force-driven nanochannel flow simulations are performed to predict the apparent viscosity of ionic solution between charged surfaces and slip lengths. Parabolic velocity profiles obtained from force-driven flow simulations are fitted to a second-order polynomial equation, where viscosity and slip lengths are quantified by comparing the coefficients of the fitted equation with continuum flow model. Presence of charged surface increases the viscosity of ionic solution while the velocity-slip at wall decreases. Afterwards, EO flow simulations are carried out under uniform electric field for different liquid-wall interaction strengths. Velocity profiles present finite slips near walls, followed with a conventional viscous flow profile in the electrical double layer that reaches a bulk flow region in the center of the channel. The EO flow enhances with increased slip at the walls, which depends on wall-liquid interaction strength and the surface charge. MD velocity profiles are compared with the predictions from analytical solutions of the slip modified PB-S equation, where the slip length and apparent viscosity values are obtained from force-driven flow simulations in charged silicon nano-channels. Our MD results show good agreements with the analytical solutions at various slip conditions, verifying the validity of PB-S equation in nanochannels as small as 3.5 nm. In addition, the continuum model normalizes slip length with the Debye length instead of the channel height, which implies that enhancement in EO flows is independent of the channel height. Further MD simulations performed at different channel heights also shows that the flow enhancement due to slip is independent of the channel height. This is important because slip enhanced EO flow is observable even in micro-channels experiments by using a hydrophobic channel with large slip and high conductivity solutions with small Debye length. The present study provides an advanced understanding of EO flows in nanochannels. Correct characterization of nanoscale EO slip flow is crucial to discover the extent of well-known continuum models, which is required for various applications spanning from ion separation to drug delivery and bio-fluidic analysis.

Keywords: electroosmotic flow, molecular dynamics, slip length, velocity-slip

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Authors: Salvatore Brischetto, Domenico Cesare

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Major improvements in future aircraft and spacecraft could be those dependent on an increasing use of conventional and unconventional multilayered structures embedding composite materials, functionally graded materials, piezoelectric or piezomagnetic materials, and soft foam or honeycomb cores. Layers made of such materials can be combined in different ways to obtain structures that are able to fulfill several structural requirements. The next generation of aircraft and spacecraft will be manufactured as multilayered structures under the action of a combination of two or more physical fields. In multifield problems for multilayered structures, several physical fields (thermal, hygroscopic, electric and magnetic ones) interact each other with different levels of influence and importance. An exact 3D shell model is here proposed for these types of analyses. This model is based on a coupled system including 3D equilibrium equations, 3D Fourier heat conduction equation, 3D Fick diffusion equation and electric and magnetic divergence equations. The set of partial differential equations of second order in z is written using a mixed curvilinear orthogonal reference system valid for spherical and cylindrical shell panels, cylinders and plates. The order of partial differential equations is reduced to the first one thanks to the redoubling of the number of variables. The solution in the thickness z direction is obtained by means of the exponential matrix method and the correct imposition of interlaminar continuity conditions in terms of displacements, transverse stresses, electric and magnetic potentials, temperature, moisture content and transverse normal multifield fluxes. The investigated structures have simply supported sides in order to obtain a closed form solution in the in-plane directions. Moreover, a layerwise approach is proposed which allows a 3D correct description of multilayered anisotropic structures subjected to field loads. Several results will be proposed in tabular and graphical formto evaluate displacements, stresses and strains when mechanical loads, temperature gradients, moisture content gradients, electric potentials and magnetic potentials are applied at the external surfaces of the structures in steady-state conditions. In the case of inclusions of piezoelectric and piezomagnetic layers in the multilayered structures, so called smart structures are obtained. In this case, a free vibration analysis in open and closed circuit configurations and a static analysis for sensor and actuator applications will be proposed. The proposed results will be useful to better understand the physical and structural behaviour of multilayered advanced composite structures in the case of multifield interactions. Moreover, these analytical results could be used as reference solutions for those scientists interested in the development of 3D and 2D numerical shell/plate models based, for example, on the finite element approach or on the differential quadrature methodology. The correct impositions of boundary geometrical and load conditions, interlaminar continuity conditions and the zigzag behaviour description due to transverse anisotropy will be also discussed and verified.

