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Authors: Juliana A. B. Silva, Caio H. T. L. Albuquerque, Leonardo L. dos Santos, Cristiane K. Oliveira, Ivani Malvestiti, Fernando Hallwass, Ricardo L. Longo

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Complexes with lanthanide ions have been extensively studied due to their applications as luminescent, magnetic and catalytic materials as molecular or extended crystals, thin films, glasses, polymeric matrices, ionic liquids, and in solution. NMR chemical shift data in solution have been reported and suggest fluxional structures in a wide range of coordination compounds with rare earth ions. However, the fluxional mechanisms for these compounds are still not established. This structural fluxionality may affect the photophysical, catalytic and magnetic properties in solution. Thus, understanding the structural interconversion mechanisms may aid the design of coordination compounds with, for instance, improved (electro)luminescence, catalytic and magnetic behaviors. The [Eu(btfa)₃bipy] complex, where btfa= 4,4,4-trifluoro-1-phenyl-1,3-butanedionate and bipy= 2,2’-bipiridyl, has a well-defined X-ray crystallographic structure and preliminary 1H NMR data suggested a structural fluxionality. Thus, we have investigated a series of coordination compounds with lanthanide ions [Ln(btfa)₃L], where Ln = La, Eu, Gd or Yb and L= bipy or phen (phen=1,10-phenanthroline) using a combined theoretical-experimental approach. These complexes were synthesized and fully characterized, and detailed NMR measurements were obtained. They were also studied by quantum chemical computational methods (DFT-PBE0). The aim was to determine the relevant factors in the structure of these compounds that favor or not the fluxional behavior. Measurements of the 1H NMR signals at variable temperature in CD₂Cl₂ of the [Eu(btfa)₃L] complexes suggest that these compounds have a fluxional structure, because the crystal structure has non-equivalent btfa ligands that should lead to non-equivalent hydrogen atoms and thus to more signals in the NMR spectra than those obtained at room temperature, where all hydrogen atoms of the btfa ligands are equivalent, and phen ligand has an effective vertical symmetry plane. For the [Eu(btfa)₃bipy] complex, the broadening of the signals at –70°C provides a lower bound for the coalescence temperature, which indicates the energy barriers involved in the structural interconversion mechanisms are quite small. These barriers and, consequently, the coalescence temperature are dependent upon the radii of the lanthanide ion as well as to their paramagnetic effects. The PBE0 calculated structures are in very good agreement with the crystallographic data and, for the [Eu(btfa)₃bipy] complex, this method provided several distinct structures with almost the same energy. However, the energy barrier for structural interconversion via dissociative pathways were found to be quite high and could not explain the experimental observations. Whereas the pseudo-rotation pathways, involving the btfa and bipy ligands, have very small activation barriers, in excellent agreement with the NMR data. The results also showed an increase in the activation barrier along the lanthanide series due to the decrease of the ionic radii and consequent increase of the steric effects. TD-DFT calculations showed a dependence of the ligand donor state energy with different structures of the complex [Eu(btfa)₃phen], which can affect the energy transfer rates and the luminescence. The energy required to promote the structural fluxionality may also enhance the luminescence quenching in solution. These results can aid in the design of more luminescent compounds and more efficient devices.

Keywords: computational chemistry, lanthanide-based compounds, NMR, structural fluxionality

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: K. C. Apil, Keshab Sharma, Bigul Pokharel

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Kathmandu Valley, capital city of Nepal houses numerous historical monuments as well as religious structures which are as old as from the 4th century A.D. The city alone is home to seven UNESCO’s world heritage sites including various public squares and religious sanctums which are often regarded as living heritages by various historians and archeological explorers. Recently on April 25, 2015, the capital city including other nearby locations was struck with Gorkha earthquake of moment magnitude (Mw) 7.8, followed by the strongest aftershock of moment magnitude (Mw) 7.3 on May 12. This study reports structural failures and collapse of heritage structures in Kathmandu Valley during the earthquake and presents preliminary findings as to the causes of failures and collapses. Field reconnaissance was carried immediately after the main shock and the aftershock, in major heritage sites: UNESCO world heritage sites, a number of temples and historic buildings in Kathmandu Durbar Square, Patan Durbar Square, and Bhaktapur Durbar Square. Despite such catastrophe, a significant number of heritage structures stood high, performing very well during the earthquake. Preliminary reports from archeological department suggest that 721 of such structures were severely affected, whereas numbers within the valley only were 444 including 76 structures which were completely collapsed. This study presents recorded accelerograms and geology of Kathmandu Valley. Structural typology and architecture of the heritage structures in Kathmandu Valley are briefly described. Case histories of damaged heritage structures, the patterns, and the failure mechanisms are also discussed in this paper. It was observed that performance of heritage structures was influenced by the multiple factors such as structural and architecture typology, configuration, and structural deficiency, local ground site effects and ground motion characteristics, age and maintenance level, material quality etc. Most of such heritage structures are of masonry type using bricks and earth-mortar as a bonding agent. The walls' resistance is mainly compressive, thus capable of withstanding vertical static gravitational load but not horizontal dynamic seismic load. There was no definitive pattern of damage to heritage structures as most of them behaved as a composite structure. Some structures were extensively damaged in some locations, while structures with similar configuration at nearby location had little or no damage. Out of major heritage structures, Dome, Pagoda (2, 3 or 5 tiered temples) and Shikhara structures were studied with similar variables. Studying varying degrees of damages in such structures, it was found that Shikhara structures were most vulnerable one where Dome structures were found to be the most stable one, followed by Pagoda structures. The seismic performance of the masonry-timber and stone masonry structures were slightly better than that of the masonry structures. Regular maintenance and periodic seismic retrofitting seems to have played pivotal role in strengthening seismic performance of the structure. The study also recommends some key functions to strengthen the seismic performance of such structures through study based on structural analysis, building material behavior and retrofitting details. The result also recognises the importance of documentation of traditional knowledge and its revised transformation in modern technology.

