Search results for: hydraulic connectivity

Authors: Yury S. Shpanskiy, Boris V. Kuteev

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Development of a fusion-fission hybrid facility based on superconducting conventional tokamak DEMO-FNS runs in Russia since 2013. The main design goal is to reach the technical feasibility and outline prospects of industrial hybrid technologies providing the production of neutrons, fuel nuclides, tritium, high-temperature heat, electricity and subcritical transmutation in Fusion-Fission Hybrid Systems. The facility should operate in a steady-state mode at the fusion power of 40 MW and fission reactions of 400 MW. Major tokamak parameters are the following: major radius R=3.2 m, minor radius a=1.0 m, elongation 2.1, triangularity 0.5. The design provides the neutron wall loading of ~0.2 MW/m², the lifetime neutron fluence of ~2 MWa/m², with the surface area of the active cores and tritium breeding blanket ~100 m². Core plasma modelling showed that the neutron yield ~10¹⁹ n/s is maximal if the tritium/deuterium density ratio is 1.5-2.3. The design of the electromagnetic system (EMS) defined its basic parameters, accounting for the coils strength and stability, and identified the most problematic nodes in the toroidal field coils and the central solenoid. The EMS generates toroidal, poloidal and correcting magnetic fields necessary for the plasma shaping and confinement inside the vacuum vessel. EMC consists of eighteen superconducting toroidal field coils, eight poloidal field coils, five sections of a central solenoid, correction coils, in-vessel coils for vertical plasma control. Supporting structures, the thermal shield, and the cryostat maintain its operation. EMS operates with the pulse duration of up to 5000 hours at the plasma current up to 5 MA. The vacuum vessel (VV) is an all-welded two-layer toroidal shell placed inside the EMS. The free space between the vessel shells is filled with water and boron steel plates, which form the neutron protection of the EMS. The VV-volume is 265 m³, its mass with manifolds is 1800 tons. The nuclear blanket of DEMO-FNS facility was designed to provide functions of minor actinides transmutation, tritium production and enrichment of spent nuclear fuel. The vertical overloading of the subcritical active cores with MA was chosen as prospective. Analysis of the device neutronics and the hybrid blanket thermal-hydraulic characteristics has been performed for the system with functions covering transmutation of minor actinides, production of tritium and enrichment of spent nuclear fuel. A study of FNS facilities role in the Russian closed nuclear fuel cycle was performed. It showed that during ~100 years of operation three FNS facilities with fission power of 3 GW controlled by fusion neutron source with power of 40 MW can burn 98 tons of minor actinides and 198 tons of Pu-239 can be produced for startup loading of 20 fast reactors. Instead of Pu-239, up to 25 kg of tritium per year may be produced for startup of fusion reactors using blocks with lithium orthosilicate instead of fissile breeder blankets.

Keywords: fusion-fission hybrid system, conventional tokamak, superconducting electromagnetic system, two-layer vacuum vessel, subcritical active cores, nuclear fuel cycle

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Authors: Abhisek Chakrabarty, Subhraprakash Mandal

