Search results for: spectral reflectance curve

Authors: Karthik K. R, Viswanath V, Asraff A. K

Abstract:

The first stage of a new-generation launch vehicle of ISRO makes use of large pressure vessels made of Aluminium alloy AA2219 to store fuel and oxidizer. These vessels have many weld joints that may contain cracks or crack-like defects during their fabrication. These defects may propagate across the vessel during pressure testing or while in service under the influence of tensile stresses leading to catastrophe. Though ductile materials exhibit significant stable crack growth prior to failure, it is not generally acceptable for an aerospace component. There is a need to predict the initiation of stable crack growth. The structural integrity of the vessel from fracture considerations can be studied by constructing the Failure Assessment Diagram (FAD) that accounts for both brittle fracture and plastic collapse. Critical crack sizes of the pressure vessel may be highly conservative if it is predicted from FAD alone. If the J-R curve for material under consideration is available apriori, the critical crack sizes can be predicted to a certain degree of accuracy. In this paper, a novel approach is proposed to predict the integrity of a weld in a pressure vessel made of AA2219 material. Fracture parameter ‘J-integral’ at the crack front, evaluated through finite element analyses, is used in the new procedure. Based on the simulation of tension tests carried out on SCT specimens by NASA, a cut-off value of J-integral value (J?ᵤₜ_ₒ??) is finalised. For the pressure vessel, J-integral at the crack front is evaluated through FE simulations incorporating different surface cracks at long seam weld in a cylinder and in dome petal welds. The obtained J-integral, at vessel level, is compared with a value of J?ᵤₜ_ₒ??, and the integrity of vessel weld in the presence of the surface crack is firmed up. The advantage of this methodology is that if SCT test data of any metal is available, the critical crack size in hardware fabricated using that material can be predicted to a better level of accuracy.

Keywords: FAD, j-integral, fracture, surface crack

Procedia PDF Downloads 187

Authors: Eric Yi-Hsiu Huang, Meng-Chun Kao, Wen-Chuan Kuo

Abstract:

For every laparoscopic surgery, a safe pneumoperitoneumcreation (gaining access to the peritoneal cavity) is the first and essential step. However, closed pneumoperitoneum is usually obtained by blind insertion of a Veress needle into the peritoneal cavity, which may carry potential risks suchas bowel and vascular injury.Until now, there remains no definite measure to visually confirm the position of the needle tip inside the peritoneal cavity. Therefore, this study established an image-guided Veress needle method by combining a fiber probe with optical coherence tomography (OCT). An algorithm was also proposed for determining the exact location of the needle tip through the acquisition of OCT images. Our method not only generates a series of “live” two-dimensional (2D) images during the needle puncture toward the peritoneal cavity but also can eliminate operator variation in image judgment, thus improving peritoneal access safety. This study was approved by the Ethics Committee of Taipei Veterans General Hospital (Taipei VGH IACUC 2020-144). A total of 2400 in vivo OCT images, independent of each other, were acquired from experiments of forty peritoneal punctures on two piglets. Characteristic OCT image patterns could be observed during the puncturing process. The ROC curve demonstrates the discrimination capability of these quantitative image features of the classifier, showing the accuracy of the classifier for determining the inside vs. outside of the peritoneal was 98% (AUC=0.98). In summary, the present study demonstrates the ability of the combination of our proposed automatic identification method and OCT imaging for automatically and objectively identifying the location of the needle tip. OCT images translate the blind closed technique of peritoneal access into a visualized procedure, thus improving peritoneal access safety.

Keywords: pneumoperitoneum, optical coherence tomography, automatic identification, veress needle

Procedia PDF Downloads 134

Authors: Mehdi Habibagahi, Shami Nejadi, Ata Aminfar

Abstract:

A significant degradation factor that impacts the durability of concrete structures is the alkali-silica reaction. Engineers are frequently charged with the challenges of conducting a thorough safety assessment of concrete structures that have been impacted by ASR. The alkali-silica reaction has a major influence on the structural capacities of structures. In most cases, the reduction in compressive strength, tensile strength, and modulus of elasticity is expressed as a function of free expansion and crack widths. Predicting the effect of ASR on flexural strength is also relevant. In this paper, a nonlinear three-dimensional (3D) finite-element model was proposed to describe the flexural strength degradation induced byASR.Initial strains, initial stresses, initial cracks, and deterioration of material characteristics were all considered ASR factors in this model. The effects of ASR on structural performance were evaluated by focusing on initial flexural stiffness, force–deformation curve, and load-carrying capacity. Degradation of concrete mechanical properties was correlated with ASR growth using material test data conducted at Tech Lab, UTS, and implemented into the FEM for various expansions. The finite element study revealed a better understanding of the ASR-affected RC beam's failure mechanism and capacity reduction as a function of ASR expansion. Furthermore, in this study, decreasing of the residual mechanical properties due to ASRisreviewed, using as input data for the FEM model. Finally, analysis techniques and a comparison of the analysis and the experiment results are discussed. Verification is also provided through analyses of reinforced concrete beams with behavior governed by either flexural or shear mechanisms.

