Search results for: cubic smoothing spline interpolation

Authors: Zongyan Yang, Gagan K. Jena, Sankar B. Karanam, Noora M. A. Hokal

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Jumeirah First beach, a segment of coastline of length 1.5 km, is one of the popular public beaches in Dubai, UAE. The stability of the beach has been affected by several coastal developmental projects, including The World, Island 2 and La Mer. A comprehensive stabilization scheme comprising of two composite groynes (of lengths 90 m and 125m), modification to the northern breakwater of Jumeirah Fishing Harbour and beach re-nourishment was implemented by Dubai Municipality in 2012. However, the performance of the implemented stabilization scheme has been compromised by La Mer project (built in 2016), which modified the wave climate at the Jumeirah First beach. The objective of the coastal modelling studies is to establish design basis for further beach stabilization scheme(s). Comprehensive coastal modelling studies had been conducted to establish the nearshore wave climate, equilibrium beach orientations and stable beach plan forms. Based on the outcomes of the modeling studies, recommendation had been made to extend the composite groynes to stabilize the Jumeirah First beach. Wave transformation was performed following an interpolation approach with wave transformation matrixes derived from simulations of a possible range of wave conditions in the region. The Dubai coastal wave model is developed with MIKE21 SW. The offshore wave conditions were determined from PERGOS wave data at 4 offshore locations with consideration of the spatial variation. The lateral boundary conditions corresponding to the offshore conditions, at Dubai/Abu Dhabi and Dubai Sharjah borders, were derived with application of LitDrift 1D wave transformation module. The Dubai coastal wave model was calibrated with wave records at monitoring stations operated by Dubai Municipality. The wave transformation matrix approach was validated with nearshore wave measurement at a Dubai Municipality monitoring station in the vicinity of the Jumeirah First beach. One typical year wave time series was transformed to 7 locations in front of the beach to count for the variation of wave conditions which are affected by adjacent and offshore developments. Equilibrium beach orientations were estimated with application of LitDrift by finding the beach orientations with null annual littoral transport at the 7 selected locations. The littoral transport calculation results were compared with beach erosion/accretion quantities estimated from the beach monitoring program (twice a year including bathymetric and topographical surveys). An innovative integral method was developed to outline the stable beach plan forms from the estimated equilibrium beach orientations, with predetermined minimum beach width. The optimal lengths for the composite groyne extensions were recommended based on the stable beach plan forms.

Keywords: composite groyne, equilibrium beach orientation, stable beach plan form, wave transformation matrix

Procedia PDF Downloads 213

Authors: Bolawole F. Ogunbodede, Mokolade Johnson, Adetunji Adejumo

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High population growth rate, reactive infrastructure provision, inability of physical planning to cope with developmental pace are responsible for waste water crisis in the Lagos Metropolis. Septic tank is still the most prevalent waste-water holding system. Unfortunately, there is a dearth of septage treatment infrastructure. Public waste-water treatment system statistics relative to the 23 million people in Lagos State is worrisome. 1.85 billion Cubic meters of wastewater is generated on daily basis and only 5% of the 26 million population is connected to public sewerage system. This is compounded by inadequate budgetary allocation and erratic power supply in the last two decades. This paper explored community participatory waste-water management alternative at Oworonshoki Municipality in Lagos. The study is underpinned by decentralized Waste-water Management systems in built-up areas. The initiative accommodates 5 step waste-water issue including generation, storage, collection, processing and disposal through participatory decision making in two Oworonshoki Community Development Association (CDA) areas. Drone assisted mapping highlighted building footage. Structured interviews and focused group discussion of land lord associations in the CDA areas provided collaborator platform for decision-making. Water stagnation in primary open drainage channels and natural retention ponds in framing wetlands is traceable to frequent of climate change induced tidal influences in recent decades. Rise in water table resulting in septic-tank leakage and water pollution is reported to be responsible for the increase in the water born infirmities documented in primary health centers. This is in addition to unhealthy dumping of solid wastes in the drainage channels. The effect of uncontrolled disposal system renders surface waters and underground water systems unsafe for human and recreational use; destroys biotic life; and poisons the fragile sand barrier-lagoon urban ecosystems. Cluster decentralized system was conceptualized to service 255 households. Stakeholders agreed on public-private partnership initiative for efficient wastewater service delivery.

Keywords: health, infrastructure, management, septage, well-being

Procedia PDF Downloads 143

Authors: D. Lopes, I. I. R. Baptista, R. F. Vieira, J. Vaz, H. Varela, O. M. Freitas, V. F. Domingues, R. Jorge, C. Delerue-Matos, S. A. Figueiredo

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Deodorization is nowadays a need in wastewater treatment plants. Nitrogen and sulphur compounds, volatile fatty acids, aldehydes and ketones are responsible for the unpleasant odours, being ammonia, hydrogen sulphide and mercaptans the most common pollutants. Although chemical treatments of the air extracted are efficient, these are more expensive than biological treatments, namely due the use of chemical reagents (commonly sulphuric acid, sodium hypochlorite and sodium hydroxide). Biofiltration offers the advantage of avoiding the use of reagents (only in some cases, nutrients are added in order to increase the treatment efficiency) and can be considered a sustainable process when the packing medium used is of natural origin. In this work the application of some natural materials locally available was studied both at laboratory and pilot scale, in a real wastewater treatment plant. The materials selected for this study were indigenous Portuguese forest materials derived from eucalyptus and pinewood, such as woodchips and bark, and coconut fiber was also used for comparison purposes. Their physico-chemical characterization was performed: density, moisture, pH, buffer and water retention capacity. Laboratory studies involved batch adsorption studies for ammonia and hydrogen sulphide removal and evaluation of microbiological activity. Four pilot-scale biofilters (1 cubic meter volume) were installed at a local wastewater treatment plant treating odours from the effluent receiving chamber. Each biofilter contained a different packing material consisting of mixtures of eucalyptus bark, pine woodchips and coconut fiber, with added buffering agents and nutrients. The odour treatment efficiency was monitored over time, as well as other operating parameters. The operation at pilot scale suggested that between the processes involved in biofiltration - adsorption, absorption and biodegradation - the first dominates at the beginning, while the biofilm is developing. When the biofilm is completely established, and the adsorption capacity of the material is reached, biodegradation becomes the most relevant odour removal mechanism. High odour and hydrogen sulphide removal efficiencies were achieved throughout the testing period (over 6 months), confirming the suitability of the materials selected, and mixtures thereof prepared, for biofiltration applications.

Keywords: ammonia hydrogen sulphide and removal, biofiltration, natural materials, odour control in wastewater treatment plants

Procedia PDF Downloads 277

Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

Procedia PDF Downloads 72

Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

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Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

Procedia PDF Downloads 246

Authors: Sh. Sousani, Z. Shadrokh, M. Hofbauerová, J. Kollár, M. Jergel, P. Nádaždy, M. Omastová, E. Majková