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Flash flood is one of the catastrophic natural hazards in the mountainous region of India. The recent flood in the Mandakini River in Kedarnath (14-17th June, 2013) is a classic example of flash floods that devastated Uttarakhand by killing thousands of people.The disaster was an integrated effect of high intensityrainfall, sudden breach of Chorabari Lake and very steep topography. Every year in Himalayan Region flash flood occur due to intense rainfall over a short period of time, cloud burst, glacial lake outburst and collapse of artificial check dam that cause high flow of river water. In Sikkim-Derjeeling Himalaya one of the probable flash flood occurrence zone is Teesta Watershed. The Teesta River is a right tributary of the Brahmaputra with draining mountain area of approximately 8600 Sq. km. It originates in the Pauhunri massif (7127 m). The total length of the mountain section of the river amounts to 182 km. The Teesta is characterized by a complex hydrological regime. The river is fed not only by precipitation, but also by melting glaciers and snow as well as groundwater. The present study describes an attempt to model surface runoff in upper Teesta basin, which is directly related to catastrophic flood events, by creating a system based on GIS technology. The main object was to construct a direct unit hydrograph for an excess rainfall by estimating the stream flow response at the outlet of a watershed. Specifically, the methodology was based on the creation of a spatial database in GIS environment and on data editing. Moreover, rainfall time-series data collected from Indian Meteorological Department and they were processed in order to calculate flow time and the runoff volume. Apart from the meteorological data, background data such as topography, drainage network, land cover and geological data were also collected. Clipping the watershed from the entire area and the streamline generation for Teesta watershed were done and cross-sectional profiles plotted across the river at various locations from Aster DEM data using the ERDAS IMAGINE 9.0 and Arc GIS 10.0 software. The analysis of different hydraulic model to detect flash flood probability ware done using HEC-RAS, Flow-2D, HEC-HMS Software, which were of great importance in order to achieve the final result. With an input rainfall intensity above 400 mm per day for three days the flood runoff simulation models shows outbursts of lakes and check dam individually or in combination with run-off causing severe damage to the downstream settlements. Model output shows that 313 Sq. km area were found to be most vulnerable to flash flood includes Melli, Jourthang, Chungthang, and Lachung and 655sq. km. as moderately vulnerable includes Rangpo,Yathang, Dambung,Bardang, Singtam, Teesta Bazarand Thangu Valley. The model was validated by inserting the rain fall data of a flood event took place in August 1968, and 78% of the actual area flooded reflected in the output of the model. Lastly preventive and curative measures were suggested to reduce the losses by probable flash flood event.

Keywords: flash flood, GIS, runoff, simulation model, Teesta river basin

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Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

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Authors: Sanaz Alizadeh, Yves Comeau, Arshath Abdul Rahim, Sunhasis Ghoshal

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The application of silver nanoparticles (AgNPs) in personal care products, various household and industrial products has resulted in an inevitable environmental exposure of such engineered nanoparticles (ENPs). Ag ENPs, released via household and industrial wastes, reach water resource recovery facilities (WRRFs), yet the fate and transport of ENPs in WRRFs and their potential risk in the biological wastewater processes are poorly understood. Accordingly, our main objective was to elucidate the impact of long-term continuous exposure to AgNPs on biological activity of aerobic wastewater biofilm. The fate, transport and toxicity of 10 μg.L-1and 100 μg.L-1 PVP-stabilized AgNPs (50 nm) were evaluated in an attached growth biological treatment process, using lab-scale moving bed bioreactors (MBBRs). Two MBBR systems for organic matter removal were fed with a synthetic influent and operated at a hydraulic retention time (HRT) of 180 min and 60% volumetric filling ratio of Anox-K5 carriers with specific surface area of 800 m2/m3. Both reactors were operated for 85 days after reaching steady state conditions to develop a mature biofilm. The impact of AgNPs on the biological performance of the MBBRs was characterized over a period of 64 days in terms of the filtered biodegradable COD (SCOD) removal efficiency, the biofilm viability and key enzymatic activities (α-glucosidase and protease). The AgNPs were quantitatively characterized using single-particle inductively coupled plasma mass spectroscopy (spICP-MS), determining simultaneously the particle size distribution, particle concentration and dissolved silver content in influent, bioreactor and effluent samples. The generation of reactive oxygen species and the oxidative stress were assessed as the proposed toxicity mechanism of AgNPs. Results indicated that a low concentration of AgNPs (10 μg.L-1) did not significantly affect the SCOD removal efficiency whereas a significant reduction in treatment efficiency (37%) was observed at 100 μg.L-1AgNPs. Neither the viability nor the enzymatic activities of biofilm were affected at 10 μg.L-1AgNPs but a higher concentration of AgNPs induced cell membrane integrity damage resulting in 31% loss of viability and reduced α-glucosidase and protease enzymatic activities by 31% and 29%, respectively, over the 64-day exposure period. The elevated intercellular ROS in biofilm at a higher AgNPs concentration over time was consistent with a reduced biological biofilm performance, confirming the occurrence of a nanoparticle-induced oxidative stress in the heterotrophic biofilm. The spICP-MS analysis demonstrated a decrease in the nanoparticles concentration over the first 25 days, indicating a significant partitioning of AgNPs into the biofilm matrix in both reactors. The concentration of nanoparticles increased in effluent of both reactors after 25 days, however, indicating a decreased retention capacity of AgNPs in biofilm. The observed significant detachment of biofilm also contributed to a higher release of nanoparticles due to cell-wall destabilizing properties of AgNPs as an antimicrobial agent. The removal efficiency of PVP-AgNPs and the biofilm biological responses were a function of nanoparticle concentration and exposure time. This study contributes to a better understanding of the fate and behavior of AgNPs in biological wastewater processes, providing key information that can be used to predict the environmental risks of ENPs in aquatic ecosystems.