Keywords: alkali-silica reaction, analysis, assessment, finite element, nonlinear analysis, reinforced concrete

Procedia PDF Downloads 159

Authors: Swarnapriya Thiyagarajan, Modesto Antonio Sosa Aquino, Miguel Vallejo Hernandez, Senthilkumar Kalaiselvan Dhivyaraj, Jayaramakrishnan Velusamy

Abstract:

In this paper the lithium tetra borate (Li2B4O7) was prepared by used water/solution assisted synthesis method. Once finished the synthesization, Copper (Cu) were used to doping material with Li2B4O7 in order to enhance its thermo luminescent properties. The heating temperature parameters were 750°C for 2 hr and 150°C for 2hr. The samples produced by water assisted method were doped at different doping percentage (0.02%, 0.04%, 0.06%, 0.08%, 0.12%, 0.5%, 0.1%, and 1%) of Cu.The characteristics and identification of Li2B4O7 (undoped and doped) were determined in four tests. They are X-ray diffraction (XRD), Scanning electron microscope (SEM), Photoluminescence (PL), Ultra violet visible spectroscopy (UV Vis). As it is evidence from the XRD and SEM results the obtained Li2B4O7 and Li2B4O7 doping with Cu was confirmed and also confirmed the chemical compositition and their morphologies. The obtained lithium tetraborate XRD pattern result was verified with the reference data of lithium tetraborate with tetragonal structure from JCPDS. The glow curves of Li2B4O7 and Li2B4O7 : Cu were obtained by thermo luminescence (TLD) reader (Harshaw 3500). The pellets were irradiated with different kind of dose (58mGy, 100mGy, 500mGy, and 945mGy) by using an X-ray source. Finally this energy response was also compared with TLD100. The order of kinetics (b), frequency factor (S) and activation energy (E) or the trapping parameters were calculated using peak shape method. Especially Li2B4O7: Cu (0.1%) presents good glow curve in all kind of doses. The experimental results showed that this Li2B4O7: Cu could have good potential applications in radiation dosimetry. The main purpose of this paper is to determine the effect of synthesis on the TL properties of doped lithium tetra borate Li2B4O7.

Keywords: dosimetry, irradiation, lithium tetraborate, thermoluminescence

Procedia PDF Downloads 277

Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

Abstract:

Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

Procedia PDF Downloads 170

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 69

Authors: Amanina Iymia Jeffree, Reena Thriumani, Mohammad Iqbal Omar, Ammar Zakaria, Yumi Zuhanis Has-Yun Hashim, Ali Yeon Md Shakaff

Abstract:

Metabolite profiling is a strategy to be approached in the pattern recognition method focused on three types of cancer cell line that driving the most to death specifically lung, breast, and colon cancer. The purpose of this study was to discriminate the VOCs pattern among cancerous and control group based on metabolite profiling. The sampling was executed utilizing the cell culture technique. All culture flasks were incubated till 72 hours and data collection started after 24 hours. Every running sample took 24 minutes to be completed accordingly. The comparative metabolite patterns were identified by the implementation of headspace-solid phase micro-extraction (HS-SPME) sampling coupled with gas chromatography-mass spectrometry (GCMS). The optimizations of the main experimental variables such as oven temperature and time were evaluated by response surface methodology (RSM) to get the optimal condition. Volatiles were acknowledged through the National Institute of Standards and Technology (NIST) mass spectral database and retention time libraries. To improve the reliability of significance, it is of crucial importance to eliminate background noise which data from 3rd minutes to 17th minutes were selected for statistical analysis. Targeted metabolites, of which were annotated as known compounds with the peak area greater than 0.5 percent were highlighted and subsequently treated statistically. Volatiles produced contain hundreds to thousands of compounds; therefore, it will be optimized by chemometric analysis, such as principal component analysis (PCA) as a preliminary analysis before subjected to a pattern classifier for identification of VOC samples. The volatile organic compound profiling has shown to be significantly distinguished among cancerous and control group based on metabolite profiling.

Keywords: in vitro cancer cell line, metabolite profiling, pattern recognition, volatile organic compounds

Procedia PDF Downloads 367

Authors: Tao Yang, Yongli Zhao

Abstract:

Low-temperature cracking is one of the major challenges for asphalt pavement in the cold region. Fracture energy could determine from various test methods, which is a commonly used parameter to evaluate the low-temperature cracking resistance of asphalt mixture. However, the feasibility of evaluating the low-temperature cracking performance of asphalt mixture using fracture energy is not investigated comprehensively. This paper aims to verify whether fracture energy is an appropriate parameter to evaluate the low-temperature cracking performance. To achieve this goal, this paper compared the test results of thermal stress restrained specimen test (TSRST) and semi-circular bending test (SCB) of asphalt mixture with different types of aggregate, TSRST and indirect tensile test (IDT) of asphalt mixture with different additives, and single-edge notched beam test (SENB) and TSRST of asphalt mixture with different asphalt. Finally, the correlation between in-suit cracking performance and fracture energy was surveyed. The experimental results showed the evaluation result of critical cracking temperature and fracture energy are not always consistent; the in-suit cracking performance is also not correlated well with fracture energy. These results indicated that it is not feasible to evaluate low-temperature performance by fracture energy. Then, the composition of fracture energy of TSRST, SCB, disk-shaped compact tension test (DCT), three-point bending test (3PB) and IDT was analyzed. The result showed: the area of thermal stress versus temperature curve is the multiple of fracture energy and could be used to represent fracture energy of TSRST, as the multiple is nearly equal among different asphalt mixtures for a specific specimen; the fracture energy, determined from TSRST, SCB, DCT, 3PB, SENB and IDT, is mainly the surface energy that forms the fracture face; fracture energy is inappropriate to evaluate the low-temperature cracking performance of asphalt mixture, as the relaxation/viscous performance is not considered; if the fracture energy was used, it is recommended to combine this parameter with an index characterizing the relaxation or creep performance of asphalt mixture.