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Perovskite quantum dots (PQDs) have the potential to increase the performance of the perovskite solar cell (PSCs). The integration of PQDs into PSCs can extend the absorption range and enhance photon harvesting and device efficiency. In addition, PQDs can stabilize the device structure by passivating surface defects and traps in the perovskite layer and enhance its stability. The integration of PQDs into PSCs is strongly affected by the type of ligands on the surface of PQDs. The ligands affect the charge transport properties of PQDs, as well as the formation of well-defined interfaces and stability of PSCs. In this work, the CsPbBr₃ QDs were synthesized by the conventional hot-injection method using cesium oleate, PbBr₂ and two different ligands, namely oleic acid (OA) oleylamine (OAm) and didodecyldimethylammonium bromide (DDAB). The STEM confirmed regular shape and relatively monodisperse cubic structure with an average size of about 10-14 nm of the prepared CsPbBr₃ QDs. Further, the photoluminescent (PL) properties of the PQDs/perovskite bilayer with the ligand OA, OAm and DDAB were studied. For this purpose, ITO/PQDs as well as ITO/PQDs/MAPI perovskite structures were prepared by spin coating and the effect of the ligand and oxygen plasma treatment was analyzed. The plasma treatment of the PQDs layer could be beneficial for the deposition of the MAPI perovskite layer and the formation of a well-defined PQDs/MAPI interface. The absorption edge in UV-Vis absorption spectra for OA, OAm CsPbBr₃ QDs is placed around 513 nm (the band gap 2.38 eV); for DDAB CsPbBr₃ QDs, it is located at 490 nm (the band gap 2.33 eV). The photoluminescence (PL) spectra of CsPbBr₃ QDs show two peaks located around 514 nm (503 nm) and 718 nm (708 nm) for OA, OAm (DDAB). The peak around 500 nm corresponds to the PL of PQDs, and the peak close to 710 nm belongs to the surface states of PQDs for both types of ligands. These surface states are strongly affected by the O₃ plasma treatment. For PQDs with DDAB ligand, the O₃ exposure (5, 10, 15 s) results in the blue shift of the PQDs peak and a non-monotonous change of the amplitude of the surface states' peak. For OA, OAm ligand, the O₃ exposition did not cause any shift of the PQDs peak, and the intensity of the PL peak related to the surface states is lower by one order of magnitude in comparison with DDAB, being affected by O₃ plasma treatment. The PL results indicate the possibility of tuning the position of the PL maximum by the ligand of the PQDs. Similar behavior of the PQDs layer was observed for the ITO/QDs/MAPI samples, where an additional strong PL peak at 770 nm coming from the perovskite layer was observed; for the sample with PQDs with DDAB ligands, a small blue shift of the perovskite PL maximum was observed independently of the plasma treatment. These results suggest the possibility of affecting the PL maximum position and the surface states of the PQDs by the combination of a suitable ligand and the O₃ plasma treatment.

Keywords: perovskite quantum dots, photoluminescence, O₃ plasma., Perovskite Solar Cells

Procedia PDF Downloads 35

Authors: Sh. Sousani, Z. Shadrokh, M. Hofbauerová, J. Kollár, M. Jergel, P. Nádaždy, M. Omastová, E. Majková

Abstract:

Perovskite quantum dots (PQDs) have the potential to increase the performance of the perovskite solar cells (PSCs). The integration of PQDs into PSCs can extend the absorption range and enhance photon harvesting and device efficiency. In addition, PQDs can stabilize the device structure by passivating surface defects and traps in the perovskite layer and enhance its stability. The integration of PQDs into PSCs is strongly affected by the type of ligands on the surface of PQDs. The ligands affect the charge transport properties of PQDs, as well as the formation of well-defined interfaces and stability of PSCs. In this work, the CsPbBr₃ QDs were synthesized by the conventional hot-injection method using cesium oleate, PbBr₂, and two different ligands, namely oleic acid (OA)@oleylamine (OAm) and didodecyldimethylammonium bromide (DDAB). The STEM confirmed regular shape and relatively monodisperse cubic structure with an average size of about 10-14 nm of the prepared CsPbBr₃ QDs. Further, the photoluminescent (PL) properties of the PQDs/perovskite bilayer with the ligand OA@OAm and DDAB were studied. For this purpose, ITO/PQDs, as well as ITO/PQDs/MAPI perovskite structures, were prepared by spin coating, and the effect of the ligand and oxygen plasma treatment was analysed. The plasma treatment of the PQDs layer could be beneficial for the deposition of the MAPI perovskite layer and the formation of a well-defined PQDs/MAPI interface. The absorption edge in UV-Vis absorption spectra for OA@OAm CsPbBr₃ QDs is placed around 513 nm (the band gap 2.38 eV); for DDAB CsPbBr₃ QDs, it is located at 490 nm (the band gap 2.33 eV). The photoluminescence (PL) spectra of CsPbBr₃ QDs show two peaks located around 514 nm (503 nm) and 718 nm (708 nm) for OA@OAm (DDAB). The peak around 500 nm corresponds to the PL of PQDs, and the peak close to 710 nm belongs to the surface states of PQDs for both types of ligands. These surface states are strongly affected by the O₃ plasma treatment. For PQDs with DDAB ligand, the O₃ exposure (5, 10, 15 s) results in the blue shift of the PQDs peak and a non-monotonous change of the amplitude of the surface states' peak. For OA@OAm ligand, the O₃ exposition did not cause any shift of the PQDs peak, and the intensity of the PL peak related to the surface states is lower by one order of magnitude in comparison with DDAB, being affected by O₃ plasma treatment. The PL results indicate the possibility of tuning the position of the PL maximum by the ligand of the PQDs. Similar behaviour of the PQDs layer was observed for the ITO/QDs/MAPI samples, where an additional strong PL peak at 770 nm coming from the perovskite layer was observed; for the sample with PQDs with DDAB ligands, a small blue shift of the perovskite PL maximum was observed independently of the plasma treatment. These results suggest the possibility of affecting the PL maximum position and the surface states of the PQDs by the combination of a suitable ligand and the O₃ plasma treatment.

Keywords: perovskite quantum dots, photoluminescence, O₃ plasma., perovskite solar cells

Procedia PDF Downloads 39

Authors: Burçak Boztemur, Yue Xu, Laima Luo, M. Lütfi Öveçoğlu, Duygu Ağaoğulları

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Tungsten (W) is used chiefly as plasma-facing material. However, it has some problems, such as brittleness after plasma exposure. High-entropy alloys (RHEAs) are a new opportunity for this deficiency. So, the neutron shielding behavior of WNbMoVTa and WNbMoVTaCr₀.₅Al compositions were examined against He⁺ irradiation in this study. The mechanical and irradiation properties of the WNbMoVTa base composition were investigated by adding the Al and Cr elements. The mechanical alloying (MA) for 6 hours was applied to obtain RHEA powders. According to the X-ray diffraction (XRD) method, the body-centered cubic (BCC) phase and NbTa phase with a small amount of WC impurity that comes from vials and balls were determined after 6 h MA. Also, RHEA powders were consolidated with the spark plasma sintering (SPS) method (1500 ºC, 30 MPa, and 10 min). After the SPS method, (Nb,Ta)C and W₂C₀.₈₅ phases were obtained with the decomposition of WC and stearic acid that is added during MA based on XRD results. Also, the BCC phase was obtained for both samples. While the Al₂O₃ phase with a small intensity was seen for the WNbMoVTaCr₀.₅Al sample, the Ta₂VO₆ phase was determined for the base sample. These phases were observed as three different regions according to scanning electron microscopy (SEM). All elements were distributed homogeneously on the white region by measuring an electron probe micro-analyzer (EPMA) coupled with a wavelength dispersive spectroscope (WDS). Also, the grey region of the WNbMoVTa sample was rich in Ta, V, and O elements. However, the amount of Al and O elements was higher for the grey region of the WNbMoVTaCr₀.₅Al sample. The high amount of Nb, Ta, and C elements were determined for both samples. Archimedes’ densities that were measured with alcohol media were closer to the theoretical densities of RHEAs. These values were important for the microhardness and irradiation resistance of compositions. While the Vickers microhardness value of the WNbMoVTa sample was measured as ~11 GPa, this value increased to nearly 13 GPa with the WNbMoVTaCr₀.₅Al sample. These values were compatible with the wear behavior. The wear volume loss was decreased to 0.16×10⁻⁴ from 1.25×10⁻⁴ mm³ by the addition of Al and Cr elements to the WNbMoVTa. The He⁺ irradiation was conducted on the samples to observe surface damage. After irradiation, the XRD patterns were shifted to the left because of defects and dislocations. He⁺ ions were infused under the surface, so they created the lattice expansion. The peak shifting of the WNbMoVTaCr₀.₅Al sample was less than the WNbMoVTa base sample, thanks to less impact. A small amount of fuzz was observed for the base sample. This structure was removed and transformed into a wavy structure with the addition of Cr and Al elements. Also, the deformation hardening was actualized after irradiation. A lower amount of hardening was obtained with the WNbMoVTaCr₀.₅Al sample based on the changing microhardness values. The surface deformation was decreased in the WNbMoVTaCr₀.₅Al sample.