Keywords: biofilm, silver nanoparticle, single particle ICP-MS, toxicity, wastewater

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Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Pierre-Andre Mudry, Jean Decaix, Jeremy Schmid, Cesar Papilloud, Cecile Munch-Alligne

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In most of the Swiss Alpine regions, the availability of water resources is usually adequate even in times of drought, as evidenced by the 2003 and 2018 summers. Indeed, important natural stocks are for the moment available in the form of snow and ice, but the situation is likely to change in the future due to global and regional climate change. In addition, alpine mountain regions are areas where climate change will be felt very rapidly and with high intensity. For instance, the ice regime of these regions has already been affected in recent years with a modification of the monthly availability and extreme events of precipitations. The current research, focusing on the municipality of Val de Bagnes, located in the canton of Valais, Switzerland, is part of a project led by the Altis company and achieved in collaboration with WSL, BlueArk Entremont, and HES-SO Valais-Wallis. In this region, water occupies a key position notably for winter and summer tourism. Thus, multiple actors want to apprehend the future needs and availabilities of water, on both the 2050 and 2100 horizons, in order to plan the modifications to the water supply and distribution networks. For those changes to be salient and efficient, a good knowledge of the current water distribution networks is of most importance. In the current case, the water drinking network is well documented, but this is not the case for the irrigation one. Since the water consumption for irrigation is ten times higher than for drinking water, data acquisition on the irrigation network is a major point to determine future scenarios. This paper first presents the instrumentation and simulation of the irrigation network using custom-designed IoT devices, which are coupled with a digital clone simulated to reduce the number of measuring locations. The developed IoT ad-hoc devices are energy-autonomous and can measure flows and pressures using industrial sensors such as calorimetric water flow meters. Measurements are periodically transmitted using the LoRaWAN protocol over a dedicated infrastructure deployed in the municipality. The gathered values can then be visualized in real-time on a dashboard, which also provides historical data for analysis. In a second phase, a digital clone of the irrigation network was modeled using EPANET, a software for water distribution systems that performs extended-period simulations of flows and pressures in pressurized networks composed of reservoirs, pipes, junctions, and sinks. As a preliminary work, only a part of the irrigation network was modelled and validated by comparisons with the measurements. The simulations are carried out by imposing the consumption of water at several locations. The validation is performed by comparing the simulated pressures are different nodes with the measured ones. An accuracy of +/- 15% is observed on most of the nodes, which is acceptable for the operator of the network and demonstrates the validity of the approach. Future steps will focus on the deployment of the measurement devices on the whole network and the complete modelling of the network. Then, scenarios of future consumption will be investigated. Acknowledgment— The authors would like to thank the Swiss Federal Office for Environment (FOEN), the Swiss Federal Office for Agriculture (OFAG) for their financial supports, and ALTIS for the technical support, this project being part of the Swiss Pilot program 'Adaptation aux changements climatiques'.

