Maximum Time Research Articles

Numerical method determining the time-dependent position of a minority phase sphere in the Fe-Cu alloy droplet

Abstract A numerical method was developed to track the dynamic positions of the L2 phase sphere inside the Fe-Cu alloy droplet. Firstly, the temperature field distribution within alloy droplet was calculated, and the variation in thermal gradient was analyzed. Secondly, the migration behavior of the sphere was analyzed based on Marangoni convection. Finally, the theoretical position of the 10 μm sphere was determined. The results demonstrated that there is a little difference in temperature between the center and the surface of the droplet, but its gradient is very different. Moreover, the maximum migration times for the L2 phase sphere were determined to be ~0.02 s, 0.07 s, and 0.14 s within 300μm, 600μm, and 900μm alloy droplets, respectively. In addition, it was also found that the same-sized spheres can reach the same relative position, i.e., 0.485R. This means the final position of the sphere within the different alloy droplets is independent of the droplet size.

Heat–power decoupling for the CHP unit by utilizing heat storage in the district heating system integrated with heat pumps: Dynamic modeling and performance analysis

Heat–power decoupling is a key issue to be addressed for the combined heat and power (CHP) unit to enhance its operational flexibility, and utilizing heat storage in district heating systems represents a viable approach. The widespread adoption of heat pumps to boost heating network also increases the complexity of managing heat storage, and the quantitative impact of heat storage has significant implications during operation. To this end, dynamic models of heating networks and heat pumps were developed. A metric, the maximum maintenance time, was established to quantitatively assess heat storage utilization. Dynamic simulations and performance analyses were conducted on a 330 MW CHP unit. The results indicate that by employing heat storage, the feasible maximum and minimum output power of the heating system can be increased by 20 MW and decreased by 45.5 MW, respectively. With the integration of a heat pump, these values can further increase by 9 MW and decrease by 158 MW, respectively, significantly enhancing the operational flexibility of CHP unit.

Detraining's Effects on Cardiorespiratory Fitness and Maximal and Explosive Strength in Army Soldiers: Does Age Matter?

This study investigated the impact of four weeks of age-dependent detraining on army soldiers' cardiorespiratory fitness and maximal and explosive strength. Fourteen volunteer tactical athletes participated, divided into two age groups (20 to 29 and 30 to 40 years). Before and after the detraining period, we assessed their anthropometric measurements (weight, height, body mass index, fat mass, and fat-free mass), cardiorespiratory fitness (maximal oxygen uptake [VO2max] and ventilatory thresholds [VT1 and VT2]), and kinematic properties during a single-leg counter-moving jump (CMJ) test for both the dominant and non-dominant legs. Two-way ANOVA followed by the Holm-Sidak post hoc test was used. The anthropometric and cardiovascular variables did not show significant differences between the groups. However, both groups exhibited a significantly reduced maximum time and speed at the VO2max. Furthermore, the flight time and maximum height during the CMJ significantly decreased in the non-dominant leg for both age groups. Notably, the dominant leg's concentric impulse (CI) significantly reduced during the CMJ, but this effect was observed only in the 30-40 age group. There were significant differences between the two age groups. Our findings suggest that four weeks of detraining negatively impacts aerobic fitness and muscular strength, independently of age. However, the dominant leg may be more susceptible to detraining effects in army soldiers aged 30-40. Furthermore, as a perspective, our results strongly suggest that a detraining period could affect successful missions (aerobic performance deterioration), as well as promote a muscle imbalance between the legs, which could encourage muscle injuries and endanger combat missions.