Keywords: composite structures, 3D shell model, stress analysis, multifield loads, exponential matrix method, layer wise approach

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Authors: Dace Grauda, Inta Belogrudova, Alexei Katashev, Linda Lancere, Isaak Rashal

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The goal of study was the elaboration of easy applicable flow cytometry method for detection of influence of abiotic stress factors on plants, which could be useful for detection of environmental stresses in urban areas. The lime tree Tillia vulgaris H. is a popular tree species used for urban landscaping in Europe and is one of the main species of street greenery in Riga, Latvia. Tree decline and low vitality has observed in the central part of Riga. For this reason lime trees were select as a model object for the investigation. During the period of end of June and beginning of July 12 samples from different urban environment locations as well as plant material from a greenhouse were collected. BD FACSJazz® cell sorter (BD Biosciences, USA) with flow cytometer function was used to test viability of plant cells. The method was based on changes of relative fluorescence intensity of cells in blue laser (488 nm) after influence of stress factors. SpheroTM rainbow calibration particles (3.0–3.4 μm, BD Biosciences, USA) in phosphate buffered saline (PBS) were used for calibration of flow cytometer. BD PharmingenTM PBS (BD Biosciences, USA) was used for flow cytometry assays. The mean fluorescence intensity information from the purified cell suspension samples was recorded. Preliminary, multiple gate sizes and shapes were tested to find one with the lowest CV. It was found that low CV can be obtained if only the densest part of plant cells forward scatter/side scatter profile is analysed because in this case plant cells are most similar in size and shape. The young pollen cells in one nucleus stage were found as the best for detection of influence of abiotic stress. For experiments only fresh plant material was used– the buds of Tillia vulgaris with diameter 2 mm. For the cell suspension (in vitro culture) establishment modified protocol of microspore culture was applied. The cells were suspended in the MS (Murashige and Skoog) medium. For imitation of dust of urban area SiO2 nanoparticles with concentration 0.001 g/ml were dissolved in distilled water. Into 10 ml of cell suspension 1 ml of SiO2 nanoparticles suspension was added, then cells were incubated in speed shaking regime for 1 and 3 hours. As a stress factor the irradiation of cells for 20 min by UV was used (Hamamatsu light source L9566-02A, L10852 lamp, A10014-50-0110), maximum relative intensity (100%) at 365 nm and at ~310 nm (75%). Before UV irradiation the suspension of cells were placed onto a thin layer on a filter paper disk (diameter 45 mm) in a Petri dish with solid MS media. Cells without treatment were used as a control. Experiments were performed at room temperature (23-25 °C). Using flow cytometer BS FACS Software cells plot was created to determine the densest part, which was later gated using oval-shaped gate. Gate included from 95 to 99% of all cells. To determine relative fluorescence of cells logarithmic fluorescence scale in arbitrary fluorescence units were used. 3x103 gated cells were analysed from the each sample. The significant differences were found among relative fluorescence of cells from different trees after treatment with SiO2 nanoparticles and UV irradiation in comparison with the control.

