Spray System Research Articles

Agricultural spray drone deposition, Part 2: Operational height and nozzle influence pattern uniformity, drift, and weed control

Abstract Agricultural spray drone (ASD) use in managed turfgrass has been given limited attention in the scientific literature. Further, deposition patterns of ASD spray have been obscured in previous research by ambient wind, crop canopy interference, and limited sampling resolution. Using a continuous sampling method involving blue colorant and water sprayed over white Kraft paper that was assessed via digital image analysis of stain objects and referenced spectrophotometric analysis of extractant, deposition metrics were estimated across a 29.3-m transect perpendicular to an ASD or ground sprayer spray swath. The ASD applies very fine droplets that are highly concentrated with herbicide, similar to ultra-low volume treatments, that improved smooth crabgrass [Digitaria ischemum (Schreb.) Schreb. ex Muhl.] control compared to a ground sprayer when the ASD was operated at 2 m above the turf. Unfortunately, these very fine droplets also drift, leading to four times greater droplet density at distance of almost 12 m away from the targeted spray swath following an operational height of 10 m compared to that at 2 m. As ASD operational height increases, drift and effective swath width at 30% coefficient of variation uniformity increases while effective application rate, total deposition, and D. ischemum control by quinclorac herbicide decreased. Total deposition decreased 6% for each m increase in ASD operational height, likely due to evaporation. The potential losses due to evaporation is a serious consideration for ASD use that has received little attention in the scientific literature. Our data suggest that ASD operational height should be as low as possible, but modification of spray systems may be needed to improve homogeneity of spray pattern.

Visualization of Aerial Droplet Distribution for Unmanned Aerial Spray Systems Based on Laser Imaging

Unmanned aerial spray systems (UASSs) are a commonly used spraying method for plant protection operations. However, their spraying parameters have complex effects on droplet distribution. The large-scale 3D droplet density distribution measurement method is insufficient, especially since the downwash wind is easily affected by the environment. Therefore, there is a need to develop a technique that can quickly visualize 3D droplet distribution. In this study, a laser imaging method was proposed to quickly scan moving droplets in the air, and a test method that can visualize 3D droplet distribution was constructed by using the traveling mode of the machine perpendicular to the scanning plane. The 3D droplet distribution of targeted and conventional UAVs was tested, and the methods for signal processing, noise reduction, and point cloud rebuilding for laser imaging were developed. Compared with the simulation results, laser imaging showed the pattern of droplet distribution from the two UAV structures well. The results showed that the laser imaging based method for detecting 3D droplet distribution is feasible, fast, and environmentally friendly.

IoT Based Precision Farming

This project focuses on leveraging drone images of the pests equipped with advanced sensors for pest detection in crops, combined with methods for image processing to identify diseases. The ultimate goal is to enhance crop health and productivity through timely and targeted pesticide application. Image processing techniques are used to detect signs of diseases and pests in the captured images. The use of machine learning CNN algorithm enhances the system’s ability to accurately classify and diagnose crop heath issues. Upon detection of pests, the IOT platform triggers a response mechanism to deploy a precision pesticide spraying system. This ensures targeted and localized treatment, reducing the overall use of pesticides and minimizing environmental impact. This project involves capturing images of pests using a camera, followed by processing these images to extract key features using various image processing techniques. The extracted features are analyzed using algorithms, primarily Convolutional Neural Networks (CNNs), to detect variations in color and other dominant characteristics in the images. By comparing these features across samples, the system can identify pests and plant diseases more efficiently. This approach aims to provide a quicker and more cost-effective solution for pest detection and disease management.

Improvement of thermal environment in the outdoor atrium by employing the spray system

Outdoor atriums have recently been applied with increasing frequency for natural illumination, but they produce a harsh thermal environment easily in summer. Moreover, overheating of the outdoor atrium necessitates air-conditioning to moderate indoor thermal comfort. Simultaneously, the substantial heat emissions from air-conditioning outdoor units worsen the outdoor thermal environment, creating a vicious cycle. Traditional passive evaporative methods involving water and greenery, while capable of regulating the thermal environment, suffer from low evaporative efficiency and pose significant challenges. To improve thermal environment in outdoor atriums, the spray system was employed due to its high cooling efficiency, especially in open or semi-open spaces. In this study, a comparative experiment was conducted to evaluate the effectiveness of using a spray system for evaporative cooling in open outdoor spaces. Furthermore, employing high-efficiency evaporative cooling through spraying to disrupt the vicious cycle of indoor and outdoor thermal environments. The dual goals include regulating indoor and outdoor thermal conditions while also mitigating the local heat island effect. Temperature and humidity distribution within the atrium and adjacent hallways were monitored, along with the impact on air-conditioning operation consumption in neighboring offices. Results showed that the spray system significantly improved the thermal environment in the outdoor atrium, reducing the average and peak air temperatures by 0.94–2.83 °C and 2.92–5.21 °C, respectively. It also resulted in a drop in the average temperature by 0.56–1.62 °C and the peak temperature by 2.31–3.25 °C in adjacent hallways. This effectively eased the issue of overheating in these areas while raising the comfort level in adjacent office spaces. The predicted mean vote decreased from 1.46 to 0.87, indicating a significant improvement in thermal environment in neighboring offices. Furthermore, the daily energy consumption was reduced by 10.6–12.4% in neighboring offices. This study provided the valuable guidance for improving thermal environments within outdoor atrium.