Keywords: refractory high entropy alloy, microhardness, wear resistance, He⁺ irradiation

Procedia PDF Downloads 43

Authors: Maksudur Rahman Khan, Kar Min Chan, Huei Ruey Ong, Chin Kui Cheng, Wasikur Rahman

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Microbial fuel cells (MFCs) represent a promising technology for simultaneous bioelectricity generation and wastewater treatment. Catalysts are significant portions of the cost of microbial fuel cell cathodes. Many materials have been tested as aqueous cathodes, but air-cathodes are needed to avoid energy demands for water aeration. The sluggish oxygen reduction reaction (ORR) rate at air cathode necessitates efficient electrocatalyst such as carbon supported platinum catalyst (Pt/C) which is very costly. Manganese oxide (MnO2) was a representative metal oxide which has been studied as a promising alternative electrocatalyst for ORR and has been tested in air-cathode MFCs. However, the single MnO2 has poor electric conductivity and low stability. In the present work, the MnO2 catalyst has been modified by doping Pt nanoparticle. The goal of the work was to improve the performance of the MFC with minimum Pt loading. MnO2 and Pt nanoparticles were prepared by hydrothermal and sol-gel methods, respectively. Wet impregnation method was used to synthesize Pt/MnO2 catalyst. The catalysts were further used as cathode catalysts in air-cathode cubic MFCs, in which anaerobic sludge was inoculated as biocatalysts and palm oil mill effluent (POME) was used as the substrate in the anode chamber. The as-prepared Pt/MnO2 was characterized comprehensively through field emission scanning electron microscope (FESEM), X-Ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and cyclic voltammetry (CV) where its surface morphology, crystallinity, oxidation state and electrochemical activity were examined, respectively. XPS revealed Mn (IV) oxidation state and Pt (0) nanoparticle metal, indicating the presence of MnO2 and Pt. Morphology of Pt/MnO2 observed from FESEM shows that the doping of Pt did not cause change in needle-like shape of MnO2 which provides large contacting surface area. The electrochemical active area of the Pt/MnO2 catalysts has been increased from 276 to 617 m2/g with the increase in Pt loading from 0.2 to 0.8 wt%. The CV results in O2 saturated neutral Na2SO4 solution showed that MnO2 and Pt/MnO2 catalysts could catalyze ORR with different catalytic activities. MFC with Pt/MnO2 (0.4 wt% Pt) as air cathode catalyst generates a maximum power density of 165 mW/m3, which is higher than that of MFC with MnO2 catalyst (95 mW/m3). The open circuit voltage (OCV) of the MFC operated with MnO2 cathode gradually decreased during 14 days of operation, whereas the MFC with Pt/MnO2 cathode remained almost constant throughout the operation suggesting the higher stability of the Pt/MnO2 catalyst. Therefore, Pt/MnO2 with 0.4 wt% Pt successfully demonstrated as an efficient and low cost electrocatalyst for ORR in air cathode MFC with higher electrochemical activity, stability and hence enhanced performance.

Keywords: microbial fuel cell, oxygen reduction reaction, Pt/MnO2, palm oil mill effluent, polarization curve

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Authors: Magdalena Idzikowska, Katarzyna Pająk, Kamil Kowalczyk

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Seafloor topography is a fundamental issue in geological, geophysical, and oceanographic studies. Single-beam or multibeam sonars attached to the hulls of ships are used to emit a hydroacoustic signal from transducers and reproduce the topography of the seabed. This solution provides relevant accuracy and spatial resolution. Bathymetric data from ships surveys provides National Centers for Environmental Information – National Oceanic and Atmospheric Administration. Unfortunately, most of the seabed is still unidentified, as there are still many gaps to be explored between ship survey tracks. Moreover, such measurements are very expensive and time-consuming. The solution is raster bathymetric models shared by The General Bathymetric Chart of the Oceans. The offered products are a compilation of different sets of data - raw or processed. Indirect data for the development of bathymetric models are also measurements of gravity anomalies. Some forms of seafloor relief (e.g. seamounts) increase the force of the Earth's pull, leading to changes in the sea surface. Based on satellite altimetry data, Sea Surface Height and marine gravity anomalies can be estimated, and based on the anomalies, it’s possible to infer the structure of the seabed. The main goal of the work is to create regional bathymetric models and models of the sea surface in the area of the east coast of North America – a region of seamounts and undulating seafloor. The research includes an analysis of the methods and techniques used, an evaluation of the interpolation algorithms used, model thickening, and the creation of grid models. Obtained data are raster bathymetric models in NetCDF format, survey data from multibeam soundings in MB-System format, and satellite altimetry data from Copernicus Marine Environment Monitoring Service. The methodology includes data extraction, processing, mapping, and spatial analysis. Visualization of the obtained results was carried out with Geographic Information System tools. The result is an extension of the state of the knowledge of the quality and usefulness of the data used for seabed and sea surface modeling and knowledge of the accuracy of the generated models. Sea level is averaged over time and space (excluding waves, tides, etc.). Its changes, along with knowledge of the topography of the ocean floor - inform us indirectly about the volume of the entire water ocean. The true shape of the ocean surface is further varied by such phenomena as tides, differences in atmospheric pressure, wind systems, thermal expansion of water, or phases of ocean circulation. Depending on the location of the point, the higher the depth, the lower the trend of sea level change. Studies show that combining data sets, from different sources, with different accuracies can affect the quality of sea surface and seafloor topography models.

Keywords: seafloor, sea surface height, bathymetry, satellite altimetry

Procedia PDF Downloads 53

Authors: Bastian Waduge Naveen Harindu Hemasiri, Jae-Kwan Kim, Ji-Myon Lee

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Indium tin oxide (ITO) remains the industrial standard transparent conducting oxides with better performances. Recently, graphene becomes as a strong material with unique properties to replace the ITO. However, graphene/ITO hybrid composite material is a newly born field in the electronic world. In this study, the graphene/ITO composite bi-film was synthesized by a two steps process. 10 wt.% tin-doped, ITO thin films were produced by an environmentally friendly aqueous sol-gel spin coating technique with economical salts of In(NO3)3.H2O and SnCl4 without using organic additives. The wettability and surface free energy (97.6986 mJ/m2) enhanced oxygen plasma treated glass substrates were used to form voids free continuous ITO film. The spin-coated samples were annealed at 600 0C for 1 hour under low vacuum conditions to obtained crystallized, ITO film. The crystal structure and crystalline phases of ITO thin films were analyzed by X-ray diffraction (XRD) technique. The Scherrer equation was used to determine the crystallite size. Detailed information about chemical composition and elemental composition of the ITO film were determined by X-ray photoelectron spectroscopy (XPS) and energy dispersive X-ray spectroscopy (EDX) coupled with FE-SEM respectively. Graphene synthesis was done under chemical vapor deposition (CVD) method by using Cu foil at 1000 0C for 1 min. The quality of the synthesized graphene was characterized by Raman spectroscopy (532nm excitation laser beam) and data was collected at room temperature and normal atmosphere. The surface and cross-sectional observation were done by using FE-SEM. The optical transmission and sheet resistance were measured by UV-Vis spectroscopy and four point probe head at room temperature respectively. Electrical properties were also measured by using V-I characteristics. XRD patterns reveal that the films contain the In2O3 phase only and exhibit the polycrystalline nature of the cubic structure with the main peak of (222) plane. The peak positions of In3d5/2 (444.28 eV) and Sn3d5/2 (486.7 eV) in XPS results indicated that indium and tin are in the oxide form only. The UV-visible transmittance shows 91.35 % at 550 nm with 5.88 x 10-3 Ωcm specific resistance. The G and 2D band in Raman spectroscopy of graphene appear at 1582.52 cm-1 and 2690.54 cm-1 respectively when the synthesized CVD graphene on SiO2/Si. The determined intensity ratios of 2D to G (I2D/IG) and D to G (ID/IG) were 1.531 and 0.108 respectively. However, the above-mentioned G and 2D peaks appear at 1573.57 cm-1 and 2668.14 cm-1 respectively when the CVD graphene on the ITO coated glass, the positions of G and 2D peaks were red shifted by 8.948 cm-1 and 22.396 cm-1 respectively. This graphene/ITO bi-film shows modified electrical properties when compares with sol-gel derived ITO film. The reduction of sheet resistance in the bi-film was 12.03 % from the ITO film. Further, the fabricated graphene/ITO bi-film shows 88.66 % transmittance at 550 nm wavelength.

