[Departement_IRSTEA]Eaux [TR1_IRSTEA]RIVAGE

Deep-sea cages are highly susceptible to biofouling due to long-term seawater immersion, which promotes the attachment and growth of marine organisms on nets, significantly reducing fish survival. To address this issue, this study explores the use of low-pressure abrasive-water jets (LPAWJ) for cage fouling removal through numerical simulation. Based on a Box-Behnken response surface design, nozzle inlet pressure X1, nozzle outlet diameter X2, and target distance X3 were selected as optimization parameters. The peak jet impact force Z1, stable jet impact force Z2, peak abrasive-water jet velocity Z3, and peak abrasive particle velocity Z4 were chosen as evaluation indicators to characterize the jet’s instantaneous impact ability, sustained action ability, and dynamic particle behavior. Using the entropy method, weights for each indicator were determined, and the jet’s overall removal capability was calculated. A regression model was developed by integrating numerical simulation with the response surface methodology (RSM), and the optimal parameter combination was identified as X1 = 4.5 MPa, X2 = 10 mm, and X3 = 205.396 mm. Compared with the poorest experimental condition (Condition 1), the jet’s overall removal capability obtained under the optimal parameter combination increases by 101.35%. Experimental validation further confirms that the optimized parameters yield the best oyster-removal performance of the low-pressure abrasive jet, with the average removal rate improving by 100.55% relative to Condition 1. The methodology and results of this study provide a theoretical foundation and technical reference for the design and optimization of automated net-cleaning systems or net-cleaning robots equipped with low-pressure abrasive jets. By integrating the proposed model and operating parameters, future robotic systems will be able to predict and dynamically adjust jet conditions according to fouling characteristics, thereby improving the efficiency, cost-effectiveness, and sustainability of maintenance operations in marine aquaculture.

The application of biochar or silicate rock powder as soil amendments combines carbon dioxide removal with soil improvement. However, their combined short-term effects on nutrient dynamics and microbial activity are poorly understood. Therefore, we combined wood biochar and basanite powder via co-application and via co-pyrolysis of biomass and basanite to rock-enhanced biochar in a nine-week semi-field-based lysimeter experiment with cabbage turnip ( Brassica oleracea var. gongylodes L.). We measured carbon (C), nitrogen (N), available phosphorous (P), mineral N, dissolved organic C (DOC), microbial biomass C (C mic ), soil pH, and electric conductivity (EC). We examined extracellular enzyme kinetics of ß-glucosidase (BG), chitinase (CH), leucine-aminopeptidase (LAP), and acid phosphatase (AP) related to C, N, and P cycles. From potential enzyme activity (V max ) of BG, LAP, and AP we calculated extracellular enzyme stoichiometry (EES), vector angle and length to assess nutrient limitations. In combined applications, the influence of biochar was dominant. The application of biochar-containing amendments (biochar, co-application, co-pyrolyzed rock-enhanced biochar) to our sandy topsoil significantly increased C, P, DOC, C mic , pH, and EC. Co-application even exceeded single biochar in increasing N, pH, and EC. Single biochar application resulted in the highest short-term P availability, while combined applications potentially result in a long-term P supply. While LAP’s V max increased following biochar-containing amendment application, V max of the other enzymes decreased. Although AP showed the highest V max , indicating a P limitation, the enzyme patterns and EES suggest an increased N demand and a shift from P-limited towards a more balanced microbial nutrient demand following biochar-containing amendment application. • Combined applications mainly driven by biochar, not by basanite • Biochar and combined applications increased P availability and relative N demand • Co-pyrolysis showed no advantage compared to co-application of biochar and basanite • No basanite weathering during 9-week planted lysimeter experiment visible in soil • Basanite application caused no negative effects, highlighting its CDR potential