Enabling Space-Based Computed Cloud Tomography with a Mixed Integer Linear Programming Scheduler

Cumuliform clouds in Earth’s lower atmosphere play important roles in the radiative balance and hydrological cycle of the climate system. Yet key processes unfolding in these clouds, such as aerosol interactions and precipitation initiation, are still poorly understood. Current space-based cloud observation methods are inadequate for inferring the internal structure of clouds outside of a narrow transect that is probed actively by radar and lidar. Cloud tomography is an emerging technique that uses passive imaging of a cloud target from multiple locations with a large angular range to infer internal cloud structure. Many low convective clouds only have a lifetime of 15–25 min, necessitating autonomous scheduling of observation targets as they appear. Onboard autonomous scheduling is formulated as a mixed-integer optimization problem (MILP) with a finite time horizon and a reward scheme designed to maximize the angular range of the observations. A finite time horizon MILP scheduler is well suited to this mission because the short lifetime of low convective clouds creates a natural time horizon. This MILP can solve for an optimal observation schedule in a maximum time of 15 ms on a desktop CPU. The MILP scheduler is able to observe nearly 60% more targets than a conventional push-broom camera configuration. This initial result is promising and demonstrates the need for continued research in this area.

Workshop Response Time at the Emergency Room Lubuk Pakam Health Center

Higher level of achievement of the community in the local area, this is also a service in the area which is a world-class public and individual service, at the same time prioritized in promotion and prevention efforts. Decree of the Minister of Health Number 129 of 2008 concerning Minimum Service Standards in Emergency Installations, Response Time, also known as "emergency service response time", is the time needed by patients from the time they arrive at the Emergency Installation until they are given first aid in minutes. The maximum response time is five minutes. The results of the study showed that the number of qualified nurses, the availability of medical equipment, and emergency room employees are the main factors affecting response time. An important factor in evaluating the quality of health services is patient satisfaction, which is measured by how patients act after receiving health services. Patient satisfaction also depends on how well the service offers patient expectations. Patient service has a significant impact on patient satisfaction and is an important component in the Puskesmas system that must always be evaluated. The experience and ability of a doctor in handling emergency patients quickly and accurately correlates with patient satisfaction. Patients who receive good health services will indirectly promote and recommend the health facility to their families.

PERANCANGAN DAN IMPLEMENTASI JARINGAN FTTH GPON DI CLUSTER GILIMANUK

This research aims to meet the target of building a homepass network of 512 homepasses from PT. PLN ICON PLUS in the North Bali UP3 area sector, namely the Gilimanuk Village area, Melaya District, Jembrana and the use of Huawei Optical Line Terminal (OLT) equipment with a total of 8 ports as well as the use of backbone network access that is already available in the Gilimanuk area. Gilimanuk demographically has an area of 56.01 km2 and consists of residential buildings inhabited by 2,451 families. To accommodate homepass from the Gilimanuk housing complex, this research offers a cascading scheme for Fiber To The Home (FTTH) with Gigabit Passive Optical Network (GPON) technology that is appropriate to use but still pays attention to the quality of the network provided. In determining the feasibility of the network design and determining the appropriate cascading scheme for the Gilimanuk Cluster, the parameters in network design and implementation are focused on measuring the power link budget in theory and implementation, then the rise time budget value in the network optisystem software simulation. The results of this research show that the 1:4 to 1:16 cascading scheme has better FTTH network system feasibility than the 1:8 to 1:8 cascading scheme with a Prx value of -18.42 dBm, which does not exceed the minimum Prx threshold value of the ITU-T G standard. 984, namely -28 dBm, then the rise time budget shows the system rise time value: 0.25537 ns, which does not exceed the maximum rise time limit, namely 0.292 ns, so the 1:4 to 1:16 cascading scheme is feasible to implement.