Keywords: asphalt pavement, cold region, critical cracking temperature, fracture energy, low-temperature cracking

Procedia PDF Downloads 188

Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

Abstract:

Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

Procedia PDF Downloads 493

Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

Abstract:

Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: damage level monitoring, drift ratio, fragility curve, smart grid, transmission tower

Procedia PDF Downloads 299

Authors: Foo Shen Hwang, Thomas Confrey, Stephen Scully, Barry Flannery

Abstract:

Thermal characterization plays an important role in battery pack design. Lithium-ion batteries have to be maintained between 15-35 °C to operate optimally. Heat is generated (Q) internally within the batteries during both the charging and discharging phases. This can be quantified using several standard methods. The most common method of calculating the batteries heat generation is through the addition of both the joule heating effects and the entropic changes across the battery. In addition, such values can be derived by identifying the open-circuit voltage (OCV), nominal voltage (V), operating current (I), battery temperature (T) and the rate of change of the open-circuit voltage in relation to temperature (dOCV/dT). This paper focuses on experimental characterization and comparative modelling of the heat generation rate (Q) across several current discharge rates (0.5C, 1C, and 1.5C) of a 18650 cell. The analysis is conducted utilizing several non-linear mathematical functions methods, including polynomial, exponential, and power models. Parameter fitting is carried out over the respective function orders; polynomial (n = 3~7), exponential (n = 2) and power function. The generated parameter fitting functions are then used as heat source functions in a 3-D computational fluid dynamics (CFD) solver under natural convection conditions. Generated temperature profiles are analyzed for errors based on experimental discharge tests, conducted at standard room temperature (25°C). Initial experimental results display low deviation between both experimental and CFD temperature plots. As such, the heat generation function formulated could be easier utilized for larger battery applications than other methods available.

Keywords: computational fluid dynamics, curve fitting, lithium-ion battery, voltage drop

Procedia PDF Downloads 95

Authors: T. S. Soliman, A. G. Galyas, E. V. Rusinova, S. A. Vshivkov

Abstract:

The liquid crystals combining properties of a liquid and an anisotropic crystal substance play an important role in a science and engineering. Molecules of cellulose and its derivatives have rigid helical conformation, stabilized by intramolecular hydrogen bonds. Therefore the macromolecules of these polymers are capable to be ordered at dissolution and form liquid crystals of cholesteric type. Phase diagrams of solutions of some cellulose derivatives are known. However, little is known about the effect of a magnetic field on the viscosity of polymer solutions. The systems hydroxypropyl cellulose (HPC) – ethanol, HPC – ethylene glycol, HPC–DМАA, HPC–DMF, ethyl cellulose (EC)–ethanol, EC–DMF, were studied in the presence and absence of magnetic field. The solution viscosity was determined on a Rheotest RN 4.1 rheometer. The effect of a magnetic field on the solution properties was studied with the use of two magnets, which induces a magnetic-field-lines directed perpendicularly and parallel to the rotational axis of a rotor. Application of the magnetic field is shown to be accompanied by an increase in the additional assembly of macromolecules, as is evident from a gain in the radii of light scattering particles. In the presence of a magnetic field, the long chains of macromolecules are oriented in parallel with field lines. Such an orientation is associated with the molecular diamagnetic anisotropy of macromolecules. As a result, supramolecular particles are formed, especially in the vicinity of the region of liquid crystalline phase transition. The magnetic field leads to the increase in viscosity of solutions. The results were used to plot the concentration dependence of η/η0, where η and η0 are the viscosities of solutions in the presence and absence of a magnetic field, respectively. In this case, the values of viscosity corresponding to low shear rates were chosen because the concentration dependence of viscosity at low shear rates is typical for anisotropic systems. In the investigated composition range, the values of η/η0 are described by a curve with a maximum.

Keywords: rheology, liquid crystals, magnetic field, cellulose ethers

Procedia PDF Downloads 348

Authors: Rukshika S Hewawasam, Sisira K. Weliwegamage, Sanath Rajapakse, Subramanium Sotheeswaran

Abstract:

Bio fuel is one of the emerging industries around the world due to arise of crisis in petroleum fuel. Fermentation is a cost effective and eco-friendly process in production of bio-fuel. So inventions in microbes, substrates, technologies in fermentation cause new modifications in fermentation. One major problem in microbial ethanol fermentation is the low resistance of conventional microorganisms to the high ethanol concentrations, which ultimately lead to decrease in the efficiency of the process. In the present investigation, an ethanol resistant bacterium was isolated from sap of Saccharum officinarum (sugar cane). The optimal cultural conditions such as pH, temperature, incubation period, and microbiological characteristics, morphological characteristics, biochemical characteristics, ethanol tolerance, sugar tolerance, growth curve assay were investigated. Isolated microorganism was tolerated to 18% (V/V) of ethanol concentration in the medium and 40% (V/V) glucose concentration in the medium. Biochemical characteristics have revealed as Gram negative, non-motile, negative for Indole test ,Methyl Red test, Voges- Proskauer`s test, Citrate Utilization test, and Urease test. Positive results for Oxidase test was shown by isolated bacterium. Sucrose, Glucose, Fructose, Maltose, Dextrose, Arabinose, Raffinose, Lactose, and Sachcharose can be utilized by this particular bacterium. It is a significant feature in effective fermentation. The fermentation process was carried out in glucose medium under optimum conditions; pH 4, temperature 30˚C, and incubated for 72 hours. Maximum ethanol production was recorded as 12.0±0.6% (V/V). Methanol was not detected in the final product of the fermentation process. This bacterium is especially useful in bio-fuel production due to high ethanol tolerance of this microorganism; it can be used to enhance the fermentation process over conventional microorganisms. Investigations are currently conducted on establishing the identity of the bacterium