Keywords: chemical vapor deposition, graphene, ITO, Raman Spectroscopy, sol-gel

Procedia PDF Downloads 232

Authors: Brayden Mi

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Reverse time migration has been widely used in the Petroleum exploration industry to reveal subsurface images and to detect rock and fluid properties since the early 1980s. The seismic technology involves the construction of a velocity model through interpretive model construction, seismic tomography, or full waveform inversion, and the application of the reverse-time propagation of acquired seismic data and the original wavelet used in the acquisition. The methodology has matured from 2D, simple media to present-day to handle full 3D imaging challenges in extremely complex geological conditions. Conventional Ultrasound computed tomography (USCT) utilize travel-time-inversion to reconstruct the velocity structure of an organ. With the velocity structure, USCT data can be migrated with the “bend-ray” method, also known as migration. Its seismic application counterpart is called Kirchhoff depth migration, in which the source of reflective energy is traced by ray-tracing and summed to produce a subsurface image. It is well known that ray-tracing-based migration has severe limitations in strongly heterogeneous media and irregular acquisition geometries. Reverse time migration (RTM), on the other hand, fully accounts for the wave phenomena, including multiple arrives and turning rays due to complex velocity structure. It has the capability to fully reconstruct the image detectable in its acquisition aperture. The RTM algorithms typically require a rather accurate velocity model and demand high computing powers, and may not be applicable to real-time imaging as normally required in day-to-day medical operations. However, with the improvement of computing technology, such a computational bottleneck may not present a challenge in the near future. The present-day (RTM) algorithms are typically implemented from a flat datum for the seismic industry. It can be modified to accommodate any acquisition geometry and aperture, as long as sufficient illumination is provided. Such flexibility of RTM can be conveniently implemented for the application in USCT imaging if the spatial coordinates of the transmitters and receivers are known and enough data is collected to provide full illumination. This paper proposes an implementation of a full 3D RTM algorithm for USCT imaging to produce an accurate 3D acoustic image based on the Phase-shift-plus-interpolation (PSPI) method for wavefield extrapolation. In this method, each acquired data set (shot) is propagated back in time, and a known ultrasound wavelet is propagated forward in time, with PSPI wavefield extrapolation and a piece-wise constant velocity model of the organ (breast). The imaging condition is then applied to produce a partial image. Although each image is subject to the limitation of its own illumination aperture, the stack of multiple partial images will produce a full image of the organ, with a much-reduced noise level if compared with individual partial images.

Keywords: illumination, reverse time migration (RTM), ultrasound computed tomography (USCT), wavefield extrapolation

Procedia PDF Downloads 48

Authors: C. Fornacelli, P. Colomban, E. Mugnaioli, I. Memmi Turbanti

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When semiconductor particles are reduced in scale to nanometer dimension, their optical and electro-optical properties strongly differ from those of bulk crystals of the same composition. Since sampling is often not allowed concerning cultural heritage artefacts, the potentialities of two non-invasive techniques, such as Raman and Fiber Optic Reflectance Spectroscopy (FORS), have been investigated and the results of the analysis on some original glasses of different colours (from yellow to orange and deep red) and periods (from the second decade of the 20th century to present days) are reported in the present study. In order to evaluate the potentialities of the application of non-invasive techniques to the investigation of the structure and distribution of nanoparticles dispersed in a glass matrix, Scanning Electron Microscopy (SEM) and energy-disperse spectroscopy (EDS) mapping, together with Transmission Electron Microscopy (TEM) and Electron Diffraction Tomography (EDT) have also been used. Raman spectroscopy allows a fast and non-destructive measure of the quantum dots composition and size, thanks to the evaluation of the frequencies and the broadening/asymmetry of the LO phonons bands, respectively, though the important role of the compressive strain arising from the glass matrix and the possible diffusion of zinc from the matrix to the nanocrystals should be taken into account when considering the optical-phonons frequency values. The incorporation of Zn has been assumed by an upward shifting of the LO band related to the most abundant anion (S or Se), while the role of the surface phonons as well as the confinement-induced scattering by phonons with a non-zero wavevectors on the Raman peaks broadening has been verified. The optical band gap varies from 2.42 eV (pure CdS) to 1.70 eV (CdSe). For the compositional range between 0.5≤x≤0.2, the presence of two absorption edges has been related to the contribution of both pure CdS and the CdSxSe1-x solid solution; this particular feature is probably due to the presence of unaltered cubic zinc blende structures of CdS that is not taking part to the formation of the solid solution occurring only between hexagonal CdS and CdSe. Moreover, the band edge tailing originating from the disorder due to the formation of weak bonds and characterized by the Urbach edge energy has been studied and, together with the FWHM of the Raman signal, has been assumed as a good parameter to evaluate the degree of topological disorder. SEM-EDS mapping showed a peculiar distribution of the major constituents of the glass matrix (fluxes and stabilizers), especially concerning those samples where a layered structure has been assumed thanks to the spectroscopic study. Finally, TEM-EDS and EDT were used to get high-resolution information about nanocrystals (NCs) and heterogeneous glass layers. The presence of ZnO NCs (< 4 nm) dispersed in the matrix has been verified for most of the samples, while, for those samples where a disorder due to a more complex distribution of the size and/or composition of the NCs has been assumed, the TEM clearly verified most of the assumption made by the spectroscopic techniques.

Keywords: CdSxSe1-x, EDT, glass, spectroscopy, TEM-EDS

Procedia PDF Downloads 281

Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

Procedia PDF Downloads 96

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

Procedia PDF Downloads 217

Authors: Sanchita Baitalik, Nijhuma Kayal, Omprakash Chakrabarti

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Recently SiC ceramics have been a focus of interest in the field of porous materials due to their unique combination of properties and hence they are considered as an ideal candidate for catalyst supports, thermal insulators, high-temperature structural materials, hot gas particulate separation systems etc. in different industrial processes. Several processing methods are followed for fabrication of porous SiC at low temperatures but all these methods are associated with several disadvantages. Therefore processing of porous SiC ceramics at low temperatures is still challenging. Concerning that of incorporation of secondary bond phase additives by an infiltration technique should result in a homogenous distribution of bond phase in the final ceramics. Present work is aimed to synthesis cordierite (2MgO.2Al2O3.5SiO2) bonded porous SiC ceramics following incorporation of sol-gel bond phase precursor into powder compacts of SiC and heat treating the infiltrated body at 1400 °C. In this paper the primary aim was to study the effect of infiltration of a precursor sol of cordierite into a porous SiC powder compact prepared with pore former of different particle sizes on the porosity, pore size, microstructure and the mechanical properties of the porous SiC ceramics. Cordierite sol was prepared by mixing a solution of magnesium nitrate hexahydrate and aluminium nitrate nonahydrate in 2:4 molar ratio in ethanol another solution containing tetra-ethyl orthosilicate and ethanol in 1:3 molar ratio followed by stirring for several hours. Powders of SiC (α-SiC; d50 =22.5 μm) and 10 wt. % polymer microbead of two sizes 8 and 50µm as the pore former were mixed in a suitable liquid medium, dried and pressed in the form of bars (50×20×16 mm3) at 23 MPa pressure. The well-dried bars were heat treated at 1100° C for 4 h with a hold at 750 °C for 2 h to remove the pore former. Bars were evacuated for 2 hr upto 0.3 mm Hg pressure into a vacuum chamber and infiltrated with cordierite precursor sol. The infiltrated samples were dried and the infiltration process was repeated until the weight gain became constant. Finally the infiltrated samples were sintered at 1400 °C to prepare cordierite bonded porous SiC ceramics. Porous ceramics prepared with 8 and 50 µm sized microbead exhibited lower oxidation degrees of respectively 7.8 and 4.8 % than the sample (23 %) prepared with no microbead. Depending on the size of pore former, the porosity of the final ceramic varied in the range of 36 to 40 vol. % with a variation of flexural strength from 33.7 to 24.6 MPa. XRD analysis showed major crystalline phases of the ceramics as SiC, SiO2 and cordierite. Two forms of cordierite, α-(hexagonal) and µ-(cubic), were detected by the XRD analysis. The SiC particles were observed to be bonded both by cristobalite with fish scale morphology and cordierite with rod shape morphology and thereby formed a porous network. The material and mechanical properties of cordierite bonded porous SiC ceramics are good in agreement to carry out further studies like thermal shock, corrosion resistance etc.