Under thermo-mechanical stress via a bulge test (BT), composite circular diaphragms (CCD) exhibit temperature-dependent mechanical behavior, including changes in Young’s modulus, yield strength, and residual stress. The application of a differential pressure and temperature causes the membrane to deform, allowing researchers to characterize composite material properties, particularly for materials used in microelectromechanical sensors (MEMS) operating in harsh environments. This paper aims to explore how CCD made from basalt fiber reinforced polymer (BFRP) behaves under thermal and mechanical stress, particularly in various engineering and bioengineering sensor applications, using a technique known as the BT. To start, the diaphragm is pre-stressed and clamped between two plates. When applying differential pressure, it causes the diaphragm to deform. An analytical approach is developed for utilizing the BT to describe the thermo-mechanical properties of these diaphragms. This method is well-suited for examining how diaphragms behave mechanically in both elastic and plastic states. A finite element model (FEM) is extended to analyze the BT outcomes and look into how pre-stress influences the pressure testing, comparing results from the FEM with those derived from analytical calculations. The variations in thickness and material type are also taken into account to better understand how they affect the diaphragm’s mechanical behavior under stress. Additionally, this work considers how temperature impacts the material properties of the diaphragm, which is crucial for analyzing its thermo-mechanical response. The relative () for maximum deflection the analytical and numerical results is less than 0.3%. The simulations are done using ANSYS, MATLAB and its PDE toolbox to get the results.

The cosmic-ray (CR) electrons and positrons in space are of great significance for studying the origin and propagation of cosmic-rays. The satellite-borne experiment DArk Matter Particle Explorer (DAMPE) has been used to measure the separate electron and positron spectra, as well as the positron fraction. In this work, the Earth's magnetic field is used to distinguish CR electrons and positrons, as the DAMPE detector does not carry an onboard magnet. The energy range for the measurements is from 10 to 20 GeV, being currently limited at high energy by the zenith pointing orientation of DAMPE. The results are consistent with previous measurements based on the magnetic spectrometer by AMS-02 and PAMELA, while the results of Fermi-LAT seem then to be systematically shifted to larger values.

Abstract This study examines the implementation and application of Artificial Intelligence (AI) methodologies for estimating the Remaining Useful Life (RUL) of civil infrastructure assets, with the aim of supporting more effective civil infrastructure maintenance and management practices. A total of 90 publications were reviewed. Although not all were directly related to civil infrastructure RUL, the overall body of work reveals a continuous research activity since 2014, reflecting growing interest in data-driven deterioration forecasting. A key motivation for this review is to identify AI approaches that have been successfully applied to structured datasets and that demonstrate potential for practical integration into civil engineering asset-management environments. While advanced AI techniques exist, their adoption in civil infrastructure engineering and maintenance management remains limited, and many real-world systems require methods that balance predictive capability with interpretability, robustness, and compatibility with existing workflows. This study discusses a range of AI approaches—including Deep Learning (DL), Machine Learning (ML) ensemble regression, and hybrid models—highlighting their ability to capture complex degradation processes and their potential to enhance durability predictions. Challenges such as data quality, generalisability and interpretability of AI models, and the difficulty of embedding advanced analytics into current maintenance systems are identified. Opportunities for future research include improving model stability against noise, leveraging diverse data sources, addressing class imbalance, quantifying predictive uncertainty, exploring alternative degradation models, and integrating maintenance actions within RUL prediction frameworks. Overall, the findings underscore the increasing role of AI in asset-life prediction and highlight the need for approaches that remain technically sound while being feasible for implementation in civil real infrastructure-management settings.

The Landscape of Outstanding Features of “Islands and Cliffs near Slankamen” (ICS) is a protected area in the Danube region, characterized by diverse forest and wetland habitats. Different forms of sustainable tourism (SUTO) can be developed in this area, including nature-based tourism, ecotourism, and scientific tourism. This study aims to examine the impact of SUTO dimensions on residents’ satisfaction in the settlements of Stari Slankamen and Novi Slankamen. The research is based on the Prism of Sustainability (PoS) model, which includes ecological, economic, socio-cultural, and institutional dimensions. A total of 1030 inhabitants participated in the survey. The results show that all four dimensions have a statistically significant impact on residents’ satisfaction. The economic and institutional dimensions have a stronger influence, while the socio-cultural and ecological dimensions were evaluated more positively by respondents. The results indicate the need for better coordination of tourism development and management activities in order to achieve a balance between nature protection, economic benefits, and the needs of the local community.