Keywords: bacterium, bio-fuel, ethanol tolerance, fermentation

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Authors: Benedict O. Muyale, Emmanuel S. Murunga

Abstract:

Cities have always been the loci for nationals as well as growth of cultural fusion and innovation. Over 50%of global population dwells in cities and urban centers. This means that cities are prolific users of natural resources and generators of waste; hence they produce most of the greenhouse gases which are causing global climate change. The root cause of increase in the transport sector carbon curve is mainly the greater numbers of individually owned cars. Development in these cities is geared towards economic progress while environmental sustainability is ignored. Infrastructure projects focus on road expansion, electrification, and more parking spaces. These lead to more carbon emissions, traffic congestion, and air pollution. Recent development plans for Nairobi city are now on road expansion with little priority for electric train solutions. The Vision 2030, Kenya’s development guide, has shed some light on the city with numerous road expansion projects. This chapter seeks to realize the following objectives; (1) to assess the current transport situation of Nairobi; (2) to review green transport solutions being undertaken in the city; (3) to give an overview of alternative green transportation solutions, and (4) to provide a green transportation framework matrix. This preliminary study will utilize primary and secondary data through mainly desktop research and analysis, literature, books, magazines and on-line information. This forms the basis for formulation of approaches for incorporation into the green transportation framework matrix of the main study report.The main goal is the achievement of a practical green transportation system for implementation by the City County of Nairobi to reduce carbon emissions and congestion and promote environmental sustainability.

Keywords: cities, transport, Nairobi, green technologies

Procedia PDF Downloads 321

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 90

Authors: Huixin Wei, Shibin Wang, Linan Li, Lei Zhou, Xinhao Tu

Abstract:

Facial skin is a biomedical material with complex mechanical properties of anisotropy, viscoelasticity, and hyperelasticity. The mechanical properties of facial skin are crucial for a number of applications including facial plastic surgery, animation, dermatology, cosmetic industry, and impact biomechanics. Skin is a complex multi-layered material which can be broadly divided into three main layers, the epidermis, the dermis, and the hypodermis. Collagen fibers account for 75% of the dry weight of dermal tissue, and it is these fibers which are responsible for the mechanical properties of skin. Many research on the anisotropic mechanical properties are mainly concentrated on in vitro, but there is a great difference between in vivo and in vitro for mechanical properties of the skin. In this study, we presented a method to measure the mechanical properties of facial skin in vivo. Digital image correlation (DIC) and indentation tests were used to obtain the experiment data, including the deformation of facial surface and indentation force-displacement curve. Then, the experiment was simulated using a finite element (FE) model. Application of Computed Tomography (CT) and reconstruction techniques obtained the real tissue geometry. A three-dimensional FE model of facial skin, including a bi-layer system, was obtained. As the epidermis is relatively thin, the epidermis and dermis were regarded as one layer and below it was hypodermis in this study. The upper layer was modeled as a Gasser-Ogden-Holzapfel (GOH) model to describe hyperelastic and anisotropic behaviors of the dermis. The under layer was modeled as a linear elastic model. In conclusion, the material properties of two-layer were determined by minimizing the error between the FE data and experimental data.

Keywords: facial skin, indentation test, finite element, digital image correlation, computed tomography

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Authors: Reza E. Sedgh, Rajesh P. Dhakal

Abstract:

Shear walls have been used extensively as the main lateral force resisting systems in multi-storey buildings. The recent development in performance based design urges practicing engineers to conduct nonlinear static or dynamic analysis to evaluate seismic performance of multi-storey shear wall buildings by employing distinct analytical models suggested in the literature. For practical purpose, application of macroscopic models to simulate the global and local nonlinear behavior of structural walls outweighs the microscopic models. The skill level, computational time and limited access to RC specialized finite element packages prevents the general application of this method in performance based design or assessment of multi-storey shear wall buildings in design offices. Hence, this paper organized to verify capability of nonlinear shell element in commercially available package (Sap2000) in simulating results of some specimens under monotonic and cyclic loads with very oversimplified available cyclic material laws in the analytical tool. The selection of constitutive models, the determination of related parameters of the constituent material and appropriate nonlinear shear model are presented in detail. Adoption of proposed simple model demonstrated that the predicted results follow the overall trend of experimental force-displacement curve. Although, prediction of ultimate strength and the overall shape of hysteresis model agreed to some extent with experiment, the ultimate displacement(significant strength degradation point) prediction remains challenging in some cases.