Efficient Real-Time Droplet Tracking in Crop-Spraying Systems

Spray systems in agriculture serve essential roles in the precision application of pesticides, fertilizers, and water, contributing to effective pest control, nutrient management, and irrigation. These systems enhance efficiency, reduce labor, and promote environmentally friendly practices by minimizing chemical waste and runoff. The efficacy of a spray is largely determined by the characteristics of its droplets, including their size and velocity. These parameters are not only pivotal in assessing spray retention, i.e., how much of the spray adheres to crops versus becoming environmental runoff, but also in understanding spray drift dynamics. This study introduces a real-time deep learning-based approach for droplet detection and tracking which significantly improves the accuracy and efficiency of measuring these droplet properties. Our methodology leverages advanced AI techniques to overcome the limitations of previous tracking frameworks, employing three novel deep learning-based tracking methods. These methods are adept at handling challenges such as droplet occlusion and varying velocities, ensuring precise tracking in real-time potentially on mobile platforms. The use of a high-speed camera operating at 2000 frames per second coupled with innovative automatic annotation tools enables the creation of a large and accurately labeled droplet dataset for training and evaluation. The core of our framework lies in the ability to track droplets across frames, associating them temporally despite changes in appearance or occlusions. We utilize metrics including Multiple Object Tracking Accuracy (MOTA) and Multiple Object Tracking Precision (MOTP) to quantify the tracking algorithm’s performance. Our approach is set to pave the way for innovations in agricultural spraying systems, offering a more efficient, accurate, and environmentally responsible method of applying sprays and representing a significant step toward sustainable agricultural practices.

Effect of ethanol addition on enhancing the cooling performance improvement of spray system

The widespread application of spray technology has significantly improved outdoor environmental thermal comfort. However, the spray system is unable to fulfill special comfort requirements. Utilizing mechanical ventilation and control systems effectively enhances the cooling performance of spray systems; however, those approaches are associated with elevated costs and maintenance complexities. The combination of ethanol and water has been demonstrated to produce a lower surface tension and a higher latent heat of evaporation, a property that contributes to the heat transfer efficiency and evaporation rate of the droplets. Considering the convenience and cost-effectiveness of adding ethanol as an additive, it emerges as the optimal choice. To evaluate the effectiveness of ethanol on the evaporative cooling performance of the spray system, a comparative study was conducted, comparing the cooling performances of different concentrations of ethanol with a spray system without ethanol addition. Five operating conditions were designed, including a no-spray case, a non-additive case, a 0.5% ethanol concentration case, a 1.0% ethanol concentration case, and a 1.5% ethanol concentration case. The results demonstrated that adding ethanol effectively enhanced the cooling performance of the spray system. At 1.7m above ground level (0.4m away from the nozzle), compared to the non-additive case without ethanol, the 0.5% ethanol concentration case, 1.0% ethanol concentration case, and 1.5% ethanol concentration case further reduced the temperature by 0.95°C, 1.64°C, and 2.27°C. Moreover, the relative humidity grew by 3.57%, 9.25%, and 13.5%, respectively. Adding ethanol significantly enhanced the evaporative cooling effect of the spray system, with the optimal concentration observed at 1.5%. The results demonstrate that enhancing the evaporative cooling efficacy of a spray system by introducing ethanol into the spray medium represents a viable strategy and improve urban thermal environment in summer. Furthermore, this study aims to examine the impact of droplet evaporation on relative humidity, establishing a foundation for future enhancements aimed at addressing the issue of over-humidification in spray systems.

Spatiotemporal spreading characteristics of dust aerosols by coal mining machine cutting and "partition/multi-level composite field" atomization dust purification technology

To locally atomize the spatial confinement of primary dust generated by the shearer cut-off, the CFD-DPM mathematical model was used to simulate and analyze the wind-borne dust transport law, which resulted in the heavily polluted area of primary dust. A multi-level and multi-dimensional coal machine spray system was developed for the polluted area, its atomization effect was verified by using the TAB breakup model. The results show that the heavily polluted area of primary dust is mainly concentrated in the position of fully mechanized mining face Z=24–39 m area of shearer, and the average concentration is 738.2 mg/m³. The average concentration of droplets generated by the multi-level and multi-dimensional shearer spray system at the shearer drum is 0.66 kg/m³, with a percentage of droplets with particle size between 40 and 160 μm exceeding 85 %. The coverage rate of the shearer drum is 95 %. The relationship between droplet concentration and time is consistent with the Boltzmann function fitting model. Following the implementation of the multi-level and multi-dimensional coal machine spray system in the field, it was observed that the average reduction in dust levels was 90.9 % for total dust and 85.7 % for exhaled dust in the synthesized mining face.