Keywords: Gorkha earthquake, field observation, heritage structure, seismic performance, masonry building

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Authors: Pedro Llanos, Diego García

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Spaceflight is considered the last frontier in terms of science, technology, and engineering. But it is also the next frontier in terms of human physiology and performance. After more than 200,000 years humans have evolved under earth’s gravity and atmospheric conditions, spaceflight poses environmental stresses for which human physiology is not adapted. Hypoxia, accelerations, and radiation are among such stressors, our research involves suborbital flights aiming to develop effective countermeasures in order to assure sustainable human space presence. The physiologic baseline of spaceflight participants is subject to great variability driven by age, gender, fitness, and metabolic reserve. The objective of the present study is to characterize different physiologic variables in a population of STEM practitioners during an aerobatic flight. Cardiovascular and pulmonary responses were determined in Science Astronaut Candidates (SACs) during unusual attitude aerobatic flight indoctrination. Physiologic data recordings from 20 subjects participating in high-G flight training were analyzed. These recordings were registered by wearable sensor-vest that monitored electrocardiographic tracings (ECGs), signs of dysrhythmias or other electric disturbances during all the flight. The same cardiovascular parameters were also collected approximately 10 min pre-flight, during each high-G/unusual attitude maneuver and 10 min after the flights. The ratio (pre-flight/in-flight/post-flight) of the cardiovascular responses was calculated for comparison of inter-individual differences. The resulting tracings depicting the cardiovascular responses of the subjects were compared against the G-loads (Gs) during the aerobatic flights to analyze cardiovascular variability aspects and fluid/pressure shifts due to the high Gs. In-flight ECG revealed cardiac variability patterns associated with rapid Gs onset in terms of reduced heart rate (HR) and some scattered dysrhythmic patterns (15% premature ventricular contractions-type) that were considered as triggered physiological responses to high-G/unusual attitude training and some were considered as instrument artifact. Variation events were observed in subjects during the +Gz and –Gz maneuvers and these may be due to preload and afterload, sudden shift. Our data reveal that aerobatic flight influenced the breathing rate of the subject, due in part by the various levels of energy expenditure due to the increased use of muscle work during these aerobatic maneuvers. Noteworthy was the high heterogeneity in the different physiological responses among a relatively small group of SACs exposed to similar aerobatic flights with similar Gs exposures. The cardiovascular responses clearly demonstrated that SACs were subjected to significant flight stress. Routine ECG monitoring during high-G/unusual attitude flight training is recommended to capture pathology underlying dangerous dysrhythmias in suborbital flight safety. More research is currently being conducted to further facilitate the development of robust medical screening, medical risk assessment approaches, and suborbital flight training in the context of the evolving commercial human suborbital spaceflight industry. A more mature and integrative medical assessment method is required to understand the physiology state and response variability among highly diverse populations of prospective suborbital flight participants.

Keywords: g force, aerobatic maneuvers, suborbital flight, hypoxia, commercial astronauts

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Authors: Marcial Blondet, Malena Serrano, Álvaro Rubiños, Elin Mattsson

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In Peru, there are more than two million houses made of adobe (sun dried mud bricks) or rammed earth (35% of the total houses), in which almost 9 million people live, mainly because they cannot afford to purchase industrialized construction materials. Although adobe houses are cheap to build and thermally comfortable, their seismic performance is very poor, and they usually suffer significant damage or collapse with tragic loss of life. Therefore, over the years, researchers at the Pontifical Catholic University of Peru and other institutions have developed many reinforcement techniques as an effort to improve the structural safety of earthen houses located in seismic areas. However, most rural communities live under unacceptable seismic risk conditions because these techniques have not been adopted massively, mainly due to high cost and lack of diffusion. The nylon rope mesh reinforcement technique is simple and low-cost, and two technological transference tools have been developed to diffuse it among rural communities: 1) Scale seismic simulations using a portable shaking table have been designed to prove its effectiveness to protect adobe houses; 2) A step-by-step illustrated construction manual has been developed to guide the complete building process of a nylon rope mesh reinforced adobe house. As a study case, it was selected the district of Pullo: a small rural community in the Peruvian Andes where more than 80% of its inhabitants live in adobe houses and more than 60% are considered to live in poverty or extreme poverty conditions. The research team carried out a one-day workshop in May 2015 and a two-day workshop in September 2015. Results were positive: First, the nylon rope mesh reinforcement procedure was proven simple enough to be replicated by adults, both young and seniors, and participants handled ropes and knots easily as they use them for daily livestock activity. In addition, nylon ropes were proven highly available in the study area as they were found at two local stores in variety of color and size.. Second, the portable shaking table demonstration successfully showed the effectiveness of the nylon rope mesh reinforcement and generated interest on learning about it. On the first workshop, more than 70% of the participants were willing to formally subscribe and sign up for practical training lessons. On the second workshop, more than 80% of the participants returned the second day to receive introductory practical training. Third, community members found illustrations on the construction manual simple and friendly but the roof system illustrations led to misinterpretation so they were improved. The technological transfer tools developed in this project can be used to train rural dwellers on earthquake-resistant self-construction with adobe, which is still very common in the Peruvian Andes. This approach would allow community members to develop skills and capacities to improve safety of their households on their own, thus, mitigating their high seismic risk and preventing tragic losses. Furthermore, proper training in earthquake-resistant self-construction with adobe would prevent rural dwellers from depending on external aid after an earthquake and become agents of their own development.