Keywords: cordierite, infiltration technique, porous ceramics, sol-gel

Procedia PDF Downloads 240

Authors: Andrew N. Saylor, James R. Peters

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Scoliosis is a complex 3D deformity of the thoracic and lumbar spines, clinically diagnosed by measurement of a Cobb angle of 10 degrees or more on a coronal X-ray. The Cobb angle is the angle made by the lines drawn along the proximal and distal endplates of the respective proximal and distal vertebrae comprising the curve. Traditionally, Cobb angles are measured manually using either a marker, straight edge, and protractor or image measurement software. The task of measuring the Cobb angle can also be represented by a function taking the spine geometry rendered using X-ray imaging as input and returning the approximate angle. Although the form of such a function may be unknown, it can be approximated using artificial neural networks (ANNs). The performance of ANNs is affected by many factors, including the choice of activation function and network architecture; however, the effects of these parameters on the accuracy of scoliotic deformity measurements are poorly understood. Therefore, the objective of this study was to systematically investigate the effect of ANN architecture and activation function on Cobb angle measurement from the coronal X-rays of scoliotic subjects. The data set for this study consisted of 609 coronal chest X-rays of scoliotic subjects divided into 481 training images and 128 test images. These data, which included labeled Cobb angle measurements, were obtained from the SpineWeb online database. In order to normalize the input data, each image was resized using bi-linear interpolation to a size of 500 × 187 pixels, and the pixel intensities were scaled to be between 0 and 1. A fully connected (dense) ANN with a fixed cost function (mean squared error), batch size (10), and learning rate (0.01) was developed using Python Version 3.7.3 and TensorFlow 1.13.1. The activation functions (sigmoid, hyperbolic tangent [tanh], or rectified linear units [ReLU]), number of hidden layers (1, 3, 5, or 10), and number of neurons per layer (10, 100, or 1000) were varied systematically to generate a total of 36 network conditions. Stochastic gradient descent with early stopping was used to train each network. Three trials were run per condition, and the final mean squared errors and mean absolute errors were averaged to quantify the network response for each condition. The network that performed the best used ReLU neurons had three hidden layers, and 100 neurons per layer. The average mean squared error of this network was 222.28 ± 30 degrees2, and the average mean absolute error was 11.96 ± 0.64 degrees. It is also notable that while most of the networks performed similarly, the networks using ReLU neurons, 10 hidden layers, and 1000 neurons per layer, and those using Tanh neurons, one hidden layer, and 10 neurons per layer performed markedly worse with average mean squared errors greater than 400 degrees2 and average mean absolute errors greater than 16 degrees. From the results of this study, it can be seen that the choice of ANN architecture and activation function has a clear impact on Cobb angle inference from coronal X-rays of scoliotic subjects.

Keywords: scoliosis, artificial neural networks, cobb angle, medical imaging

Procedia PDF Downloads 96

Authors: S.V. Kleyn, S.Yu. Zagorodnov, А.А. Kokoulina

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Technogenic emissions of the mining and processing complex are characterized by a high content of chemical components and solid dust particles. However, each industrial enterprise and the surrounding area have features that require refinement and parameterization. Numerous studies have shown the negative impact of fine dust PM10 and PM2.5 on the health, as well as the possibility of toxic components absorption, including heavy metals by dust particles. The target of the study was the quantitative assessment of the fractional and particle size composition of ambient air dust in the area of impact by primary magnesium production complex. Also, we tried to describe the morphology features of dust particles. Study methods. To identify the dust emission sources, the analysis of the production process has been carried out. The particulate composition of the emissions was measured using laser particle analyzer Microtrac S3500 (covered range of particle size is 20 nm to 2000 km). Particle morphology and the component composition were established by electron microscopy by scanning microscope of high resolution (magnification rate - 5 to 300 000 times) with X-ray fluorescence device S3400N ‘HITACHI’. The chemical composition was identified by X-ray analysis of the samples using an X-ray diffractometer XRD-700 ‘Shimadzu’. Determination of the dust pollution level was carried out using model calculations of emissions in the atmosphere dispersion. The calculations were verified by instrumental studies. Results of the study. The results demonstrated that the dust emissions of different technical processes are heterogeneous and fractional structure is complicated. The percentage of particle sizes up to 2.5 micrometres inclusive was ranged from 0.00 to 56.70%; particle sizes less than 10 microns inclusive – 0.00 - 85.60%; particle sizes greater than 10 microns - 14.40% -100.00%. During microscopy, the presence of nanoscale size particles has been detected. Studied dust particles are round, irregular, cubic and integral shapes. The composition of the dust includes magnesium, sodium, potassium, calcium, iron, chlorine. On the base of obtained results, it was performed the model calculations of dust emissions dispersion and establishment of the areas of fine dust РМ 10 and РМ 2.5 distribution. It was found that the dust emissions of fine powder fractions PM10 and PM2.5 are dispersed over large distances and beyond the border of the industrial site of the enterprise. The population living near the enterprise is exposed to the risk of diseases associated with dust exposure. Data are transferred to the economic entity to make decisions on the measures to minimize the risks. Exposure and risks indicators on the health are used to provide named patient health and preventive care to the citizens living in the area of negative impact of the facility.

Keywords: dust emissions, еxposure assessment, PM 10, PM 2.5

Procedia PDF Downloads 236

Authors: Olga Yu Kurapova, Alexander V. Shorokhov, Vladimir G. Konakov

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Nowadays, due to their exceptional anion conductivity at high temperatures cubic zirconia solid solutions, stabilized by rare-earth and alkaline-earth metal oxides, are widely used as a solid electrolyte (SE) materials in different electrochemical devices such as gas sensors, oxygen pumps, solid oxide fuel cells (SOFC), etc. Nowadays the intensive studies are carried out in a field of novel fully stabilized zirconia based SE development. The use of precursor powders for SE manufacturing allows predetermining the microstructure, electrical and sensor characteristics of zirconia based ceramics used as SE. Thus the goal of the present work was the investigation of the effect of precursor powder size on the electrical and sensor characteristics of fully stabilized zirconia-based solid electrolytes with compositions of 0,08Y2O3∙0,92ZrO2 (YSZ), 0,06Ce2O3∙ 0,06Y2O3∙0,88ZrO2 and 0,09Ce2O3∙0,06Y2O3-0,85ZrO2. The synthesis of precursors powders with different mean particle size was performed by sol-gel synthesis in the form of reversed co-precipitation from aqueous solutions. The cakes were washed until the neutral pH and pan-dried at 110 °С. Also, YSZ ceramics was obtained by conventional solid state synthesis including milling into a planetary mill. Then the powder was cold pressed into the pellets with a diameter of 7.2 and ~4 mm thickness at P ~16 kg/cm2 and then hydrostatically pressed. The pellets were annealed at 1600 °С for 2 hours. The phase composition of as-synthesized SE was investigated by X-Ray photoelectron spectroscopy ESCA (spectrometer ESCA-5400, PHI) X-ray diffraction analysis - XRD (Shimadzu XRD-6000). Following galvanic cell О2 (РО2(1)), Pt | SE | Pt, (РО2(2) = 0.21 atm) was used for SE sensor properties investigation. The value of РО2(1) was set by mixing of O2 and N2 in the defined proportions with the accuracy of  5%. The temperature was measured by Pt/Pt-10% Rh thermocouple, The cell electromotive force (EMF) measurement was carried out with ± 0.1 mV accuracy. During the operation at the constant temperature, reproducibility was better than 5 mV. Asymmetric potential measured for all SE appeared to be negligible. It was shown that the resistivity of YSZ ceramics decreases in about two times upon the mean agglomerates decrease from 200-250 to 40 nm. It is likely due to the both surface and bulk resistivity decrease in grains. So the overall decrease of grain size in ceramic SE results in the significant decrease of the total ceramics resistivity allowing sensor operation at lower temperatures. For the SE manufactured the estimation of oxygen ion transfer number tion was carried out in the range 600-800 °С. YSZ ceramics manufactured from powders with the mean particle size 40-140 nm, shows the highest values i.e. 0.97-0.98. SE manufactured from precursors with the mean particle size 40-140 nm shows higher sensor characteristic i.e. temperature and oxygen concentration EMF dependencies, EMF (ENernst - Ereal), tion, response time, then ceramics, manufactured by conventional solid state synthesis.