Keywords: analytical model, nonlinear shell element, structural wall, shear behavior

Procedia PDF Downloads 404

Authors: I. Asanuma, T. Yamaguchi, J. Park, K. J. Mackin

Abstract:

Fishery lights on the surface could be detected by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi-NPP). The DNB covers the spectral range of 500 to 900 nm and realized a higher sensitivity. The DNB has a difficulty of identification of fishing lights from lunar lights reflected by clouds, which affects observations for the half of the month. Fishery lights and lights of the surface are identified from lunar lights reflected by clouds by a method using the DNB and the infrared band, where the detection limits are defined as a function of the brightness temperature with a difference from the maximum temperature for each level of DNB radiance and with the contrast of DNB radiance against the background radiance. Fishery boats or structures on islands could be detected by the Synthetic Aperture Radar (SAR) on the polar orbit satellites using the reflected microwave by the surface reflecting targets. The SAR has a difficulty of tradeoff between spatial resolution and coverage while detecting the small targets like fishery boats. A distribution of fishery boats and island activities were detected by the scan-SAR narrow mode of Radarsat-2, which covers 300 km by 300 km with various combinations of polarizations. The fishing boats were detected as a single pixel of highly scattering targets with the scan-SAR narrow mode of which spatial resolution is 30 m. As the look angle dependent scattering signals exhibits the significant differences, the standard deviations of scattered signals for each look angles were taken into account as a threshold to identify the signal from fishing boats and structures on the island from background noise. It was difficult to validate the detected targets by DNB with SAR data because of time lag of observations for 6 hours between midnight by DNB and morning or evening by SAR. The temporal changes of island activities were detected as a change of mean intensity of DNB for circular area for a certain scale of activities. The increase of DNB mean intensity was corresponding to the beginning of dredging and the change of intensity indicated the ending of reclamation and following constructions of facilities.

Keywords: day night band, SAR, fishery, South China Sea

Procedia PDF Downloads 235

Authors: M. Abuqebitah, H. Tanyildizi, N. Yeyin, I. Cavdar, M. Demir, L. Kabasakal

Abstract:

Aim: Targeted radionuclide therapy (TRT) is an increasingly used treatment modality for wide range of cancers. Presently dosimetry is highly required either to plan treatment or to ascertain the absorbed dose delivered to critical organs during treatment. Methods and Materials: The study comprised 7 patients suffered from prostate cancer with progressive disease and candidate to undergo Lu-177-DOTA-617 therapy following to PSMA- PET/CT imaging for all patients. (5.2±0.3 mCi) was intravenously injected. To evaluate bone marrow absorbed dose 2 cc blood samples were withdrawn in short variable times (3, 15, 30, 60, 180 minutes) after injection. Furthermore, whole body scans were performed using scintillation gama camera in 4, 24, 48, and 120 hours after injection and in order to quantify the activity taken up in the body, kidneys , liver, right parotid, and left parotid the geometric mean of anterior and posterior counts were determined through ROI analysis, after that background subtraction and attenuation correction were applied using patients PSMA- PET/CT images taking in a consideration: organ thickness, body thickness, and Hounsfield unites from CT scan. OLINDA/EXM dosimetry program was used for curve fitting, residence time calculation, and absorbed dose calculations. Findings: Absorbed doses of bone marrow, left kidney, right kidney, liver, left parotid, right parotid, total body were 1.28±0.52, 32.36±16.36, 32.7±13.68, 10.35±3.45, 38.67±21.29, 37.55±19.77, 2.25±0.95 (mGy/mCi), respectively. Conclusion: Our first results clarify that Lu-177-DOTA-617 is safe and reliable therapy as there were no complications seen. In the other hand, the observable variation in the absorbed dose of the critical organs among the patients necessitate patient-specific dosimetry approach to save body organs and particularly highly exposed kidneys and parotid gland.

Keywords: Lu-177-PSMA, prostate cancer, radionuclide therapy

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Authors: Susanne Fridsten, Kristina Hellman, Anders Sundin, Lennart Blomqvist

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Background: Patients diagnosed with locally advanced cervical carcinoma are treated with definitive concomitant chemo-radiotherapy. Treatment failure occurs in 30-50% of patients with very poor prognoses. The treatment is standardized with risk for both over-and undertreatment. Consequently, there is a great need for biomarkers able to predict therapy outcomes to allow for individualized treatment. Aim: To explore the role of T2- and diffusion-weighted magnetic resonance imaging (MRI) for early prediction of therapy outcome and the optimal time point for assessment. Methods: A pilot study including 15 patients with cervical carcinoma stage IIB-IIIB (FIGO 2009) undergoing definitive chemoradiotherapy. All patients underwent MRI four times, at baseline, 3 weeks, 5 weeks, and 12 weeks after treatment started. Tumour size, size change (∆size), visibility on diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and change of ADC (∆ADC) at the different time points were recorded. Results: 7/15 patients relapsed during the study period, referred to as "poor prognosis", PP, and the remaining eight patients are referred to "good prognosis", GP. The tumor size was larger at all time points for PP than for GP. The ∆size between any of the four-time points was the same for PP and GP patients. The sensitivity and specificity to predict prognostic group depending on a remaining tumor on DWI were highest at 5 weeks and 83% (5/6) and 63% (5/8), respectively. The combination of tumor size at baseline and remaining tumor on DWI at 5 weeks in ROC analysis reached an area under the curve (AUC) of 0.83. After 12 weeks, no remaining tumor was seen on DWI among patients with GP, as opposed to 2/7 PP patients. Adding ADC to the tumor size measurements did not improve the predictive value at any time point. Conclusion: A large tumor at baseline MRI combined with a remaining tumor on DWI at 5 weeks predicted a poor prognosis.