Keywords: adobe, Peruvian Andes, safe housing, technological transference

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Authors: Abderrazak Bannari

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Acid Mine Drainage (AMD) from mine wastes and contaminations of soils and water with metals are considered as a major environmental problem in mining areas. It is produced by interactions of water, air, and sulphidic mine wastes. This environment problem results from a series of chemical and biochemical oxidation reactions of sulfide minerals e.g. pyrite and pyrrhotite. These reactions lead to acidity as well as the dissolution of toxic and heavy metals (Fe, Mn, Cu, etc.) from tailings waste rock piles, and open pits. Soil and aquatic ecosystems could be contaminated and, consequently, human health and wildlife will be affected. Furthermore, secondary minerals, typically formed during weathering of mine waste storage areas when the concentration of soluble constituents exceeds the corresponding solubility product, are also important. The most common secondary mineral compositions are hydrous iron oxide (goethite, etc.) and hydrated iron sulfate (jarosite, etc.). The objectives of this study focus on the detection and mapping of MIOP in the soil using Hyperion EO-1 (Earth Observing - 1) hyperspectral data and constrained linear spectral mixture analysis (CLSMA) algorithm. The abandoned Kettara mine, located approximately 35 km northwest of Marrakech city (Morocco) was chosen as study area. During 44 years (from 1938 to 1981) this mine was exploited for iron oxide and iron sulphide minerals. Previous studies have shown that Kettara surrounding soils are contaminated by heavy metals (Fe, Cu, etc.) as well as by secondary minerals. To achieve our objectives, several soil samples representing different MIOP classes have been resampled and located using accurate GPS ( ≤ ± 30 cm). Then, endmembers spectra were acquired over each sample using an Analytical Spectral Device (ASD) covering the spectral domain from 350 to 2500 nm. Considering each soil sample separately, the average of forty spectra was resampled and convolved using Gaussian response profiles to match the bandwidths and the band centers of the Hyperion sensor. Moreover, the MIOP content in each sample was estimated by geochemical analyses in the laboratory, and a ground truth map was generated using simple Kriging in GIS environment for validation purposes. The acquired and used Hyperion data were corrected for a spatial shift between the VNIR and SWIR detectors, striping, dead column, noise, and gain and offset errors. Then, atmospherically corrected using the MODTRAN 4.2 radiative transfer code, and transformed to surface reflectance, corrected for sensor smile (1-3 nm shift in VNIR and SWIR), and post-processed to remove residual errors. Finally, geometric distortions and relief displacement effects were corrected using a digital elevation model. The MIOP fraction map was extracted using CLSMA considering the entire spectral range (427-2355 nm), and validated by reference to the ground truth map generated by Kriging. The obtained results show the promising potential of the proposed methodology for the detection and mapping of mine iron oxide pollution in the soil.

Keywords: hyperion eo-1, hyperspectral, mine iron oxide pollution, environmental impact, unmixing

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Authors: Damiano Omari, Topirian Kerempe, Dibo Sama, Walter Wafula, Sharon Chepkoech, Chrispine Juma, Gilbert Kirui, Simon Mburu, Susan Keino