Keywords: oxygen sensors, precursor powders, sol-gel synthesis, stabilized zirconia ceramics

Procedia PDF Downloads 246

Authors: Dechao Meng, Yongqi Dong, Qiyuan Feng, Zhangzhang Cui, Xiang Hu, Haoliang Huang, Genhao Liang, Huanhua Wang, Hua Zhou, Hawoong Hong, Jinghua Guo, Qingyou Lu, Xiaofang Zhai, Yalin Lu

Abstract:

Great efforts have been taken to reveal the intrinsic origins of emerging ferromagnetism (FM) in strained LaCoO₃ (LCO) films. However, some macro magnetic performances of LCO are still not well understood and even controversial, such as magnetic anisotropy. Determining and understanding magnetic anisotropy might help to find the true causes of FM in turn. Perpendicular magnetic anisotropy (PMA) was the first time to be directly observed in high-quality LCO films with different thickness. The in-plane (IP) and out of plane (OOP) remnant magnetic moment ratio of 30 unit cell (u.c.) films is as large as 20. The easy axis lays in the OOP direction with an IP/OOP coercive field ratio of 10. What's more, the PMA could be simply tuned by changing the thickness. With the thickness increases, the IP/OOP magnetic moment ratio remarkably decrease with magnetic easy axis changing from OOP to IP. Such a huge and tunable PMA performance exhibit strong potentials in fundamental researches or applications. What causes PMA is the first concern. More OOP orbitals occupation may be one of the micro reasons of PMA. A cluster-like magnetic domain pattern was found in 30 u.c. with no obvious color contrasts, similar to that of LaAlO₃/SrTiO₃ films. And the nanosize domains could not be totally switched even at a large OOP magnetic field of 23 T. It indicates strong IP characters or none OOP magnetism of some clusters. The IP magnetic domains might influence the magnetic performance and help to form PMA. Meanwhile some possible nonmagnetic clusters might be the reason why the measured moments of LCO films are smaller than the calculated values 2 μB/Co, one of the biggest confusions in LCO films.What tunes PMA seems much more interesting. Totally different magnetic domain patterns were found in 180 u.c. films with cluster magnetic domains surrounded by < 110 > cross-hatch lines. These lines were regarded as structure domain walls (DWs) determined by 3D reciprocal space mapping (RSM). Two groups of in-plane features with fourfold symmetry were observed near the film diffraction peaks in (002) 3D-RSM. One is along < 110 > directions with a larger intensity, which is well match the lines on the surfaces. The other is much weaker and along < 100 > directions, which is from the normal lattice titling of films deposited on cubic substrates. The < 110 > domain features obtained from (103) and (113) 3D-RSMs exhibit similar evolution of the DWs percentages and magnetic behavior. Structure domains and domain walls are believed to tune PMA performances by transform more IP magnetic moments to OOP. Last but not the least, thick films with lots of structure domains exhibit different electrical transport behaviors. A metal-to-insulator transition (MIT) and an angular dependent negative magnetic resistivity were observed near 150 K, higher than FM transition temperature but similar to that of spin-orbital coupling related 1/4 order diffraction peaks.

Keywords: structure domain, magnetic anisotropy, magnetic domain, domain wall, 3D-RSM, strain

Procedia PDF Downloads 125

Authors: P. M. Natarajan, Shambhu Kallolikar, S. Ganesh

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By size and volume of water, Ganges River basin is the biggest among the fourteen major river basins in India. By Hindu’s faith, it is the main ‘holy river’ in this nation. But, of late, the pollution load, both domestic and industrial sources are deteriorating the surface and groundwater as well as land resources and hence the environment of the Ganges River basin is under threat. Seeing this scenario, the Indian government began to reclaim this river by two Ganges Action Plans I and II since 1986 by spending Rs. 2,747.52 crores ($457.92 million). But the result was no improvement in the water quality of the river and groundwater and environment even after almost three decades of reclamation, and hence now the New Indian Government is taking extra care to rejuvenate this river and allotted Rs. 2,037 cores ($339.50 million) in 2014 and Rs. 20,000 crores ($3,333.33 million) in 2015. The reasons for the poor water quality and stinking environment even after three decades of reclamation of the river are either no treatment/partial treatment of the sewage. Hence, now the authors are suggesting a tertiary level treatment standard of sewages of all sources and origins of the Ganges River basin and recycling the entire treated water for nondomestic uses. At 20million litres per day (MLD) capacity of each sewage treatment plant (STP), this basin needs about 2020 plants to treat the entire sewage load. Cost of the STPs is Rs. 3,43,400 million ($5,723.33 million) and the annual maintenance cost is Rs. 15,352 million ($255.87 million). The advantages of the proposed exercise are: we can produce a volume of 1,769.52 million m³ of biogas. Since biogas is energy, can be used as a fuel, for any heating purpose, such as cooking. It can also be used in a gas engine to convert the energy in the gas into electricity and heat. It is possible to generate about 3,539.04 million kilowatt electricity per annum from the biogas generated in the process of wastewater treatment in Ganges basin. The income generation from electricity works out to Rs 10,617.12million ($176.95million). This power can be used to bridge the supply and demand gap of energy in the power hungry villages where 300million people are without electricity in India even today, and to run these STPs as well. The 664.18 million tonnes of sludge generated by the treatment plants per annum can be used in agriculture as manure with suitable amendments. By arresting the pollution load the 187.42 cubic kilometer (km³) of groundwater potential of the Ganges River basin could be protected from deterioration. Since we can recycle the sewage for non-domestic purposes, about 14.75km³ of fresh water per annum can be conserved for future use. The total value of the water saving per annum is Rs.22,11,916million ($36,865.27million) and each citizen of Ganges River basin can save Rs. 4,423.83/ ($73.73) per annum and Rs. 12.12 ($0.202) per day by recycling the treated water for nondomestic uses. Further the environment of this basin could be kept clean by arresting the foul smell as well as the 3% of greenhouse gages emission from the stinking waterways and land. These are the ways to reclaim the waterways of Ganges River basin from deterioration.