Keywords: chemoradiotherapy, diffusion-weighted imaging, magnetic resonance imaging, uterine cervical carcinoma

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Authors: N. Tochukwu, M. Mukhopadhyay, A. Mohamed

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It is no new that Nigeria faces a continual power shortage problem due to its vast population power demand and heavy reliance on nonrenewable forms of energy such as thermal power or fossil fuel. Many researchers have recommended using geothermal energy as an alternative; however, Past studies focus on the geophysical & geochemical investigation of this energy in the sedimentary and basement complex; only a few studies incorporated the remote sensing methods. Therefore, in this study, the preliminary examination of geothermal resources in the Middle Benue was carried out using satellite imagery in ArcMap. Landsat 8 scene (TIR, NIR, Red spectral bands) was used to estimate the Land Surface Temperature (LST). The Maximum Likelihood Classification (MLC) technique was used to classify sites with very low, low, moderate, and high LST. The intermediate and high classification happens to be possible geothermal zones, and they occupy 49% of the study area (38077km2). Riverline were superimposed on the LST layer, and the identification tool was used to locate high temperate sites. Streams that overlap on the selected sites were regarded as geothermal springs as. Surprisingly, the LST results show lower temperatures (<36°C) at the famous thermal springs (Awe & Wukari) than some unknown rivers/streams found in Kwande (38°C), Ussa, (38°C), Gwer East (37°C), Yola Cross & Ogoja (36°C). Studies have revealed that temperature increases with depth. However, this result shows excellent geothermal resources potential as it is expected to exceed the minimum geothermal gradient of 25.47 with an increase in depth. Therefore, further investigation is required to estimate the depth of the causative body, geothermal gradients, and the sustainability of the reservoirs by geophysical and field exploration. This method has proven to be cost-effective in locating geothermal resources in the study area. Consequently, the same procedure is recommended to be applied in other regions of the Precambrian basement complex and the sedimentary basins in Nigeria to save a preliminary field survey cost.

Keywords: ArcMap, geothermal resources, Landsat 8, LST, thermal springs, MLC

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Authors: Gelacio JuáRez-Luna, Daniel Enrique GonzáLez-RamíRez, Enrique Tenorio-Montero

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Frame elements coupled with springs elements are used for modelling the development of hinges in segmented tunnels, the spring elements modelled the rotational, transversal and axial failure. These spring elements are equipped with constitutive models to include independently the moment, shear force and axial force, respectively. These constitutive models are formulated based on damage mechanics and experimental test reported in the literature review. The mesh of the segmented tunnels was discretized in the software GID, and the nonlinear analyses were carried out in the finite element software ANSYS. These analyses provide the capacity curve of the primary and secondary lining of a segmented tunnel. Two numerical examples of segmented tunnels show the capability of the spring elements to release energy by the development of hinges. The first example is a segmental concrete lining discretized with frame elements loaded until hinges occurred in the lining. The second example is a tunnel with primary and secondary lining, discretized with a double ring frame model. The outer ring simulates the segmental concrete lining and the inner ring simulates the secondary cast-in-place concrete lining. Spring elements also modelled the joints between the segments in the circumferential direction and the ring joints, which connect parallel adjacent rings. The computed load vs displacement curves are congruent with numerical and experimental results reported in the literature review. It is shown that the modelling of a tunnel with primary and secondary lining with frame elements and springs provides reasonable results and save computational cost, comparing with 2D or 3D models equipped with smeared crack models.

Keywords: damage, hinges, lining, tunnel

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Authors: Kehabtimer Shiferaw Kotiso, Getachew Hailemariam, Abiy Seifu Estifanos

Abstract:

Introduction: Despite the highest share of low birth weight (LBW) for neonatal mortality and morbidity, predicting births with LBW for better intervention preparation is challenging. This study aims to predict LBW using a dataset encompassing 53,637 birth cohorts collected from 36 primary hospitals across seven regions in Ethiopia from February 2022 to June 2024. Methods: We identified ten explanatory variables related to maternal and neonatal characteristics, including maternal education, age, residence, history of miscarriage or abortion, history of preterm birth, type of pregnancy, number of livebirths, number of stillbirths, antenatal care frequency, and sex of the fetus to predict LBW. Using WEKA 3.8.2, we developed and compared seven machine learning algorithms. Data preprocessing included handling missing values, outlier detection, and ensuring data integrity in birth weight records. Model performance was evaluated through metrics such as accuracy, precision, recall, F1-score, and area under the Receiver Operating Characteristic curve (ROC AUC) using 10-fold cross-validation. Results: The results demonstrated that the decision tree, J48, logistic regression, and gradient boosted trees model achieved the highest accuracy (94.5% to 94.6%) with a precision of 93.1% to 93.3%, F1-score of 92.7% to 93.1%, and ROC AUC of 71.8% to 76.6%. Conclusion: This study demonstrates the effectiveness of machine learning models in predicting LBW. The high accuracy and recall rates achieved indicate that these models can serve as valuable tools for healthcare policymakers and providers in identifying at-risk newborns and implementing timely interventions to achieve the sustainable developmental goal (SDG) related to neonatal mortality.