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The One Health concept was officially adopted by the international organizations and scholarly bodies in 1984. It aims at combining human, animal and environmental components to address global health challenges. Using collaborative efforts optimal health to people, animals, and the environment can be achieved. One health approach plays a significant approach role in prevention and control of zoonosis diseases. It has also been noted that 75% of new emerging human infectious diseases are zoonotic. In Kenya, one health has been embraced and strongly advocated for by One Health East and Central Africa (OHCEA). It was inaugurated on 17th of October 2010 at a historic meeting facilitated by USAID with participants from 7 public health schools, seven faculties of veterinary medicine in Eastern Africa and 2 American universities (Tufts and University of Minnesota) in addition to respond project staff. The study was conducted in Loitoktok Sub County, specifically in the Amboseli Ecosystem. The Amboseli ecosystem covers an area of 5,700 square kilometers and stretches between Mt. Kilimanjaro, Chyulu Hills, Tsavo West National park and the Kenya/Tanzania border. The area is arid to semi-arid and is more suitable for pastoralism with a high potential for conservation of wildlife and tourism enterprises. The ecosystem consists of the Amboseli National Park, which is surrounded by six group ranches which include Kimana, Olgulului, Selengei, Mbirikani, Kuku and Rombo in Loitoktok District. The Manyatta of study was Osiram Cultural Manyatta in Mbirikani group ranch. Apart from visiting the Manyatta, we also visited the sub-county hospital, slaughter slab, forest service, Kimana market, and the Amboseli National Park. The aim of the study was to identify the one health issues facing the community. This was done by a conducting a community needs assessment and prioritization. Different methods were used in data collection for the qualitative and numerical data. They include among others; key informant interviews and focus group discussions. We also guided the community members in drawing their Resource Map this helped identify the major resources in their land and also help them identify some of the issues they were facing. Matrix piling, root cause analysis, and force field analysis tools were used to establish the one health related priority issues facing community members. Skits were also used to present to the community interventions to the major one health issues. Some of the prioritized needs among the community were water scarcity and inadequate markets for their beadwork. The group intervened on the various needs of the Manyatta. For water scarcity, we educated the community on water harvesting methods using gutters as well as proper storage by the use of tanks and earth dams. The community was also encouraged to recycle and conserve water. To improve markets; we educated the community to upload their products online, a page was opened for them and uploading the photos was demonstrated to them. They were also encouraged to be innovative to attract more clients.

Keywords: Amboseli ecosystem, community interventions, community needs assessment and prioritization, one health issues

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Authors: Dionyssia Lyra, Shoaib Ismail

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Salinization of natural resources constitutes a significant component of the degradation force that leads to depletion of productive lands and fresh water reserves. The global extent of salt-affected soils is approximately 7% of the earth’s land surface and is expanding. The problems of excessive salt accumulation are most widespread in coastal, arid and semi-arid regions, where agricultural production is substantially hindered. The use of crops that can withstand high saline conditions is extremely interesting in such a context. Salt-loving plants or else ‘halophytes’ thrive when grown in hostile saline conditions, where traditional crops cannot survive. Salicornia bigelovii, a halophytic crop with multiple uses (vegetable, forage, biofuel), has demonstrated remarkable adaptability to harsh climatic conditions prevailing in dry areas with great potential for its expansion. Since 2011, the International Center for Biosaline Agriculture (ICBA) with Masdar Institute (MI) and King Abdul Aziz University of Science & Technology (KAUST) to look into the potential for growing S. bigelovii under hot and dry conditions. Through the projects undertaken, 50 different S. bigelovii genotypes were assessed under high saline conditions. The overall goal was to select the best performing S. bigelovii populations in terms of seed and biomass production for future breeding. Specific objectives included: 1) evaluation of selected S. bigelovii genotypes for various agronomic and growth parameters under field conditions, 2) seed multiplication of S. bigelovii using saline groundwater and 3) acquisition of inbred lines for further breeding. Field trials were conducted for four consecutive years at ICBA headquarters. During the first year, one Salicornia population was evaluated for seed and biomass production at different salinity levels, fertilizer treatments and planting methods. All growth parameters and biomass productivity for the salicornia population showed better performance with optimal biomass production in terms of both salinity level and fertilizer application. During the second year, 46 Salicornia populations (obtained from KAUST and Masdar Institute) were evaluated for 24 growth parameters and treated with groundwater through drip irrigation. The plant material originated from wild collections. Six populations were also assessed for their growth performance under full-strength seawater. Salicornia populations were highly variable for all characteristics under study for both irrigation treatments, indicating that there is a large pool of genetic information available for breeding. Irrigation with the highest level of salinity had a negative impact on the agronomic performance. The maximum seed yield obtained was 2 t/ha at 20 dS/m (groundwater treatment) at 25 cm x 25 cm planting distance. The best performing Salicornia populations for fresh biomass and seed yield were selected for the following season. After continuous selection, the best performing salicornia will be adopted for scaling-up options. Taking into account the results of the production field trials, salicornia expansion will be targeted in coastal areas of the Arabian Peninsula. As a crop with high biofuel and forage potential, its cultivation can improve the livelihood of local farmers.

Keywords: biosaline agriculture, genotypes selection, halophytes, Salicornia bigelovii