Keywords: flow cytometry, fluorescence, SiO2 nanoparticles, UV irradiation

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Authors: Tamal Roy, Anuradha Bhat

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Cognitive abilities aid fishes in foraging, avoiding predators & locating mates. Factors like predation pressure & habitat complexity govern learning & memory in fishes. This study aims to compare spatial learning & memory across four natural populations of zebrafish. Zebrafish, a small cyprinid inhabits a diverse range of freshwater habitats & this makes it amenable to studies investigating role of native environment in spatial cognitive abilities. Four populations were collected across India from waterbodies with contrasting ecological conditions. Habitat complexity of the water-bodies was evaluated as a combination of channel substrate diversity and diversity of vegetation. Experiments were conducted on populations under controlled laboratory conditions. A square shaped spatial testing arena (maze) was constructed for testing the performance of adult zebrafish. The square tank consisted of an inner square shaped layer with the edges connected to the diagonal ends of the tank-walls by connections thereby forming four separate chambers. Each of the four chambers had a main door in the centre. Each chamber had three sections separated by two windows. A removable coloured window-pane (red, yellow, green or blue) identified each main door. A food reward associated with an artificial plant was always placed inside the left-hand section of the red-door chamber. The position of food-reward and plant within the red-door chamber was fixed. A test fish would have to explore the maze by taking turns and locate the food inside the right-side section of the red-door chamber. Fishes were sorted from each population stock and kept individually in separate containers for identification. At a time, a test fish was released into the arena and allowed 20 minutes to explore in order to find the food-reward. In this way, individual fishes were trained through the maze to locate the food reward for eight consecutive days. The position of red door, with the plant and the reward, was shuffled every day. Following training, an intermission of four days was given during which the fishes were not subjected to trials. Post-intermission, the fishes were re-tested on the 13th day following the same protocol for their ability to remember the learnt task. Exploratory tendencies and latency of individuals to explore on 1st day of training, performance time across trials, and number of mistakes made each day were recorded. Additionally, mechanism used by individuals to solve the maze each day was analyzed across populations. Fishes could be expected to use algorithm (sequence of turns) or associative cues in locating the food reward. Individuals of populations did not differ significantly in latencies and tendencies to explore. No relationship was found between exploration and learning across populations. High habitat-complexity populations had higher rates of learning & stronger memory while low habitat-complexity populations had lower rates of learning and much reduced abilities to remember. High habitat-complexity populations used associative cues more than algorithm for learning and remembering while low habitat-complexity populations used both equally. The study, therefore, helped understand the role of natural ecology in explaining variations in spatial learning abilities across populations.

Keywords: algorithm, associative cue, habitat complexity, population, spatial learning

Procedia PDF Downloads 287

Authors: Milos Travar, Jovana Nikolov, Andrej Vranicar, Natasa Todorovic

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Over the years, High Purity Germanium (HPGe) detectors proved to be an excellent practical tool and, as such, have established their today's wide use in low background γ-spectrometry. One of the advantages of gamma-ray spectrometry is its easy sample preparation as chemical processing and separation of the studied subject are not required. Thus, with a single measurement, one can simultaneously perform both qualitative and quantitative analysis. One of the most prominent features of HPGe detectors, besides their excellent efficiency, is their superior resolution. This feature virtually allows a researcher to perform a thorough analysis by discriminating photons of similar energies in the studied spectra where otherwise they would superimpose within a single-energy peak and, as such, could potentially scathe analysis and produce wrongly assessed results. Naturally, this feature is of great importance when the identification of radionuclides, as well as their activity concentrations, is being practiced where high precision comes as a necessity. In measurements of this nature, in order to be able to reproduce good and trustworthy results, one has to have initially performed an adequate full-energy peak (FEP) efficiency calibration of the used equipment. However, experimental determination of the response, i.e., efficiency curves for a given detector-sample configuration and its geometry, is not always easy and requires a certain set of reference calibration sources in order to account for and cover broader energy ranges of interest. With the goal of overcoming these difficulties, a lot of researches turned towards the application of different software toolkits that implement the Monte Carlo method (e.g., MCNP, FLUKA, PENELOPE, Geant4, etc.), as it has proven time and time again to be a very powerful tool. In the process of creating a reliable model, one has to have well-established and described specifications of the detector. Unfortunately, the documentation that manufacturers provide alongside the equipment is rarely sufficient enough for this purpose. Furthermore, certain parameters tend to evolve and change over time, especially with older equipment. Deterioration of these parameters consequently decreases the active volume of the crystal and can thus affect the efficiencies by a large margin if they are not properly taken into account. In this study, the optimisation method of two HPGe detectors through the implementation of the Geant4 toolkit developed by CERN is described, with the goal of further improving simulation accuracy in calculations of FEP efficiencies by investigating the influence of certain detector variables (e.g., crystal-to-window distance, dead layer thicknesses, inner crystal’s void dimensions, etc.). Detectors on which the optimisation procedures were carried out were a standard traditional co-axial extended range detector (XtRa HPGe, CANBERRA) and a broad energy range planar detector (BEGe, CANBERRA). Optimised models were verified through comparison with experimentally obtained data from measurements of a set of point-like radioactive sources. Acquired results of both detectors displayed good agreement with experimental data that falls under an average statistical uncertainty of ∼ 4.6% for XtRa and ∼ 1.8% for BEGe detector within the energy range of 59.4−1836.1 [keV] and 59.4−1212.9 [keV], respectively.