Deep Learning Models for Accurate Diagnosis and Detection of Bone Pathologies: A Comprehensive Analysis and Research Challenges

The presence of bone disease has been observed to have a substantial influence on an individual's overall health. There are conventional techniques to detect as well as diagnose them but they often suffer limitations in the form of misdiagnosis because of manual error as well as maximum time consumption. Therefore, it is of utmost importance to accurately and proficiently identify it by integrating conventional methods with advanced artificial intelligence techniques. The objective of this study is to conduct a comprehensive analysis of the present state of research concerning the identification and diagnosis of bone disease using machine learning and deep learning. A review is conducted in accordance with the PRISMA guidelines which focus on the examination of scholarly articles published within the timeframe of 2019 to 2024. This review analyzes peer-reviewed literature and research findings to show how machine and deep learning can improve bone disease diagnosis accuracy. It has been found that in the case of osteoporosis, the highest recall, precision, and F1 score is computed by random forest with 93%, 94%, and 93%, respectively while as advanced CNN technique computed 98% accuracy for osteoporosis and 98.4% accuracy, 95% sensitivity as well as 97% specificity for osteonecrosis. Likewise, for bone tumor and osteoarthritis, AlexNet achieved 98% and 98.90% accuracy, respectively. The study introduces a novel approach to the diagnosis of bone diseases by emphasizing the usage of advanced learning techniques over conventional methods. Additionally, the paper highlights the significance of analyzing the clinical or imaging data and extracting features to improve image quality and provide a pathway toward more accurate and efficient diagnosis of bone diseases. By delving into these techniques, the paper offers valuable insights into enhancing diagnostic capabilities for bone diseases, which ultimately leads to improved patient care and treatment outcomes.

Optimal algorithms for solving green online reheat furnace scheduling problems with deterioration effect

Optimizing reheating furnace scheduling in terms of energy saving and reheating time reduction is a vital component in improving competitive advantage of the steel enterprises. However, current reheating furnace scheduling models are still limited since (1) most of the scheduling problems involving reheating furnace suppose that the steel orders and their information are known in advance and (2) the reheating time of a slab in reheating operation is a constant in the majority of current reheating furnace scheduling models. To address these issues, three online reheat furnace scheduling models with deterioration effect are proposed in order to minimize the maximum residence time, the maximum energy consumption as well as total energy consumption of all slabs in reheating operation, respectively. Furthermore, for these online scheduling problems, deterministic online algorithms are presented and shown to be optimal, respectively. In addition, the computational experiments confirm that the three online algorithms developed in this paper are particularly efficient and effective in practice.

Rainfall impacts on urban route choices by private vehicle users: insights from São Paulo, Brazil

Urban drivers frequently experience challenges posed by adverse weather conditions like heavy rain. Despite the influence of these conditions on individual travel behaviour, there is limited understanding of how various aspects of rainfall affect the route choices in urban trips. In this context, this paper aims to evaluate the impacts of different rainfall conditions on the route choice behaviour of private vehicle users. We propose a method to identify the specific routes taken by drivers, utilizing observed trips reproduced from a large-scale dataset containing license plate information recognized by speed device cameras. Path Size Multinomial Logit models penalizing routes that share common links were estimated based on a choice set comprised of routes with a maximum similarity threshold. Distance and the actual travel times in the routes were estimated using real-world data from a third-party company, and cumulative, average and maximum rainfall through each route of the choice set were obtained from data captured by meteorological radar. A case study in the city of São Paulo, Brazil, considered the average and maximum rainfall intensities, distance, and travel time in different models. The results indicate that both average and maximum rainfall intensities negatively impact the utility of routes. This research enables the identification of routes with the highest probabilities of being chosen during intense rainfall. Such information is valuable for implementing measures to minimize the impacts caused by adverse weather conditions in urban trips.

The successful use of rituximab in IgA nephropathy patients with podocytopathy: a case series.