Socio-cultural tourism factors include folk music, cuisine and gastronomic brands, domestic handicrafts, crafts, folk customs, events, local tourist culture and cultural–historical heritage, language, social life of residents, and other factors. Important natural factors are the geographical and tourist location, features of relief, hydrographic potential, types of climates, plant and animal species, and others. Socio-cultural factors, together with natural factors, can create the basic characteristics of a destination. This research used the two landscapes of outstanding features (LOFs) that are part of the wider area of Serbia’s capital city, Belgrade. The selected areas are the main excursion and tourist centers, which possess significant natural and cultural characteristics for the development of sustainable tourism (STO). The main characteristics of these LOFs are forest ecosystems, which have an impact on tourism and recreation. The article used a quantitative methodology, based on the survey technique, which was used to collect data. A total of 1120 respondents were surveyed. Respondents expressed their views on claims related to space factors, which can influence the development of tourism and recreation. By analyzing the results, it can be concluded that there is an impact of factors on satisfaction with STO.

Current automatic control system uses linear mathematical models to validate automatic flight control for airplanes. Gain scheduling, non linearity and improved feedback through simulation are also introduced. Very computers operate the actuators in order to keep the airplane on the right path, in the current trim and with the proper safety margin. Some engineers are testing fuzzy control logic to control airplanes and UAVs (Unmanned Aerial Vehicles). The result is brilliant, since very simple controllers are able to fulfill the specification with little "knowledge" about the airplane performances. This means that fuzzy controllers are very robust since they are able to operate with much degraded aerodynamics or with reduced thrust. However no one was able to validate the airplane/fuzzy controller with a mathematical proof. So it is not sure that it will works in any condition. By the way the same happens for the airplane/human pilot model. So a mathematical proof is still required also for this later solution. On the other side, very accurate, time based non linear mathematical models are available for flight simulation. These models are used in several fields ranging from development to training. In recent years computers that can run these accurate models in fractions of seconds were marketed at very low prices. The idea introduced in this paper is to run an accurate mathematical model on some of these fast autopilot computer in order to optimize the sequence of commands to be inputted to the FBW system of the airplane in order to keep the path in the safest way possible. For this purpose it is necessary to have enough computing power to calculate this best solution at a rate compatible to a correct control of the airplane. In this paper we will demonstrate that these computing resources are already available and it is predictable that the computing speed of future years will allow running even more sophisticated simulators. The question may be: why use more complicated systems when current control system fulfills satisfactorily the same task in a cheaper and more reliable way? The answers are several. At first it is a matter of robustness, what happens if the yaw damper fails or the actuator of the left ailerons is unable to fulfill its task or the tail is ripped off? In this case standard systems are not able to take the airplane to the ground safely even if it is indeed possible to control the airplane by a coordinate action of the remaining control surfaces. Optimization means that it is possible to reduce the stress on structures in order to improve aircraft life, to find the control sequence that assure the mean fuel consumption or to prefer the shortest time possible to reach the required trim on the right path. In other words it is more flexible. It is also possible to monitor aircraft performance in order to evaluate external or internal disturbances. Air turbulences, wind gusts may be controlled in order to optimize structural integrity or passenger comfort. Internal disturbances, as defective functioning of components or controls, occasional failure of sensors may be diagnosed, in some cases corrected in other simply reported after landing. The reliability improvement is not the latest benefit. As a rule of the thumb more electronics or more components means less reliability with the exception of redundancy and this is the case of this paper. © 2006-2015 Asian Research Publishing Network (ARPN).