Keywords: HPGe detector, γ spectrometry, efficiency, Geant4 simulation, Monte Carlo method

Procedia PDF Downloads 119

Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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Authors: Chandra Shekhar Prasad, Ludek Pesek Prasad

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In the present day fan blade of aero engine, turboprop propellers, gas turbine or steam turbine low-pressure blades are getting bigger, lighter and thus, become more flexible. Therefore, flutter, forced blade response and vibration related failure of the high aspect ratio blade are of main concern for the designers, thus need to be address properly in order to achieve successful component design. At the preliminary design stage large number of design iteration is need to achieve the utter free safe design. Most of the numerical method used for aeroelastic analysis is based on field-based methods such as finite difference method, finite element method, finite volume method or coupled. These numerical schemes are used to solve the coupled fluid Flow-Structural equation based on full Naiver-Stokes (NS) along with structural mechanics’ equations. These type of schemes provides very accurate results if modeled properly, however, they are computationally very expensive and need large computing recourse along with good personal expertise. Therefore, it is not the first choice for aeroelastic analysis during preliminary design phase. A reduced order aeroelastic model (ROAM) with acceptable accuracy and fast execution is more demanded at this stage. Similar ROAM are being used by other researchers for aeroelastic and force response analysis of turbomachinery. In the present paper new medium fidelity ROAM is successfully developed and implemented in numerical tool to simulated the aeroelastic stability phenomena in turbomachinery and well as flexible wings. In the present, a hybrid flow solver based on 3D viscous-inviscid coupled 3D panel method (PM) and 3d discrete vortex particle method (DVM) is developed, viscous parameters are estimated using boundary layer(BL) approach. This method can simulate flow separation and is a good compromise between accuracy and speed compared to CFD. In the second phase of the research work, the flow solver (PM) will be coupled with ROM non-linear beam element method (BEM) based FEM structural solver (with multibody capabilities) to perform the complete aeroelastic simulation of a steam turbine bladed disk, propellers, fan blades, aircraft wing etc. The partitioned based coupling approach is used for fluid-structure interaction (FSI). The numerical results are compared with experimental data for different test cases and for the blade cascade test case, experimental data is obtained from in-house lab experiments at IT CAS. Furthermore, the results from the new aeroelastic model will be compared with classical CFD-CSD based aeroelastic models. The proposed methodology for the aeroelastic stability analysis of gas turbine or steam turbine blades, or propellers or fan blades will provide researchers and engineers a fast, cost-effective and efficient tool for aeroelastic (classical flutter) analysis for different design at preliminary design stage where large numbers of design iteration are required in short time frame.

Keywords: aeroelasticity, beam element method (BEM), discrete vortex particle method (DVM), classical flutter, fluid-structure interaction (FSI), panel method, reduce order aeroelastic model (ROAM), turbomachinery, viscous-inviscid coupling

Procedia PDF Downloads 265