Immunoglobulin A nephropathy (IgAN) with podocytopathy is a rare pathological type of glomerular disease. The use of rituximab (RTX) in the treatment of glomerular diseases has increased in recent decades, but the efficacy of RTX in the treatment of patients with IgAN and podocytopathy has rarely been reported. This was a single-centre retrospective study of IgAN patients with podocytopathy who were treated with RTX as second-line therapy was conducted at our centre from 2019 to 2022. The aim of this study was to investigate the efficacy and safety of RTX in IgAN patients with podocytopathy. Seven out of eight patients met the criteria for complete remission following RTX therapy. Only one patient experienced adverse events (infectious diarrhoea and pulmonary infection) and experienced relapse 6 months after RTX therapy. The maximum relapse-free time after RTX therapy was 20 months, while the maximum relapse-free time before RTX therapy was only 6 months. The number of relapses before RTX therapy (per year) was one to four; moreover, seven patients did not relapse and maintained remission at the last follow-up despite steroid withdrawal after RTX therapy. Overall, RTX effectively reduced proteinuria, increased the maximum relapse-free time, reduced the number of relapses per year and helped patients stop steroid use as soon as possible. RTX also helped most patients achieve clinical remission. RTX appears to be an effective and safe alternative for treating IgAN patients with podocytopathy with steroid dependence or frequent relapse.

Persistency of horse habituation to distracting sounds

Habituation indicates a decrement in response to a specific stimulus by repeated exposure to that stimulus. Responding to or ignoring sound stimuli, which are common background distractors, is important for the undisturbed functioning of the organism, efficient animal management and safe handling. We habituated 20 warmblood horses to a set of distracting sounds and assessed the possibility of reversing this process through simple modifications in sound playback. The study involved three stages: habituation (Stage 1) and two trials of dishabituation (Stage 2, 3). In Stage 1, five different sounds of animals, each on a separate day, were repeatedly (every 20 minutes (min)) played during a stay on an experimental paddock. The sounds were selected out of 40 sounds of different origin based on their distracting effect on the horses (e.g., interruption of previous activity, increase in emotional arousal) during the first exposure to them three months earlier. In Stage 2, four new and unknown sounds (futuristic characteristics) were additionally introduced to the set of habituated sounds, whereas in Stage 3, habituated sounds (from Stage 1) were played from an altered location. Behavioral (e.g., disruption of feeding, duration of feeding, locomotion and standing alert) and cardiac (heart rate and heart rate variability) variables were assessed. Generally, horses quickly habituated to the initially distracting sounds, but great variability was observed in the number of needed playbacks (1–7) for each horse. After completion of Stage 1, the horses responded with an increase in vigilance, locomotion, refeeding frequency and a 1-minute increase in mean heart rate to novel but not to known sounds. None of the modifications resulted in a recovery of previously habituated reactions. After introduction of playback modifications, only maximum heart rate (in Stage 2, Stage 3) and time of standing alert (in Stage 3) increased after re-exposure to sounds horses had been habituated to, suggesting some level of vigilance. However, this response was too weak to conclude about dishabituation. The results of the study confirm sound recognition and the fast and persistent audio habituation in horses.

Cooperative path planning study of distributed multi-mobile robots based on optimised ACO algorithm

The rapid development of robotics technology has driven the growth of robot types and the development of related technologies. As an important aspect of robot research, path planning technology plays an irreplaceable role in practical production and application. Ant colony algorithm has a wide range of applications in robot path planning, but there is also a problem of performance overly relying on initial parameter selection. In order to solve this problem and improve the performance of mobile robot path planning, an improved ant colony algorithm based on firefly algorithm was studied and designed in a two-dimensional environment. In order to further explore the performance of ant colony algorithm in solving robot coordinated path planning problems, an improved ant colony algorithm based on heuristic function was also designed. In a three-dimensional environment, an improved ant colony algorithm based on the improved artificial potential field method was designed. The research results show that the maximum running time of the improved ant colony algorithm based on the firefly algorithm in different grid environments is 819.36 s, 847.01 s, and 811.54 s, respectively. The average running time of the improved ant colony algorithm based on heuristic function in different grid environments is 5.19 s, 5.97 s, and 9.09 s, with average path lengths of 29.90 cm, 31.08 cm, and 37.01 cm, and path length variances of 0.35, 0.87, and 2.21, respectively. The ant colony algorithm based on the improved artificial potential field method has a running time of 1.930 s, 3.182 s, and 4.662 s in different grid environments, and a path length of 29.275 cm, 49.447 cm, and 67.057 cm, respectively. The ant colony algorithm for research and design optimization has good performance. The contribution of the research lies in the design of three path planning methods for mobile robots, including two-dimensional path planning and three-dimensional path planning, which improves the time of path planning and shortens the average path length. The novelty of the research is reflected in the design of a path planning method for mobile robots in two-dimensional and three-dimensional environments, which improves the ant colony algorithm through firefly algorithm and heuristic function, and combines the ant colony algorithm with the improved artificial potential field method. The method designed by the research institute can provide technical support for path planning of mobile robots.