Keywords: Holy Ganges River, lifeline of India, wastewater treatment and management, making Ganges permanently holy

Procedia PDF Downloads 257

Authors: A. Chiker, A. Benamor, A. Haddad, Y. Hadji, M. Hadji

Abstract:

Metal matrix composites (MMCs) have been of big interest for a few decades. Their major drawback lies in their enhanced mechanical performance over unreinforced alloys. They found ground in many engineering fields, such as aeronautics, aerospace, automotive, and other structural applications. One of the most used alloys as a matrix is nickel alloys, which meet the need for high-temperature mechanical properties; some attempts have been made to develop nickel base composites reinforced by high melt point and high modulus particulates. Among the carbides used as reinforcing particulates, chromium carbide is interesting for wear applications; it is widely used as a tribological coating material in high-temperature applications requiring high wear resistance and hardness. Moreover, a set of properties make it suitable for use in MMCs, such as toughness, the good corrosion and oxidation resistance of its three polymorphs -the cubic (Cr23C6), the hexagonal (Cr7C3), and the orthorhombic (Cr3C2)-, and it’s coefficient of thermal expansion that is almost equal to that of metals. The in-situ synthesis of CrC-reinforced Ni matrix composites could be achieved by the powder metallurgy route. To ensure the in-situ reactions during the sintering process, the use of phase precursors is necessary. Recently, new precursor materials have been proposed; these materials are called MAX phases. The MAX phases are thermodynamically stable nano-laminated materials displaying unusual and sometimes unique properties. These novel phases possess Mn+1AXn chemistry, where n is 1, 2, or 3, M is an early transition metal element, A is an A-group element, and X is C or N. Herein, the pressureless sintering method is used to elaborate Ni/Cr2AlC composites. Four composites were elaborated from 5, 10, 15 and 20 wt% of Cr2AlC MAX phase precursor which fully reacted with Ni-matrix at 1100 °C sintering temperature for 4 h in argon atmosphere. XRD results showed that Cr2AlC MAX phase was totally decomposed forming chromium carbide Cr7C3, and the released Al and Cr atoms diffused in Ni matrix giving rise to γ-Ni(Al,Cr) solid solution and γ’-Ni3(Al,Cr) intermetallic. Scanning Electron Microscopy (SEM) of the elaborated samples showed the presence of nanosized Cr7C3 reinforcing particles embedded in the Ni metal matrix, which have a direct impact on the tribological properties of the composites and their hardness. All the composites exhibited higher hardness than pure Ni; whereas adding 15 wt% of Cr2AlC gives the highest hardness (1.85 GPa). Using a ball-on-disc tribometer, dry sliding tests for the elaborated composites against 100Cr6 steel ball were studied under different applied loads. The microstructures and worn surface characteristics were then analyzed using SEM and Raman spectroscopy. The results show that all the composites exhibited better wear resistance compared to pure Ni, which could be explained by the formation of a lubricious tribo-layer during sliding and the good bonding between the Ni matrix and the reinforcing phases.

Keywords: composites, microscopy, sintering, wear

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

Procedia PDF Downloads 45

Authors: Dhanuj M. Gandikota

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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

Procedia PDF Downloads 62

Authors: Ali Ateş, Ansar B. Mwimbo, Ali H. Abdulkarim

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General transport equation has a wide range of application in Fluid Mechanics and Heat Transfer problems. In this equation, generally when φ variable which represents a flow property is used to represent fluid velocity component, general transport equation turns into momentum equations or with its well known name Navier-Stokes equations. In these non-linear differential equations instead of seeking for analytic solutions, preferring numerical solutions is a more frequently used procedure. Finite difference method is a commonly used numerical solution method. In these equations using velocity and pressure gradients instead of stress tensors decreases the number of unknowns. Also, continuity equation, by integrating the system, number of equations is obtained as number of unknowns. In this situation, velocity and pressure components emerge as two important parameters. In the solution of differential equation system, velocities and pressures must be solved together. However, in the considered grid system, when pressure and velocity values are jointly solved for the same nodal points some problems confront us. To overcome this problem, using staggered grid system is a referred solution method. For the computerized solutions of the staggered grid system various algorithms were developed. From these, two most commonly used are SIMPLE and SIMPLER algorithms. In this study Navier-Stokes equations were numerically solved for Newtonian flow, whose mass or gravitational forces were neglected, for incompressible and laminar fluid, as a hydro dynamically fully developed region and in two dimensional cartesian coordinate system. Finite difference method was chosen as the solution method. This is a parametric study in which varying values of velocity components, pressure and Reynolds numbers were used. Differential equations were discritized using central difference and hybrid scheme. The discritized equation system was solved by Gauss-Siedel iteration method. SIMPLE and SIMPLER were used as solution algorithms. The obtained results, were compared for central difference and hybrid as discritization methods. Also, as solution algorithm, SIMPLE algorithm and SIMPLER algorithm were compared to each other. As a result, it was observed that hybrid discritization method gave better results over a larger area. Furthermore, as computer solution algorithm, besides some disadvantages, it can be said that SIMPLER algorithm is more practical and gave result in short time. For this study, a code was developed in DELPHI programming language. The values obtained in a computer program were converted into graphs and discussed. During sketching, the quality of the graph was increased by adding intermediate values to the obtained result values using Lagrange interpolation formula. For the solution of the system, number of grid and node was found as an estimated. At the same time, to indicate that the obtained results are satisfactory enough, by doing independent analysis from the grid (GCI analysis) for coarse, medium and fine grid system solution domain was obtained. It was observed that when graphs and program outputs were compared with similar studies highly satisfactory results were achieved.

Keywords: finite difference method, GCI analysis, numerical solution of the Navier-Stokes equations, SIMPLE and SIMPLER algoritms

Procedia PDF Downloads 362

Authors: Ahmed Elaksher, Islam Omar

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Accurate geometric relation algorithms are imperative in Earth and planetary satellite and aerial image processing, particularly for high-resolution images that are used for topographic mapping. Most of these satellites carry push-broom sensors. These sensors are optical scanners equipped with linear arrays of CCDs. These sensors have been deployed on most EOSs. In addition, the LROC is equipped with two push NACs that provide 0.5 meter-scale panchromatic images over a 5 km swath of the Moon. The HiRISE carried by the MRO and the HRSC carried by MEX are examples of push-broom sensor that produces images of the surface of Mars. Sensor models developed in photogrammetry relate image space coordinates in two or more images with the 3D coordinates of ground features. Rigorous sensor models use the actual interior orientation parameters and exterior orientation parameters of the camera, unlike approximate models. In this research, we generate a generic push-broom sensor model to process imageries acquired through linear array cameras and investigate its performance, advantages, and disadvantages in generating topographic models for the Earth, Mars, and the Moon. We also compare and contrast the utilization, effectiveness, and applicability of available photogrammetric techniques and softcopies with the developed model. We start by defining an image reference coordinate system to unify image coordinates from all three arrays. The transformation from an image coordinate system to a reference coordinate system involves a translation and three rotations. For any image point within the linear array, its image reference coordinates, the coordinates of the exposure center of the array in the ground coordinate system at the imaging epoch (t), and the corresponding ground point coordinates are related through the collinearity condition that states that all these three points must be on the same line. The rotation angles for each CCD array at the epoch t are defined and included in the transformation model. The exterior orientation parameters of an image line, i.e., coordinates of exposure station and rotation angles, are computed by a polynomial interpolation function in time (t). The parameter (t) is the time at a certain epoch from a certain orbit position. Depending on the types of observations, coordinates, and parameters may be treated as knowns or unknowns differently in various situations. The unknown coefficients are determined in a bundle adjustment. The orientation process starts by extracting the sensor position and, orientation and raw images from the PDS. The parameters of each image line are then estimated and imported into the push-broom sensor model. We also define tie points between image pairs to aid the bundle adjustment model, determine the refined camera parameters, and generate highly accurate topographic maps. The model was tested on different satellite images such as IKONOS, QuickBird, and WorldView-2, HiRISE. It was found that the accuracy of our model is comparable to those of commercial and open-source software, the computational efficiency of the developed model is high, the model could be used in different environments with various sensors, and the implementation process is much more cost-and effort-consuming.