Computationally cost-efficient analysis of the flow behavior of twin-fluid atomizers using computational fluid dynamics

In industrial-scale operations, wet electrostatic precipitators (WESPs) are used to minimize particulate matter, employing atomizers such as single-fluid and twin-fluid atomizers (TFAs). While TFAs provide several benefits over single-fluid atomizers, quantifying their spray characteristics is more complex, necessitating comprehensive case studies to design the internal structure of the spray and achieve desired properties. This study employed computational fluid dynamics (CFD) to simulate the internal and external flow phenomena of TFAs in industrial-scale WESPs, aiming to facilitate various parametric studies by reducing the high computational costs associated with analyzing high-speed internal flows and particle dynamics within the spray system. To decrease computational costs, the simulation was divided into two parts using stepwise segregated scenarios: Part I focused on the high-cost internal flow analysis, examining the spatiotemporal evolution of internal flow until it is fully developed, followed by droplet size distribution estimation at the nozzle. Part II computed the external flow of the spray, assessed potential cost reductions by examining the interactions between dispersed droplets, and validated the spray angle, penetration, and coverage against experimental data. The segregated strategy employed mapping techniques to integrate the two parts seamlessly. The simulation results closely matched the experimental benchmarks for spray angle, penetration, and coverage within a minimal error margin (<5%), demonstrating the model’s accuracy in capturing actual spray phenomena in TFAs. This approach significantly reduced the computational cost by more than twentyfold compared to conventional one-step solvers, offering a viable method for conducting various case studies in spray CFD simulations.

Design and Testing of a Fruit Tree Variable Spray System Based on ExG-AABB

This paper addresses the issue of pesticide waste and low utilization rates resulting from traditional plant protection via spraying operations, which apply equal dosages to different targets or to different parts of the same target. To tackle this problem, we designed a variable fruit tree spraying system based on the ExG-AABB (excess green and axis-aligned bounding box) algorithm. We used a Kinect depth camera to capture information about the fruit tree canopy and constructed a spray flow model using pulse width modulation and variable spray control technology. Variable multi-nozzle spraying was guided by combining this canopy data. We evaluated the accuracy of each model in calculating canopy volume by comparing the coefficient of determination (R2) and root mean square error (RMSE) of the ExG-AABB with the slice convex hull method, voxel method, three-dimensional alpha-shape method, and QuickHull method. The ExG-AABB algorithm had the highest R2 value (0.9334) and the lowest RMSE value (0.0353 m3) among the five models, indicating that it most accurately reflects the true volume of the fruit tree canopy. This validates the effectiveness of the ExG-AABB algorithm in calculating canopy volume. We established a correlation model between canopy volume and spray volume, designed a canopy-adaptive layering method based on point cloud processing, and achieved precise calculation of nozzle flow. Comparative field experiments were conducted to analyze the spray coverage rate and observed flow, thereby evaluating the spraying effect of this variable spraying system. The experimental results showed that compared to conventional continuous spraying, this variable spraying system not only achieves more uniform spray coverage but also significantly reduces pesticide usage by 48.1%. Furthermore, through system optimization, the average coverage rate of the middle layer of the canopy decreased by 17.53%, effectively reducing the phenomenon of overlapping spraying from multiple nozzles and improving spraying efficiency.

Strategies, challenges, and outcomes of heat stress resilience in sub-Saharan African community-based cattle feedlots: a systematic review.