DEVELOPMENT AND ASSESSMENT OF MANUAL AND AUTOMATED PID CONTROLLERS FOR THE OPTIMUM PRODUCTION OF ETHYLENE GLYCOL IN A CSTR

Industrially, one of the techniques used to enhance the optimum production of petrochemicals is the configuration of process control units such as gas chromatography (G.C. Analyzer) for concentration and thermocouple for temperature in the production system. This research focused on the application of the principles of mass and energy conservation in the development of dynamic or unsteady state models for predicting the behaviour of the system or process involved in the production of ethylene glycol from a reaction involving oxidation of ethylene-to-ethylene oxide which further undergoes hydrolysis to produce ethylene glycol in a continuous stirred tank reactor (CSTR). The high mathematical complexities of the mass and energy balance models of the Process as a result of the reaction kinetic scheme of the non-elementary reaction of the process which integrated both linear and non-linear terms into the models were resolved by the application of the principles of Taylor’s series expansion, Laplace Transform, partial fraction and matrix in the development of the dynamic models. Process simulation tool (Simulink) was utilized in the configuration of closed-loop systems with thermocouple and G. C. Analyzer, at the feed point of the reactor for process variables (temperature and concentration) control during the process using proportional, integral and derivative (PID) as controller parameters. The results of the process behaviour showed that manual tuning of different controller parameters experienced a high level of fluctuations and would not attain its stability or steady state even at a processing time above 16 seconds. Whereas, automatic tuning of desired controller gains of 1.361, 1.056 and 0.4109 for K P, K I and K D for temperature and pressure with a tuning time of 143.9 Seconds, requires a maximum time of 8 seconds for the system to attain stability. This study showed that automated tuning of the controller resulted in better performance characteristics for optimum production of ethylene glycol in a non-isotheral continuous stirred tank reactor within the shortest possible time.

Maxima Times of Pulsating Variables Obtained in 2023-2024

We present 17 times of maxima of 10 delta Scuti type pulsating variables obtained with the IST40 telescope of the Istanbul University Observatory between May 2023 - May 2024.

Scheduling of twin automatic stacking cranes and automated guided vehicle considering buffer mode on automated container terminal

To improve the efficiency of automatic stacking crane (ASC) and automated guided vehicle (AGV) scheduling in synchronized import and export mode at automated container terminal (ACT), with the objective of minimizing the maximum ASC completion time and AGV wait time, a twin ASCs and AGV scheduling model is established, which considers both the size of handshake area and buffer, and the location constraints of handshake area. Longest transport time priority (LTTP) and traversal priority (TP) heuristics strategies are designed to adjust the execution order of ASCs to reduce the wait time of ASCs. Based on the comprehensive learning particle swarm optimization algorithm (CLPSO), the discrete coding CLPSO algorithm (CLDPSO) is developed by designed permutation coding for ASC execution order and integer coding for AGV numbering, and the convergence speed is improved by dynamically adjusting the weight parameters. The experimental results show that increasing the handshake area and buffer size can reduce the fitness value by 3.64 % and 5.58 % on average respectively, the selected optimal handshake area location can reduce the fitness value by 3.51 % on average compared with the conventional location, the TP strategy can reduce the waiting time of ASC by up to 16.89 %. Compared to the PSO and DPSO algorithms, the fitness value of CLDPSO can reduce the fitness value by 13.83 % and 7.80 %, and the computation time is reduced by 10.67 % and 7.43 % on average, respectively.