Keywords: photogrammetry, push-broom sensors, IKONOS, HiRISE, collinearity condition

Procedia PDF Downloads 39

Authors: E. K. Tripsanas, D. Spanos, I. Oikonomopoulos, K. Stathopoulou, A. S. Abdelsamad, A. Pagoulatos

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Patraikos Gulf is located offshore western Greece, and it is limited to the west by the Zante, Cephalonia, and Lefkas islands. The Plio/Pleistocene sequence is characterized by two depocenters, the east and west Patraikos basins separated from each other by a prominent sill. This study is based on the Plio/Pleistocene seismic stratigraphy analysis of a newly acquired 3D PSDM (Pre-Stack depth migration) seismic survey in the west Patraikos Basin and few 2D seismic profiles throughout the entire Patraikos Gulf. The eastern Patraikos Basin, although completely buried today with water depths less than 100 m, it was a deep basin during Pliocene ( > 2 km of Pliocene-Pleistocene sediments) and appears to have gathered most of Achelous River discharges. The west Patraikos Gulf was shallower ( < 1300 m of Pliocene-Pleistocene sediments) and characterized by a hummocky relief due to thrust-belt tectonics and Miocene to Pleistocene halokinetic processes. The transition from Pliocene to Miocene is expressed by a widespread erosional unconformity with evidence of fluvial drainage patterns. This indicates that west Patraikos Basin was aerially exposed during the Messinian Salinity Crisis. Continuous to semi-continuous, parallel reflections in the lower, early- to mid-Pliocene seismic packet provides evidence that the re-connection of the Mediterranean Sea with the Atlantic Ocean during Zanclean resulted in the flooding of the west Patraikos basin and the domination of hemipelagic sedimentation interrupted by occasional gravity flows. This is evident in amplitude and semblance horizon slices, which clearly show the presence of long-running, meandering submarine channels sourced from the southeast (northwest Peloponnese) and north. The long-running nature of the submarine channels suggests mobile efficient turbidity currents, probably due to the participation of a sufficient amount of clay minerals in their suspended load. The upper seismic section in the study area mainly consists of several successions of clinoforms, interpreted as progradational delta complexes of Achelous River. This sudden change from marine to shallow marine sedimentary processes is attributed to climatic changes and eustatic perturbations since late Pliocene onwards (~ 2.6 Ma) and/or a switch of Achelous River from the east Patraikos Basin to the west Patraikos Basin. The deltaic seismic unit consists of four delta complexes. The first two complexes result in the infill of topographic depressions and smoothing of an initial hummocky bathymetry. The distribution of the upper two delta complexes is controlled by compensational stacking. Amplitude and semblance horizon slices depict the development of several almost straight and short (a few km long) distributary submarine channels at the delta slopes and proximal prodeltaic plains with lobate sand-sheet deposits at their mouths. Such channels are interpreted to result from low-efficiency turbidity currents with low content in clay minerals. Such a differentiation in the nature of the gravity flows is attributed to the switch of the sediment supply from clay-rich sediments derived from the draining of flysch formations of the Ionian and Gavrovo zones, to the draining of poor in clay minerals carbonate formations of Gavrovo zone through the Achelous River.

Keywords: sequence stratigraphy, basin analysis, river deltas, submarine channels

Procedia PDF Downloads 297

Authors: Nicola Colaninno, Eugenio Morello

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The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

Procedia PDF Downloads 168

Authors: Meiyan Gao, Zongmin Wang, Haibo Yang, Qiuhua Liang

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Under the background of global climate change and rapid development of modern urbanization, the frequency of climate disasters such as extreme precipitation in cities around the world is gradually increasing. In this paper, Hi-PIMS model is used to simulate the "720" flood in Zhengzhou, and the continuous stages of flood resilience are determined with the urban flood stages are divided. The flood resilience curve under the influence of multiple factors were determined and the urban flood toughness was evaluated by combining the results of resilience curves. The flood resilience of urban unit grid was evaluated based on economy, population, road network, hospital distribution and land use type. Firstly, the rainfall data of meteorological stations near Zhengzhou and the remote sensing rainfall data from July 17 to 22, 2021 were collected. The Kriging interpolation method was used to expand the rainfall data of Zhengzhou. According to the rainfall data, the flood process generated by four rainfall events in Zhengzhou was reproduced. Based on the results of the inundation range and inundation depth in different areas, the flood process was divided into four stages: absorption, resistance, overload and recovery based on the once in 50 years rainfall standard. At the same time, based on the levels of slope, GDP, population, hospital affected area, land use type, road network density and other aspects, the resilience curve was applied to evaluate the urban flood resilience of different regional units, and the difference of flood process of different precipitation in "720" rainstorm in Zhengzhou was analyzed. Faced with more than 1,000 years of rainstorm, most areas are quickly entering the stage of overload. The influence levels of factors in different areas are different, some areas with ramps or higher terrain have better resilience, and restore normal social order faster, that is, the recovery stage needs shorter time. Some low-lying areas or special terrain, such as tunnels, will enter the overload stage faster in the case of heavy rainfall. As a result, high levels of flood protection, water level warning systems and faster emergency response are needed in areas with low resilience and high risk. The building density of built-up area, population of densely populated area and road network density all have a certain negative impact on urban flood resistance, and the positive impact of slope on flood resilience is also very obvious. While hospitals can have positive effects on medical treatment, they also have negative effects such as population density and asset density when they encounter floods. The result of a separate comparison of the unit grid of hospitals shows that the resilience of hospitals in the distribution range is low when they encounter floods. Therefore, in addition to improving the flood resistance capacity of cities, through reasonable planning can also increase the flood response capacity of cities. Changes in these influencing factors can further improve urban flood resilience, such as raise design standards and the temporary water storage area when floods occur, train the response speed of emergency personnel and adjust emergency support equipment.

Keywords: urban flood resilience, resilience assessment, hydrodynamic model, resilience curve

Procedia PDF Downloads 18

Authors: Michal Geca, Grzegorz Baranski, Ksenia Siadkowska

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The work is a part of the project which aims at developing innovative power and control systems for the high power aircraft piston engine ASz62IR. Developed electronically controlled ignition system will reduce emissions of toxic compounds as a result of lowered fuel consumption, optimized combustion and engine capability of efficient combustion of ecological fuels. The tested unit is an air-cooled four-stroke gasoline engine of 9 cylinders in a radial setup, mechanically charged by a radial compressor powered by the engine crankshaft. The total engine cubic capac-ity is 29.87 dm3, and the compression ratio is 6.4:1. The maximum take-off power is 1000 HP at 2200 rpm. The maximum fuel consumption is 280 kg/h. Engine powers aircrafts: An-2, M-18 „Dromader”, DHC-3 „OTTER”, DC-3 „Dakota”, GAF-125 „HAWK” i Y5. The main problems of the engine includes the imbalanced work of cylinders. The non-uniformity value in each cylinder results in non-uniformity of their work. In radial engine cylinders arrangement causes that the mixture movement that takes place in accordance (lower cylinder) or the opposite (upper cylinders) to the direction of gravity. Preliminary tests confirmed the presence of uneven workflow of individual cylinders. The phenomenon is most intense at low speed. The non-uniformity is visible on the waveform of cylinder pressure. Therefore two studies were conducted to determine the impact of this phenomenon on the engine performance: simulation and real tests. Simplified simulation was conducted on the element of the intake system coated with fuel film. The study shows that there is an effect of gravity on the movement of the fuel film inside the radial engine intake channels. Both in the lower and the upper inlet channels the film flows downwards. It follows from the fact that gravity assists the movement of the film in the lower cylinder channels and prevents the movement in the upper cylinder channels. Real tests on aircraft engine ASz62IR was conducted in transients condition (rapid change of the excess air in each cylinder were performed. Calculations were conducted for mass of fuel reaching the cylinders theoretically and really and on this basis, the factors of fuel evaporation “x” were determined. Therefore a simplified model of the fuel supply to cylinder was adopted. Model includes time constant of the fuel film τ, the number of engine transport cycles of non-evaporating fuel along the intake pipe γ and time between next cycles Δt. The calculation results of identification of the model parameters are presented in the form of radar graphs. The figures shows the averages declines and increases of the injection time and the average values for both types of stroke. These studies shown, that the change of the position of the cylinder will cause changes in the formation of fuel-air mixture and thus changes in the combustion process. Based on the results of the work of simulation and experiments was possible to develop individual algorithms for ignition control. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: radial engine, ignition system, non-uniformity, combustion process

Procedia PDF Downloads 334