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Authors: Eman Ghoneim

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The Arabian deserts include some of the driest areas on Earth. Yet, its landforms reserved a record of past wet climates. During humid phases, the desert was green and contained permanent rivers, inland deltas and lakes. Some of their water would have seeped and replenished the groundwater aquifers. When the wet periods came to an end, several thousand years ago, the entire region transformed into an extended band of desert and its original fluvial surface was totally covered by windblown sand. In this work, radar and thermal infrared images were used to reveal numerous hidden surface/subsurface features. Radar long wavelength has the unique ability to penetrate surface dry sands and uncover buried subsurface terrain. Thermal infrared also proven to be capable of spotting cooler moist areas particularly in hot dry surfaces. Integrating Radarsat images and GIS revealed several previously unknown paleoriver and lake basins in the region. One of these systems, known as the Kufrah, is the largest yet identified river basin in the Eastern Sahara. This river basin, which straddles the border between Egypt and Libya, flowed north parallel to the adjacent Nile River with an extensive drainage area of 235,500 km2 and massive valley width of 30 km in some parts. This river was most probably served as a spillway for an overflow from Megalake Chad to the Mediterranean Sea and, thus, may have acted as a natural water corridor used by human ancestors to migrate northward across the Sahara. The Gilf-Kebir is another large paleoriver system located just east of Kufrah and emanates from the Gilf Plateau in Egypt. Both river systems terminate with vast inland deltas at the southern margin of the Great Sand Sea. The trends of their distributary channels indicate that both rivers drained to a topographic depression that was periodically occupied by a massive lake. During dry climates, the lake dried up and roofed by sand deposits, which is today forming the Great Sand Sea. The enormity of the lake basin provides explanation as to why continuous extraction of groundwater in this area is possible. A similar lake basin, delimited by former shorelines, was detected by radar space data just across the border of Sudan. This lake, called the Northern Darfur Megalake, has a massive size of 30,750 km2. These former lakes and rivers could potentially hold vast reservoirs of groundwater, oil and natural gas at depth. Similar to radar data, thermal infrared images were proven to be useful in detecting potential locations of subsurface water accumulation in desert regions. Analysis of both Aster and daily MODIS thermal channels reveal several subsurface cool moist patches in the sandy desert of the Arabian Peninsula. Analysis indicated that such evaporative cooling anomalies were resulted from the subsurface transmission of the Monsoonal rainfall from the mountains to the adjacent plain. Drilling a number of wells in several locations proved the presence of productive water aquifers confirming the validity of the used data and the adopted approaches for water exploration in dry regions.

Keywords: radarsat, SRTM, MODIS, thermal infrared, near-surface water, ancient rivers, desert, Sahara, Arabian peninsula

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Authors: Marilena Fatigante

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Contemporary psychoanalysis is increasingly acknowledging the existential demands of clients in psychotherapy. A significant aspect of the personal crises that patients face today is often rooted in the difficulty to find meaning in their own existence, even after working through or resolving traumatic memories and experiences. Tracing back to the correspondence between Freud and Romain Rolland (1927), psychoanalysis could not ignore that investigation of the psyche also encompasses the encounter with deep, psycho-sensory experiences, which involve a sense of "being one with the external world as a whole", the well-known “oceanic feeling”, as Rolland posed it. Despite the recognition of Non-ordinary States of Consciousness (NSC) as catalysts for transformation in clinical practice, highlighted by neuroscience and results from psychedelic-assisted therapies, there is few research on how psychoanalytic knowledge can integrate with other treatment traditions. These traditions, commonly rooted in non -Western, unconventional, and non-formal psychological knowledge, emphasize the individual’s innate tendency toward existential integrity and transcendence of self-boundaries. Inspired by an autobiographical account, this paper examines narratives of 12 individuals, who engaged in psychoanalytic therapy and also underwent treatment involving a non-formal helping relationship with an expert guide in consciousness, which included experience of this nature. The guide relies on 35 yrs of experience in Psychological, multidisciplinary studies in Human Sciences and Art, and demonstrates knowledge of many wisdom traditions, ranging from Eastern to Western philosophy, including Psychoanalysis and its development in cultural perspective (e.g, Ethnopsychiatry). Analyses focused primarily on two dimensions that research has identified as central in assessing the degree of treatment “success” in the patients’ narrative accounts of their therapies: agency and coherence, defined respectively as the increase, expressed in language, of the client’s perceived ability to manage his/her own challenges and the capacity, inherent in “narrative” itself as a resource for meaning making (Bruner, 1990), to provide the subject with a sense of unity, endowing his /her life experience with temporal and logical sequentiality. The present study reports that, in all narratives from the participants, agency and coherence are described differently than in “common” psychotherapy narratives. Although the participants consistently identified themselves as responsible agentic subject, the sense of agency derived from the non-conventional guidance pathway is never reduced to a personal, individual accomplishment. Rather, the more a new, fuller sense of “Life” (more than “Self”) develops out of the guidance pathway they engage with the expert guide, the more they “surrender” their own sense of autonomy and self-containment. Something, which Safran (2016) identified as well talking about the sense of surrender and “grace” in psychoanalytic sessions. Secondly, narratives of individuals engaging with the expert guide describe coherence not as repairing or enforcing continuity but as enhancing their ability to navigate dramatic discontinuities, falls, abrupt leaps and passages marked by feelings of loss and bereavement. The paper ultimately explores whether valid criteria can be established to analyze experiences of non-conventional paths of self-evolution. These paths are not opposed or alternative to conventional ones, and should not be simplistically dismissed as exotic or magical.