Fouling and energy consumption impede electrochemical disinfection of constructed wetland effluents

Electrochemical disinfection (ECD) of constructed wetlands (CWs) effluents via in situ chlorine electrogeneration has been proposed for decentralised water treatment and reclamation. Studies demonstrating the feasibility of continuous ECD of CW effluents in field conditions for several weeks are scarce. Here, a pilot-scale CW was operated for 28 weeks to treat a calcium-rich wastewater stream (131 ± 42 mg L−1) for reclamation. Five electrochemical cell configurations were designed to continuously disinfect the effluent from the pilot-scale CW, differing in the water route, membrane type and catholyte. All configurations inactivated pathogens to levels considered safe for water reclamation. For four configurations, the maximum operating times without maintenance were short (< 1 week) due to calcium-based precipitates inducing membrane and cathode scaling. An additional configuration used rainwater as a cathodic influent for producing an alkaline stream to precipitate mostly calcium carbonate upstream from the ECD system. This avoided premature reactor failure, allowing 21 weeks of operation without apparent scaling. However, the alkaline stream demanded higher charge densities to be neutralised at the anode via water oxidation before a sufficient chlorine evolution. Thus, the flow rate of water treated (1.8 L h−1) was 4.6 times lower than for the other configurations. The resulting energy consumption (5.9 kWh m−3) was considered high for water reclamation. This work illustrates the practical aspects impeding stability and efficiency for ECD of hard waters and highlights possible strategies to deal with adverse scaling.

Hybrid SPEAK OUT! protocol improves aerodynamic measurements and PROMs in Parkinson's disease.

SPEAK OUT! has been shown to enhance various aspects of voice such as intensity, prosody, voice quality and perception of voice. However, their impacts on expiration and communication effectiveness have not yet been evaluated. This study aimed to evaluate the effectiveness of the Hybrid SPEAK OUT! method on aerodynamic measurements and patient-reported outcome measures (PROMs) in individuals with Parkinson's disease (PD). This study included 157 participants with PD who underwent an intensive 8-week multidisciplinary treatment program. The Hybrid SPEAK OUT! method consisted of three sessions per week, including two group sessions and one individual treatment session. Voice-related aerodynamic measures included maximum phonation time (MPT), vocal cord function using the S/Z ratio, and expiratory flow measures including peakexpiratoryflow (PEF) and peak cough flow (PCF). Two PROMs were included: the Hebrew version of the voice handicap index-10 and communication effectiveness questionnaire. The results of 111 participants were analysed. MPT duration increased, PEF and PCF increased, and better scores were found in PROMs. These findings would appear to support the effectiveness of the Hybrid SPEAK OUT! methods improving function, activity and participation in individuals with PD. However, further research is needed. What is already known on the subject Prior research has demonstrated the effectiveness of behavioral therapies, including the SPEAK OUT! program, in managing speech symptoms in individuals with Parkinson's disease (PD). These therapies have shown improvements in voice intensity, fundamental frequency, voice quality, and voice perception. However, the impact on aerodynamic measures, expiratory flow, and patient-reported outcome measures has not been extensively studied. What this paper adds to existing knowledge This study adds to the existing knowledge by demonstrating that a Hybrid SPEAK OUT! approach, can lead to improvements in aerodynamic measures, including maximum phonation time (MPT), expiratory and cough peak flow. In terms of motor learning, we found that two non-speech exhalation-related tasks that were not directly trained improved following the intensive speech training protocol. Furthermore, it shows positive changes in patient-reported outcome measures, with reduced voice-related disability and improved communication efficiency. What are the potential or actual clinical implications of this work? The findings of this study have important clinical implications for the management of speech symptoms in individuals with PD. The Hybrid SPEAK OUT! program, which combines group and individual sessions, can effectively improve voice, aerodynamic measurements and patient-reported outcome measures (PROMs), ultimately enhancing the overall quality of life for patients. These findings support the effectiveness of the Hybrid SPEAK OUT! methods for improving function, activity, and participation in individuals with PD.