Keywords: hydraulic digital clone, IoT water monitoring, LoRaWAN water measurements, EPANET, irrigation network

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Authors: Z. A. Al Marhoon, H. S. Al Ramis, C. Teodoriu

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Well-integrity is one of the major elements considered for drilling geothermal, oil, and gas wells. Well-integrity is minimizing the risk of unplanned fluid flow in the well bore throughout the well lifetime. Well integrity is maximized by applying technical concepts along with practical practices and strategic planning. These practices are usually governed by standardization and regulation entities. Practices during well construction can affect the integrity of the seal at the time of abandonment. On the other hand, achieving a perfect barrier system is impracticable due to the needed cost. This results in a needed balance between regulations requirements and practical applications. The guidelines are only effective when they are attainable in practical applications. Various governmental regulations and international standards have different guidelines on what constitutes high-quality isolation from unwanted flow. Each regulating or standardization body differ in requirements based on the abandonment objective. Some regulation account more for the environmental impact, water table contamination, and possible leaks. Other regulation might lean towards driving more economical benefits while achieving an acceptable isolation criteria. The research methodology used in this topic is derived from a literature review method combined with a compare and contrast analysis. The literature review on various zonal isolation regulations and standards has been conducted. A review includes guidelines from NORSOK (Norwegian governing entity), BSEE (USA offshore governing entity), API (American Petroleum Institute) combined with ISO (International Standardization Organization). The compare and contrast analysis is conducted by assessing the objective of each abandonment regulations and standardization. The current state of well barrier regulation is in balancing action. From one side of this balance, the environmental impact and complete zonal isolation is considered. The other side of the scale is practical application and associated cost. Some standards provide a fair amount of details concerning technical requirements and are often flexible with the needed associated cost. These guidelines cover environmental impact with laws that prevent major or disastrous environmental effects of improper sealing of wells. Usually these regulations are concerned with the near future of sealing rather than long-term. Consequently, applying these guidelines become more feasible from a cost point of view to the required plugging entities. On the other hand, other regulation have well integrity procedures and regulations that lean toward more restrictions environmentally with an increased associated cost requirements. The environmental impact is detailed and covered with its entirety, including medium to small environmental impact in barrier installing operations. Clear and precise attention to long-term leakage prevention is present in these regulations. The result of the compare and contrast analysis of the literature showed that there are various objectives that might tip the scale from one side of the balance (cost) to the other (sealing quality) especially in reference to zonal isolation. Furthermore, investing in initial well construction is a crucial part of ensuring safe final well abandonment. The safety and the cost saving at the end of the well life cycle is dependent upon a well-constructed isolation systems at the beginning of the life cycle. Long term studies on zonal isolation using various hydraulic or mechanical materials need to take place to further assess permanently abandoned wells to achieve the desired balance. Well drilling and isolation techniques will be more effective when they are operationally feasible and have reasonable associated cost to aid the local economy.

Keywords: plug and abandon, P&A regulation, P&A standards, international guidelines, gap analysis

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Authors: David A. Olasehinde, Peter I. Olasehinde, Segun M. A. Adelana, Dapo O. Olasehinde