Keywords: oceanic feeling, non conventional guidance, consciousness, narratives, treatment outcomes

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

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The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

Procedia PDF Downloads 137

Authors: Dimitrios Tzilopoulos, Panagiotis Symeonidis, Michael Loufakis, Dimosthenis Ioannidis, Dimitrios Tzovaras

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The domestic film industry in Greece has traditionally relied heavily on state support. While film productions are crucial for the country's economy, it has not fully capitalized on attracting and promoting foreign productions. The lack of motivation, organized state support for attraction and licensing, and the absence of location scouting have hindered its potential. Although recent legislative changes have addressed the first two of these issues, the development of a comprehensive location database and a search engine that would effectively support location scouting at the pre-production location scouting is still in its early stages. In addition to the expected benefits of the film, television, marketing, and multimedia industries, a location-scouting service platform has the potential to yield significant financial gains locally and nationally. By promoting featured places like cultural and archaeological sites, natural monuments, and attraction points for visitors, it plays a vital role in both cultural promotion and facilitating tourism development. This study introduces LOCATION3, an internet platform revolutionizing film production location management. It interconnects location providers, film crews, and multimedia stakeholders, offering a comprehensive environment for seamless collaboration. The platform's central geodatabase (PostgreSQL) stores each location’s attributes, while web technologies like HTML, JavaScript, CSS, React.js, and Redux power the user-friendly interface. Advanced functionalities, utilizing deep learning models, developed in Python, are integrated via Node.js. Visual data presentation is achieved using the JS Leaflet library, delivering an interactive map experience. LOCATION3 sets a new standard, offering a range of essential features to enhance the management of film production locations. Firstly, it empowers users to effortlessly upload audiovisual material enriched with geospatial and temporal data, such as location coordinates, photographs, videos, 360-degree panoramas, and 3D location models. With the help of cutting-edge deep learning algorithms, the application automatically tags these materials, while users can also manually tag them. Moreover, the application allows users to record locations directly through its user-friendly mobile application. Users can then embark on seamless location searches, employing spatial or descriptive criteria. This intelligent search functionality considers a combination of relevant tags, dominant colors, architectural characteristics, emotional associations, and unique location traits. One of the application's standout features is the ability to explore locations by their visual similarity to other materials, facilitated by a reverse image search. Also, the interactive map serves as both a dynamic display for locations and a versatile filter, adapting to the user's preferences and effortlessly enhancing location searches. To further streamline the process, the application facilitates the creation of location lightboxes, enabling users to efficiently organize and share their content via email. Going above and beyond location management, the platform also provides invaluable liaison, matchmaking, and online marketplace services. This powerful functionality bridges the gap between visual and three-dimensional geospatial material providers, local agencies, film companies, production companies, etc. so that those interested in a specific location can access additional material beyond what is stored on the platform, as well as access production services supporting the functioning and completion of productions in a location (equipment provision, transportation, catering, accommodation, etc.).

Keywords: deep learning models, film industry, geospatial data management, location scouting

Procedia PDF Downloads 71

Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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Authors: Sebastião Milton Pinheiro da Silva, Michele Barbosa da Rocha, Ana Lúcia Fernandes Campos, Miquéias Rildo de Souza Silva

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Water is an essential natural resource for life on Earth. Rivers, lakes, lagoons and dams are the main sources of water storage for human consumption. The costs of extracting and using these water sources are lower than those of exploiting groundwater on transition zones to semi-arid terrains. However, the volume of surface water has decreased over time, with the depletion of first-order drainage and the disappearance of springs, phenomena which are easily observed in the field. Climate change worsens water scarcity, compromising supply and hydric security for rural populations. To minimize the expected impacts, producing and storing water through watershed management planning requires detailed cartographic information on the relief and topography, and updated data on the stage and intensity of catchment basin environmental degradation problems. The cartography available of the Brazilian northeastern territory dates to the 70s, with topographic maps, printed, at a scale of 1:100,000 which does not meet the requirements to execute this project. Exceptionally, there are topographic maps at scales of 1:50,000 and 1:25,000 of some coastal regions in northeastern Brazil. Still, due to scale limitations and outdatedness, they are products of little utility for mapping low-order watersheds drainage and springs. Remote sensing data and geographic information systems can contribute to guiding the process of mapping and environmental recovery by integrating detailed relief and topographic data besides social and other environmental information in the Guajiru River Basin, located on the east coast of Rio Grande do Norte, on the Northeast region of Brazil. This study aimed to recognize and map catchment basin, springs and low-order drainage features along estimating morphometric parameters. Alos PALSAR and Copernicus DEM digital elevation models were evaluated and provided regional drainage features and the watersheds limits extracted with Terraview/Terrahidro 5.0 software. CBERS 4A satellite images with 2 m spatial resolution, processed with ESA SNAP Toolbox, allowed generating land use land cover map of Guajiru River. A Mappir Survey 3 multiespectral camera onboard of a DJI Phantom 4, a Mavic 2 Pro PPK Drone and an X91 GNSS receiver to collect the precised position of selected points were employed to detail mapping. Satellite images enabled a first knowledge approach of watershed areas on a more regional scale, yet very current, and drone images were essential in mapping details of catchment basins. The drone multispectral image mosaics, the digital elevation model, the contour lines and geomorphometric parameters were generated using OpenDroneMap/ODM and QGis softwares. The drone images generated facilitated the location, understanding and mapping of watersheds, recharge areas and first-order ephemeral watercourses on an adequate scale and will be used in the following project’s phases: watershed management planning, recovery and environmental protection of Rio's springs Guajiru. Environmental degradation is being analyzed from the perspective of the availability and quality of surface water supply.