Keywords: low birth weight, machine learning, classification, neonatal mortality, Ethiopia

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Authors: P. M. Kundu, L. R. Singo, J. O. Odiyo

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Luvuvhu River catchment in South Africa experiences floods resulting from heavy rainfall of intensities exceeding 15 mm per hour associated with the Inter-tropical Convergence Zone (ITCZ). The generation of runoff is triggered by the rainfall intensity and soil moisture status. In this study, remote sensing and GIS techniques were used to analyze the hydrologic response to land cover changes. Runoff was calculated as a product of the net precipitation and a curve number coefficient. It was then routed using the Muskingum-Cunge method using a diffusive wave transfer model that enabled the calculation of response functions between start and end point. Flood frequency analysis was determined using theoretical probability distributions. Spatial data on land cover was obtained from multi-temporal Landsat images while data on rainfall, soil type, runoff and stream discharges was obtained by direct measurements in the field and from the Department of Water. A digital elevation model was generated from contour maps available at http://www.ngi.gov.za. The results showed that land cover changes had impacted negatively to the hydrology of the catchment. Peak discharges in the whole catchment were noted to have increased by at least 17% over the period while flood volumes were noted to have increased by at least 11% over the same period. The flood time to peak indicated a decreasing trend, in the range of 0.5 to 1 hour within the years. The synergism between remotely sensed digital data and GIS for land surface analysis and modeling was realized, and it was therefore concluded that hydrologic modeling has potential for determining the influence of changes in land cover on the hydrologic response of the catchment.

Keywords: catchment, digital elevation model, hydrological model, routing, runoff

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Authors: Ella Sèdé Maforikan

Abstract:

Sustained water management requires quantitative information and the knowledge of spatiotemporal dynamics of hydrological system within the basin. This can be achieved through the research. Several studies have investigated both surface water and groundwater in Beterou catchment. However, there are few published papers on the application of the SWAT modeling in Beterou catchment. The objective of this study was to evaluate the performance of SWAT to simulate the water balance within the watershed. The inputs data consist of digital elevation model, land use maps, soil map, climatic data and discharge records. The model was calibrated and validated using the Sequential Uncertainty Fitting (SUFI2) approach. The calibrated started from 1989 to 2006 with four years warming up period (1985-1988); and validation was from 2007 to 2020. The goodness of the model was assessed using five indices, i.e., Nash–Sutcliffe efficiency (NSE), the ratio of the root means square error to the standard deviation of measured data (RSR), percent bias (PBIAS), the coefficient of determination (R²), and Kling Gupta efficiency (KGE). Results showed that SWAT model successfully simulated river flow in Beterou catchment with NSE = 0.79, R2 = 0.80 and KGE= 0.83 for the calibration process against validation process that provides NSE = 0.78, R2 = 0.78 and KGE= 0.85 using site-based streamflow data. The relative error (PBIAS) ranges from -12.2% to 3.1%. The parameters runoff curve number (CN2), Moist Bulk Density (SOL_BD), Base Flow Alpha Factor (ALPHA_BF), and the available water capacity of the soil layer (SOL_AWC) were the most sensitive parameter. The study provides further research with uncertainty analysis and recommendations for model improvement and provision of an efficient means to improve rainfall and discharges measurement data.

Keywords: watershed, water balance, SWAT modeling, Beterou

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Authors: D. F. Zeynalov, T. V. Kartseva, O. V. Sorokin

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Currently, approaches to assess cardiointervalography are based on the calculation of data variance intervals RR. However, they do not allow the evaluation of features related to a period of the cardiac cycle, so how electromechanical phenomena during cardiac subphase are characterized by differently directed changes. Therefore, we have proposed a method of subphase analysis of the cardiac cycle, developed in the department of hominal physiology Novosibirsk State Medical University to identify the features of the dispersion subphase of the cardiac cycle. In the present paper we have examined the 5-minute intervals cardiointervalography (CIG) to isolate RR-, QT-, ST-ranges in healthy children and children with acute respiratory diseases (ARD) in comparison. It is known that primary school-aged children suffer at ARD 5-7 times per year. Consequently, it is one of the most relevant problems in pediatrics. It is known that the spectral indices and indices of temporal analysis of heart rate variability are highly sensitive to the degree of intoxication during immunological process. We believe that the use of subphase analysis of heart rate will allow more thoroughly evaluate responsiveness of the child organism during the course of ARD. The study involved 60 primary school-aged children (30 boys and 30 girls). In order to assess heart rhythm regulation, the record CIG was used on the "VNS-Micro" device of Neurosoft Company (Ivanovo) for 5 minutes in the supine position and 5 minutes during active orthostatic test. Subphase analysis of variance QT-interval and ST-segment was performed on the "KardioBOS" software Biokvant Company (Novosibirsk). In assessing the CIG in the supine position and in during orthostasis of children with acute respiratory diseases only RR-intervals are observed typical trend of general biological reactions through pressosensitive compensation mechanisms to lower blood pressure, but compared with healthy children the severity of the changes is different, of sick children are more pronounced indicators of heart rate regulation. But analysis CIG RR-intervals and analysis subphase ST-segment have yielded conflicting trends, which may be explained by the different nature of the intra- and extracardiac influences on regulatory mechanisms that implement the various phases of the cardiac cycle.