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An investigation was carried out on underground water system dynamics within Ilorin metropolis to monitor the subsurface flow and its corresponding pollution. Africa population growth rate is the highest among the regions of the world, especially in urban areas. A corresponding increase in waste generation and a change in waste composition from predominantly organic to non-organic waste has also been observed. Percolation of leachate from non-engineered landfills, the chief means of waste disposal in many of its cities, constitutes a threat to the underground water bodies. Ilorin city, a transboundary town in southwestern Nigeria, is a ready microcosm of Africa’s unique challenge. In spite of the fact that groundwater is naturally protected from common contaminants such as bacteria as the subsurface provides natural attenuation process, groundwater samples have been noted to however possesses relatively higher dissolved chemical contaminants such as bicarbonate, sodium, and chloride which poses a great threat to environmental receptors and human consumption. The Geographic Information System (GIS) was used as a tool to illustrate, subsurface dynamics and the corresponding pollutant indicators. Forty-four sampling points were selected around known groundwater pollutant, major old dumpsites without landfill liners. The results of the groundwater flow directions and the corresponding contaminant transport were presented using expert geospatial software. The experimental results were subjected to four descriptive statistical analyses, namely: principal component analysis, Pearson correlation analysis, scree plot analysis, and Ward cluster analysis. Regression model was also developed aimed at finding functional relationships that can adequately relate or describe the behaviour of water qualities and the hypothetical factors landfill characteristics that may influence them namely; distance of source of water body from dumpsites, static water level of groundwater, subsurface permeability (inferred from hydraulic gradient), and soil infiltration. The regression equations developed were validated using the graphical approach. Underground water seems to flow from the northern portion of Ilorin metropolis down southwards transporting contaminants. Pollution pattern in the study area generally assumed a bimodal pattern with the major concentration of the chemical pollutants in the underground watershed and the recharge. The correlation between contaminant concentrations and the spread of pollution indicates that areas of lower subsurface permeability display a higher concentration of dissolved chemical content. The principal component analysis showed that conductivity, suspended solids, calcium hardness, total dissolved solids, total coliforms, and coliforms were the chief contaminant indicators in the underground water system in the study area. Pearson correlation revealed a high correlation of electrical conductivity for many parameters analyzed. In the same vein, the regression models suggest that the heavier the molecular weight of a chemical contaminant of a pollutant from a point source, the greater the pollution of the underground water system at a short distance. The study concludes that the associative properties of landfill have a significant effect on groundwater quality in the study area.

Keywords: dumpsite, leachate, groundwater pollution, linear regression, principal component

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Authors: Marcos Perez, Christian Dumont, Olivier Nodin, Sebastien Nouveau

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Nickel superalloys are used to manufacture high-temperature rotary engine parts such as high-pressure disks in gas turbine engines. High strength at high operating temperatures is required due to the levels of stress and heat the disk must withstand. Therefore it is necessary parts made from materials that can maintain mechanical strength at high temperatures whilst remain comparatively low in cost. A manufacturing process referred to as the triple melt process has made the production of cast and wrought (C&W) nickel superalloys possible. This means that the balance of cost and performance at high temperature may be optimized. AD730TM is a newly developed Ni-based superalloy for turbine disk applications, with reported superior service properties around 700°C when compared to Inconel 718 and several other alloys. The cast ingot is converted into billet during either cogging process or open die forging. The semi-finished billet is then further processed into its final geometry by forging, heat treating, and machining. Conventional ingot-to-billet conversion is an expensive and complex operation, requiring a significant amount of steps to break up the coarse as-cast structure and interdendritic regions. Due to the size of conventional ingots, it is difficult to achieve a uniformly high level of strain for recrystallization, resulting in non-recrystallized regions that retain large unrecrystallized grains. Non-uniform grain distributions will also affect the ultrasonic inspectability response, which is used to find defects in the final component. The main aim is to analyze the recrystallization behavior and microstructural evolution of AD730 at subsolvus temperatures from a semi-finished product (billet) under conditions representative of both cogging and hot forging operations. Special attention to the presence of large unrecrystallized grains was paid. Double truncated cones (DTCs) were hot forged at subsolvus temperatures in hydraulic press, followed by air cooling. SEM and EBSD analysis were conducted in the as-received (billet) and the as-forged conditions. AD730 from billet alloy presents a complex microstructure characterized by a mixture of several constituents. Large unrecrystallized grains present a substructure characterized by large misorientation gradients with the formation of medium to high angle boundaries in their interior, especially close to the grain boundaries, denoting inhomogeneous strain distribution. A fine distribution of intragranular precipitates was found in their interior, playing a key role on strain distribution and subsequent recrystallization behaviour during hot forging. Continuous dynamic recrystallization (CDRX) mechanism was found to be operating in the large unrecrystallized grains, promoting the formation intragranular DRX grains and the gradual recrystallization of these grains. Evidences that hetero-epitaxial recrystallization mechanism is operating in AD730 billet material were found. Coherent γ-shells around primary γ’ precipitates were found. However, no significant contribution to the overall recrystallization during hot forging was found. By contrast, strain presents the strongest effect on the microstructural evolution of AD730, increasing the recrystallization fraction and refining the structure. Regions with low level of deformation (ε ≤ 0.6) were translated into large fractions of unrecrystallized structures (strain accumulation). The presence of undissolved secondary γ’ precipitates (pinning effect), prior to hot forging operations, could explain these results.