Keywords: imaging, relief, UAV, water

Procedia PDF Downloads 32

Authors: Łukasz Mazur, Kamil Domaradzki, Bartosz Kamecki, Justyna Ignaczak, Sebastian Molin, Aleksander Gil, Tomasz Brylewski

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The rising global power consumption necessitates the development of new energy storage solutions. Prospective technologies include solid oxide electrolyzer cells (SOECs), which convert surplus electrical energy into hydrogen. An electrolyzer cell consists of a porous anode, and cathode, and a dense electrolyte. Power output is increased by connecting cells into stacks using interconnects. Interconnects are currently made from high-chromium ferritic steels – for example, Crofer 22 APU – which exhibit high oxidation resistance and a thermal expansion coefficient that is similar to that of electrode materials. These materials have one disadvantage – their area-specific resistance (ASR) gradually increases due to the formation of a Cr₂O₃ scale on their surface as a result of oxidation. The chromia in the scale also reacts with the water vapor present in the reaction media, forming volatile chromium oxyhydroxides, which in turn react with electrode materials and cause their deterioration. The electrochemical efficiency of SOECs thus decreases. To mitigate this, the interconnect surface can be modified with protective-conducting coatings of spinel or other materials. The high prices of SOEC components -especially the Crofer 22 APU- have prevented their widespread adoption. More inexpensive counterparts, therefore, need to be found, and their properties need to be enhanced to make them viable. Candidates include the Nirosta 4016/1,4016 low-chromium ferritic steel with a chromium content of just 16.3 wt%. This steel's resistance to high-temperature oxidation was improved by depositing Gd₂O₃ nanoparticles on its surface via either dip coating or electrolysis. Modification with CeO₂ or Ce₀.₉Y₀.₁O₂ nanoparticles deposited by means of spray pyrolysis was also tested. These methods were selected because of their low cost and simplicity of application. The aim of this study was to investigate the oxidation kinetics of Nirosta 4016/1,4016 modified using the afore-mentioned methods and to subsequently measure the obtained samples' ASR. The samples were oxidized for 100 h in the air as well as air/H₂O and Ar/H₂/H₂O mixtures at 1073 K. Such conditions reflect those found in the anode and cathode operating space during real-life use of SOECs. Phase and chemical composition and the microstructure of oxidation products were determined using XRD and SEM-EDS. ASR was measured over the range of 623-1073 K using a four-point, two-probe DC technique. The results indicate that the applied nanoparticles improve the oxidation resistance and electrical properties of the studied layered systems. The properties of individual systems varied significantly depending on the applied reaction medium. Gd₂O₃ nanoparticles improved oxidation resistance to a greater degree than either CeO₂ or Ce₀.₉Y₀.₁O₂ nanoparticles. On the other hand, the cerium-containing nanoparticles improved electrical properties regardless of the reaction medium. The ASR values of all surface-modified steel samples were below the 0.1 Ω.cm² threshold set for interconnect materials, which was exceeded in the case of the unmodified reference sample. It can be concluded that the applied modifications increased the oxidation resistance of Nirosta 4016/1.4016 to a level that allows its use as SOEC interconnect material. Acknowledgments: Funding of Research project supported by program "Excellence initiative – research university" for the AGH University of Krakow" is gratefully acknowledged (TB).

Keywords: cerium oxide, ferritic stainless steel, gadolinium oxide, interconnect, SOEC

Procedia PDF Downloads 87

Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

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As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