Keywords: acute respiratory diseases, cardiointervalography, subphase analysis, cardiac cycle

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Authors: Mubarak Suliman, Mohamed Hassan

Abstract:

Detection of downed conductors occurring with high fault resistance (reaching kilo-ohms) has always been a challenge, especially in countries like Saudi Arabia, on which earth resistivity is very high in general (reaching more than 1000 Ω-meter). The new approaches for the detection of resistive and high impedance faults are based on the analysis of the fault current waveform. These methods are still under research and development, and they are currently lacking security and dependability. The other approach is communication-based solutions which depends on voltage measurement at the end of overhead line branches and communicate the measured signals to substation feeder relay or a central control center. However, such a detection method is costly and depends on the availability of communication medium and infrastructure. The main objective of this research is to utilize the available standard protection schemes to increase the probability of detection of downed conductors occurring with a low magnitude of fault currents and at the same time avoiding unwanted tripping in healthy conditions and feeders. By specifying the operating region of the faulty feeder, use of tripping curve for discrimination between faulty and healthy feeders, and with proper selection of core balance current transformer (CBCT) and voltage transformers with fewer measurement errors, it is possible to set the pick-up of sensitive earth fault current to minimum values of few amps (i.e., Pick-up Settings = 3 A or 4 A, …) for the detection of earth faults with fault resistance more than (1 - 2 kΩ) for 13.8kV overhead network and more than (3-4) kΩ fault resistance in 33kV overhead network. By implementation of the outcomes of this study, the probability of detection of downed conductors is increased by the utilization of existing schemes (i.e., Directional Sensitive Earth Fault Protection).

Keywords: sensitive earth fault, zero sequence current, grounded system, resistive fault detection, healthy feeder

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Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

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Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

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Authors: Yidan Xu, Pim Martens, Thomas Krafft

Abstract:

Marine fishing, an energy-intensive activity, directly emits greenhouse gases through fuel combustion, making it a significant contributor to oceanic greenhouse gas (GHG) emissions and worsening climate change. China is the world’s second-largest economy and the top emitter of GHG emissions, and it carries a significant energy conservation and emission reduction burden. However, the increasing GHG emissions from marine fishing is an easily overlooked but essential issue in China. This study offers a diverse perspective by integrating the concepts of total carbon emissions, carbon intensity, and per capita carbon emissions as indicators into calculation and discussion. To better understand the GHG emissions-Gross marine fishery product (GFP) relationship and influencing factors in Chinese marine fishing, the relationship between GHG emissions and economic development in marine fishing, a comprehensive framework is developed by combining the environmental Kuznets curve, the Tapio elasticity index, and the decomposition model. Results indicated that (1) The GHG emissions increased from 16.479 to 18.601 million tons in 2001-2020, in which trawlers and gillnetter are the main source in fishing operation. (2) Total carbon emissions (TC) and CI presented the same decline as GHG emissions, while per capita carbon emissions (PC) displayed an uptrend. (32) GHG emissions and gross marine fishery product (GFP) presented an inverted U-shaped relationship in China; the turning point came in the 13th Five-year Plan period (2016-2020). (43) Most provinces strongly decoupled GFP and CI. Still, PC and TC need more effort to decouple. (54) GHG emissions promoted by an industry structure driven, though carbon intensity and industry scale aid in GHG emissions reduced. (5) Compare with TC and PC, CI has been relatively affected by COVID-19 in 2020. The rise in fish and seafood prices during COVID-19 has boosted the GFP.

Keywords: marine fishing economy, greenhouse gas emission, fishery management, green development

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Authors: C. Mendoza Ramírez, M. Gambús Ordaz, R. Mercado Ojeda.

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Chemical solutions flooding with surfactants, based on their property of reducing the interfacial tension between crude oil and water, is a potential application of chemical enhanced oil recovery (CEOR), however, the high-rate retention of surfactants associated with adsorption in the porous medium and the complexity of the mineralogical composition of the reservoir rock generates a limitation in the efficiency of displacement of crude oil. This study evaluates the effect of the concentration of a mixture of anionic-non-ionic surfactants with silica nanoparticles, in a rock sample composed of 25.14% clay minerals of the kaolinite, chlorite, halloysite and montmorillonite type, according to the results of X-Ray Diffraction analysis and Scanning Electron Spectrometry (XRD and SEM, respectively). The amount of the surfactant mixture adsorbed on the clay rock minerals was analyzed from the construction of its calibration curve and the 4-Region Isotherm Model in a UV-Visible spectroscopy. The adsorption rate of the surfactant in the clay rock averages 32% across all concentrations, influenced by the presence of the surface area of the substrate with a value of 1.6 m2/g and by the mineralogical composition of the clay that increases the cation exchange capacity (CEC). In addition, on Region I and II a final concentration measurement is not evident in the UV-VIS, due to its ionic nature, its high affinity with the clay rock and its low concentration. Finally, for potential CEOR applications, the adsorption of these mixed surfactant systems is considered due to their industrial relevance and it is concluded that it is possible to use concentrations in Region III and IV; initially the adsorption has an increasing slope and then reaches zero in the equilibrium where interfacial tension values are reached in the order of x10-1 mN/m.

Keywords: anionic–nonionic surfactants, clay rock, adsorption, 4-region isotherm model, cation exchange capacity, critical micelle concentration, enhanced oil recovery

Procedia PDF Downloads 69