Keywords: AD730 alloy, continuous dynamic recrystallization, hot forging, γ’ precipitates

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Authors: Swaleh Aboud, Mishal Gudka, David Obura

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Background: Coral reefs are becoming increasingly vulnerable due to several threats ranging from climate change to overfishing. This has resulted in increased management and conservation efforts to protect reefs from degradation and facilitate recovery. Recruitmentof new individuals are isimportant in the recovery process and critical for the persistence of coral reef ecosystems. Local coral community structure can be influenced by successful recruit settlement, survival, and growth Understanding coral recruitment patterns can help quantify reef resilience and connectivity, establish baselines and track changes and evaluate the effectiveness of reef restoration and conservation efforts. This study will examine the abundance and spatial pattern of coral recruits and how this relates to adult community structure, including the distribution of thermal resistance and sensitive genera and their distribution in different management regimes. Methods: Coral recruit and demography surveys were conducted from 2020 to 2022, covering 35 sites in 19coral reef locations along the Kenyan coast. These included marine parks, reserves, community conservation areas (CMAs), and open access areas from the north (Marereni) to the south (Kisite) coast of Kenya and across different reef habitats. The data was collected through the underwater visual census (UVC) technique. We counted adult corals (>10 cm diameter)of23 selected genera using belt transects (25 by 1 m) and sampling of 1 m2 quadrat (at an interval of 5m) for all coloniesless than 10 cm diameter. The benthic cover was collected using photo quadrats. The surveys were only done during the northeast monsoon season. The data wereanalyzed using the R program to see the distribution patterns and the Kruskal Wallis test to see whether there was a significant difference. Spearman correlation was also applied to assess the relationship between the distribution of coral genera in recruits and adults. Results: A total of 44 different coral genera were recorded for recruits, ranging from 3at Marereni to 30at Watamu Marine Reserve. Recruit densities ranged from 1.2±1.5recruit m-2 (mean±SD) at Likoni to 10.3± 8.4 recruit m-2 at Kisite Marine Park. The overall densityof recruitssignificantly differed between reef locations, with Kisite Marine Park and Reserve and Likonihaving significantly large differences from all the other locations, while Vuma, Watamu, Malindi, and Kilifi had significantly lower differences from all the other locations. The recruit generadensity along the Kenya coastwas divided into two clusters, one of which only included sites inKisite Marine Park. Adult colonies were dominated by Porites massive, Acropora, Platygyra, and Favites, whereas recruits were dominated by Porites branching, Porites massive, Galaxea, and Acropora. However, correlation analysis revealed a statistically significant positive correlation (r=0.81, p<0.05) between recruit and adult coral densities across the 23 coral genera. Marereni, which had the lowest densityof recruits, has only thermallyresistant coral genera, while Kisite Marine Park, with the highest recruit densities, has over 90% thermal sensitive coral genera. A weak positive correlation was found between recruit density and coralline algae, dead standing corals, and turf algae, whereas a weak negative correlation was found between recruit density and bare substrate and macroalgae. Between management regimes, marine reserves were found to have more recruits than no-take zones (marine parks and CMAs) and open access areas, although the difference was not significant. Conclusion: There was a statistically significant difference in the density of recruits between different reef locations along the Kenyan coast. Although the dominating genera of adults and recruits were different, there was a strong positive correlation between their coral communities, which could indicate self-recruitment processes or consistent distance seedings (of the same recruit genera). Sites such as Kisite Marine Park, with high recruit densities but dominated by thermally sensitive genera, will, on the other hand, be adversely affected by future thermal stress. This could imply that reducing the threats to coral reefs such as overfishingcould allow for their natural regeneration and recovery.