Procedia PDF Downloads 116

Authors: Hooshag Asadi Haroni, Maryam Veiskarami, Yongjun Lu

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The Dalli gold-rich porphyry deposit (17 Mt @ 0.5% Cu and 0.65 g/t Au) is located in the Urumieh-Dokhtar Magmatic Arc (UDMA), a small segment of the Tethyan metallogenic belt, hosting several porphyry Cu (Mo-Au) systems in Iran. This research characterizes the Dalli deposit to define exploration criteria in advanced exploration such as the drilling of possible blind porphyry centers. Geological map, trench/drill hole geochemical and ground magnetic data, and age dating and isotope trace element analyses, carried out at the John De Laeter Research Center of Curtin University, were used to characterize the Delli deposit. Mineralization at Dalli is hosted by NE-trending quartz-diorite porphyry stocks (~ 200m in diameter) intruded by a wall-rock andesite porphyry. Disseminated and stockwork Cu-Au mineralization is related to potassic alteration, comprising magnetite, late K-feldspar and biotite, and quartz-sericite-specularite overprint, surrounded by extensive barren argillic and propylitic alterations. In the peripheries of the porphyry centers, there are N-trending vuggy quartz veins, hosting epithermal Au-Ag-As-Sb mineralization. Geochemical analyses of drill core samples showed that the core of the porphyry stocks is low-grade, whereas the high-grade disseminated and stockwork mineralization (~ 1% Cu and ~ 1.2 g/t Au) occurred at the contact of the porphyry stocks and andesite porphyry. Geochemical studies of the drill hole and trench samples showed a strong correlation between Cu and Au and both show a second-order correlation with Fe and As. Magnetic survey revealed two significant magnetic anomalies, associated with intensive potassic alteration, in the reduced-to-the-pole magnetic map of the area. A relatively weaker magnetic anomaly, showing no surface porphyry expressions, is located on a lithocap, consisting of advanced argillic alteration, vuggy quartz veins, and surface expressions of epithermal geochemical signatures. The association of the lithocap and the weak magnetic anomaly could be indicative of a hidden mineralized porphyry center. Litho-geochemical analyses of the least altered Dalli intrusions and volcanic rocks indicated high Sr/Y (49-61) and Eu/Eu* (0.89-0.92), features typical of Cu porphyries. The U-Pb dating of zircons of the mineralized quartz diorite and andesite porphyry, carried out by laser ablation inductively coupled plasma mass spectrometry, yielded magmatic crystallization ages of 15.4-16.0 Ma (Middle Miocene). The zircon trace element concentrations of Dalli are characterized by high Eu/Eu* (0.3-0.8), (Ce/Nd)/Y (0.01-0.3), and 10000*(Eu/Eu*)/Y (2-15) ratios, similar to fertile porphyry suites such as the giant Sar-Cheshmeh and Qulong porphyry Cu deposits along the Tethyan belt. This suggests that the Middle Miocene Dalli intrusions are fertile and require extensive deep drillings to define their potential. Chondrite-normalized rare earth element (REE) patterns show no significant Eu anomalies, and are characterized by light-REE enrichments (La/Sm)n = 2.57–6.40). In normalized multi-element diagrams, analyzed rocks are characterized by enrichments in large ion lithophile elements (LILE) and depletions in high field strength elements (HFSE), and display typical features of subduction-related calc-alkaline magmas. The characteristics of the Dalli deposit provided several recognition criteria for detailed exploration of Cu-Au porphyry deposits and highlighted the importance of the UDMA as a potentially significant, economically important, but relatively underexplored porphyry province.

Keywords: porphyry, gold, geochronology, magnetic, exploration

Procedia PDF Downloads 63

Authors: Sireetorn Kuharat, Anwar Beg

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Motivation- Solar energy constitutes the most promising renewable energy source on earth. Nanofluids are a very successful family of engineered fluids, which contain well-dispersed nanoparticles suspended in a stable base fluid. The presence of metallic nanoparticles (e.g. gold, silver, copper, aluminum etc) significantly improves the thermo-physical properties of the host fluid and generally results in a considerable boost in thermal conductivity, density, and viscosity of nanofluid compared with the original base (host) fluid. This modification in fundamental thermal properties has profound implications in influencing the convective heat transfer process in solar collectors. The potential for improving solar collector direct absorber efficiency is immense and to gain a deeper insight into the impact of different metallic nanoparticles on efficiency and temperature enhancement, in the present work, we describe recent computational fluid dynamics simulations of an annular solar collector system. The present work studies several different metallic nano-particles and compares their performance. Methodologies- A numerical study of convective heat transfer in an annular pipe solar collector system is conducted. The inner tube contains pure water and the annular region contains nanofluid. Three-dimensional steady-state incompressible laminar flow comprising water- (and other) based nanofluid containing a variety of metallic nanoparticles (copper oxide, aluminum oxide, and titanium oxide nanoparticles) is examined. The Tiwari-Das model is deployed for which thermal conductivity, specific heat capacity and viscosity of the nanofluid suspensions is evaluated as a function of solid nano-particle volume fraction. Radiative heat transfer is also incorporated using the ANSYS solar flux and Rosseland radiative models. The ANSYS FLUENT finite volume code (version 18.1) is employed to simulate the thermo-fluid characteristics via the SIMPLE algorithm. Mesh-independence tests are conducted. Validation of the simulations is also performed with a computational Harlow-Welch MAC (Marker and Cell) finite difference method and excellent correlation achieved. The influence of volume fraction on temperature, velocity, pressure contours is computed and visualized. Main findings- The best overall performance is achieved with copper oxide nanoparticles. Thermal enhancement is generally maximized when water is utilized as the base fluid, although in certain cases ethylene glycol also performs very efficiently. Increasing nanoparticle solid volume fraction elevates temperatures although the effects are less prominent in aluminum and titanium oxide nanofluids. Significant improvement in temperature distributions is achieved with copper oxide nanofluid and this is attributed to the superior thermal conductivity of copper compared to other metallic nano-particles studied. Important fluid dynamic characteristics are also visualized including circulation and temperature shoots near the upper region of the annulus. Radiative flux is observed to enhance temperatures significantly via energization of the nanofluid although again the best elevation in performance is attained consistently with copper oxide. Conclusions-The current study generalizes previous investigations by considering multiple metallic nano-particles and furthermore provides a good benchmark against which to calibrate experimental tests on a new solar collector configuration currently being designed at Salford University. Important insights into the thermal conductivity and viscosity with metallic nano-particles is also provided in detail. The analysis is also extendable to other metallic nano-particles including gold and zinc.

Keywords: heat transfer, annular nanofluid solar collector, ANSYS FLUENT, metallic nanoparticles

Procedia PDF Downloads 143