Adaptive Traffic Management Model for Signalised Intersections

As population increases, one of the factors affecting life is traffic. Efficient traffic management has a direct positive impact on issues such as time, carbon dioxide emissions, and fuel consumption. Today, an important parameter under the heading of traffic is the signalling systems for intersections, which are operated with fixed-time, semi-actuated, fully actuated, and fully adaptive control methods. In this study, an adaptive traffic management model is developed for signalised intersections. The adaptive traffic management model developed includes phase extension with minimum and maximum time intervals dependent on density and phase skip features. Additionally, the most distinctive feature of the model is its flexible phase structure rather than a sequential phase. The Heybe intersection, located within the boundaries of Antalya province, is modelled one-to-one in the simulation of urban mobility (SUMO) simulation programme with real intersection data. The developed adaptive traffic management model is applied to the Heybe intersection, and the effects of the model are revealed. Improvements obtained from the SUMO simulation programme were verified through visual inspection, and high-accuracy results were determined. As a result of the studies, it was found that the application of the adaptive traffic management model developed at Heybe intersection, which has approximately 50,000 vehicles passing daily, resulted in a 27.2 % improvement in the average delay per vehicle parameter, a 32.4 % improvement in the average waiting time per vehicle parameter, and a 16.7 % improvement in the average speed per vehicle parameter.

Reduced Outer Space Algorithm for Globally Computing Affine Sum-of-Ratios Problems

This paper investigates the affine sum-of-ratios problem (SRP) which has numerous applications in many fields of economy and engineering. For globally computing the affine SRP, based on equivalent transformation and new affine relaxation problem, a reduced outer space branch-and-bound algorithm is designed. The designed algorithm has been proven to converge to a global optimal solution of the problem (SRP) eventually. Meanwhile, the maximum iteration time for the algorithm in the worst case is estimated by analyzing its computational complexity. Finally, numerical experimental results indicate that the presented algorithm is robust and effective.

Simulation of large plausible tsunami scenarios associated with the 2019 Durres (Albania) earthquake source and adjacent seismogenic zones

We present an analysis of the hazards of potential earthquake-generated tsunamis along the Albanian–Adriatic coast. The study adopts a case study approach to model plausible tsunamigenic events associated with the 2019 Mw 6.4 Durres (Albania) earthquake source zone. The approach combines current findings on regional tectonics and scenario-based calculations of potential tsunami impacts. The study’s goal is to analyse the propagation of tsunami waves generated by identified seismogenic sources (namely ALCS002 [Lushnje] and ALCS018 [Shijak]) and determine the tsunami risk assessment for Durres City on the Albanian–Adriatic coast. The sources can generate earthquakes with maximum moment magnitudes of Mw 7.5 and Mw 6.8, which are likely to trigger tsunamis that could cause significant impacts in the region. The modelling is performed deterministically with the NAMI DANCE numerical code, including scenarios associated with the largest plausible earthquake. The model integrates bathymetry and topography datasets of large and medium resolutions. Each tsunami scenario simulation is based on the solution of the non-linear shallow water equations used to generate maximum positive wave amplitudes (water elevation), travel time, and tsunami inundation maps. In Durres City, modelling indicates that medium-sized waves could reach up to 2.5 m inland, posing a significant danger to the city’s low-lying areas. The most substantial tsunami waves are expected to impact the area within the first 10 to 20 min. Combining inundation maps and information on exposed assets allows for identifying areas where damages can be expected. In terms of human impact, a preliminary analysis shows that the study area is prone to tsunami threat, with more than 138,000 inhabitants living in vulnerable urban areas of Durres City by 2036. The model’s capacity to capture details related to the presence of buildings is limited due to constraints posed by the resolution of bathymetry and topography datasets available during this study. If refined with high-resolution bathymetry and topography datasets, our results can be considered a backbone for exposure and resilience assessment features to be integrated into preparedness or new urban development plans.