Keywords: coral recruits, coral adult size-class, cora demography, resilience

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Authors: Mariza Kaskara, Stella Girtsou, Maria Prodromou, Alexia Tsouni, Christodoulos Mettas, Stavroula Alatza, Kyriaki Fotiou, Marios Tzouvaras, Charalampos Kontoes, Diofantos Hadjimitsis

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Natural hazard assessment and monitoring are crucial components in managing the risks associated with fires, floods, and geohazards, particularly in regions prone to these natural disasters, such as Greece and Cyprus. Recent advancements in technology led to the development of state-of-the-art systems for assessing and monitoring these hazards. These technologies, developed by the BEYOND Center of Excellence of the National Observatory of Athens, have been successfully applied in Greece and are now set to be transferred to Cyprus. The implementation of these advanced technologies in Greece has significantly improved the country's ability to respond to these natural hazards. Enhancing disaster resilience is crucial as it significantly improves our ability to predict, prepare for, and mitigate the impacts of natural disasters, ultimately saving lives and reducing economic losses. For wildfire risk assessment, a scalar wildfire occurrence risk index has been created based on the predictions of machine learning models. Our objective was to train an ML model that learns to derive a fire susceptibility score when given as input a vector of features assigned to certain spatiotemporal coordinates. Predicting fire danger is crucial for the sustainable management of forest fires as it provides essential information for designing effective prevention measures and facilitating response planning for potential fire incidents. For flood risk assessment, a multi-faceted approach has been employed, including the application of remote sensing techniques, the collection and processing of data from population, buildings, technical studies and field visits, as well as hydrological and hydraulic simulations. All input data are used to create precise flood hazard maps according to various flooding scenarios, detailed flood vulnerability and flood exposure maps, which finally produce the flood risk map. Critical points are identified, and mitigation measures are proposed for the worst-case scenario, namely, refuge areas are defined, and escape routes are designed. Flood risk maps can assist in raising awareness and save lives. For geohazards monitoring (e.g., landslides, subsidence), synthetic aperture radar (SAR) and optical satellite imagery have been combined with geomorphological and meteorological data and other landslide/ground deformation contributing factors. To monitor critical infrastructures, including dams, advanced InSAR (Interferometric SAR) methodologies are used for identifying surface movements through time. Monitoring these hazards provides valuable information for understanding processes and could lead to early warning systems to protect people and infrastructure. The success of these systems in Greece has paved the way for their transfer to Cyprus to enhance Cyprus's capabilities in natural hazard assessment and monitoring. This transfer is being made through knowledge transfer activities, fostering continuous collaboration between Greek and Cypriot experts. Furthermore, small demonstration actions are implemented to showcase the effectiveness of these technologies in real-world scenarios. In conclusion, the transfer of advanced natural hazard assessment technologies from Greece to Cyprus represents a significant step forward in enhancing the entire region's resilience to disasters. The EXCELSIOR project, funding this opportunity, is committed to empowering Cyprus with the tools and expertise needed to effectively manage and mitigate the risks associated with these natural hazards. Acknowledgment: Authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project.

Keywords: earth observation, monitoring, natural hazards, remote sensing

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