In sub-Saharan Africa, cattle feedlots face a significant challenge in dealing with heat stress. However, there is a lack of inclusive strategies for resilience in these situations. The aim of this systematic review is to investigate the strategies, challenges, and outcomes related to heat stress resilience in community-based cattle feedlots in sub-Saharan Africa. The PRISMA approach, which is a method for reporting systematic reviews and meta-analyses, was used to identify, screen, and analyze 30 peer-reviewed articles published over the last 20 years from Google Scholar and Scopus. The review found that key strategies to mitigate heat stress include providing shade through natural and artificial means, ensuring constant access to cool, clean water using water spraying systems and cooling ponds, and implementing nutritional adjustments such as high-energy feeds and electrolyte supplements. Additionally, genetic selection for heat-tolerant breeds and management practices like adjusting feeding times and improving ventilation were found to be effective in dealing with heat stress. In particular, local germplasm and genetic traits of cattle in sub-Saharan Africa play a crucial role in heat stress resilience. Indigenous breeds, which have adapted to the region's harsh climate over centuries, exhibit traits such as higher heat tolerance, better water-use efficiency, and improved feed conversion rates under heat stress conditions. This genetic resilience can be enhanced through targeted breeding programs aimed at amplifying these beneficial traits. Implementing these strategies resulted in improved cattle health and productivity, as evidenced by enhanced weight gain, better reproductive performance, and lower mortality rates. The socio-economic benefits of these strategies included reduced economic losses and increased farmer incomes, which in turn contributed to improved community health and nutrition. However, the review also identified significant challenges, including financial constraints, limited access to knowledge and training, and cultural resistance. To address these barriers, the review recommends increased investment in affordable cooling technologies, farmer education, and community-based initiatives. Additionally, leveraging the genetic strengths of local cattle breeds should be prioritized to maximize the effectiveness of heat stress resilience strategies.

Innovative double-layer coated stent for enhanced Sca-1+ stem cell recruitment and vascular repair

Abundant stem cells express the stem cell antigen 1 (Sca-1) in bone marrow and vascular adventitia possess the capacity to differentiate into endothelial cells (VECs) and vascular smooth muscle cells (VSMCs) during vascular injury, thus enabling restoration. Dickkopf-3 (Dkk3) and histone deacetylase 7 derived-peptide (7A peptide, MHSPGAD) could increase migration and differentiation of Sca-1+ cells to participate in vascular repair. Herein, we present a double-layered drug coating 316L stainless steel stent (DAC stent) using an ultrasound spray system, which consists of an inner layer of chitosan (CS) loaded with Dkk3 and an outer layer loaded with 7A peptide. The coating exhibits good biocompatibility based on platelet adhesion, water contact angle, cell proliferation, and hemolysis rate experiments. The analysis of VECs and VSMCs on the coating reveals that Sca-1+ cells promote VECs repair and maintain the contractile VSMCs. Further analysis of DAC stent implantation on neointimal inflammation, endothelium repair and vascular remodeling in 3 months shows the coating recruits Sca-1+ cells to the injury sites to differentiate into VECs and contractile VSMCs, thus accelerating vascular repair. A novel stem cell recruiting, chemical-free drug coating stent is developed, and it might be a candidate strategy and promising application prospect for implantation devices.

Simulation of the removal of radioactive aerosols from the atmosphere of NPP containment by spray system droplets using the MAVR-TA code

Simulation of the removal of radioactive aerosols from the atmosphere of NPP containment by spray system droplets using the MAVR-TA code

Improving UASS pesticide application: optimizing and validating drift and deposition simulations.

As unmanned aerial spraying systems (UASS) usage grows rapidly worldwide, a critical research study was conducted to optimize the simulation of UASS applications, aiming to enhance pesticide delivery efficiency and reduce environmental impact. The study examined several key aspects for accurate simulation of UASS application with lattice Boltzmann method (LBM). Based on these discussions, the most suitable grid size and simulation parameters were selected to create a robust model for optimizing UASS performance in various pest management scenarios, potentially leading to more targeted and sustainable pest control practices. The effect of stability parameter, grid size around the rotor and near ground, and parameters at wake flow were carefully analyzed to improve the precision of pesticide drift predictions and deposition patterns. Optimal grid sizes were identified as 0.2 m generally, 0.025 m near rotors, and a 0.1 + 0.2 m scheme for ground proximity, with finer grids improving accuracy but increasing computation time. Wake resolution and threshold significantly influenced simulation results, while wake distance had minimal impact beyond a certain point. The LBM's accuracy was validated by comparing simulated downwash flow and droplet deposition with field test data. This study optimized UASS simulation parameters, balancing computational efficiency with accuracy. The validated model enhances our ability to design more effective UASS for pest management, potentially leading to more precise and targeted pesticide applications. These advancements contribute to the development of sustainable pest control strategies, aiming to reduce pesticide usage and environmental impact while maintaining crop protection efficacy. © 2024 Society of Chemical Industry.

Knapsack air assisted electrostatic sprayer for agricultural formulations

An experimental prototype of a backpack-type rechargeable battery-powered air-assisted electrostatic sprayer was designed and tested for performance while preserving techno-commercial competence and affordability for India's marginal and small farmer communities. The designed prototype electrostatic sprayer achieved good levels of charge induction on the spray particles at various electrode potentials (1 to 12 kV). At a charging electrode potential of 9 kV and a nozzle discharge rate of 2 mL s−1, electrostatically charged spray had a maximum charge to mass ratio (CMR) of 1.79 mC kg−1. The Electric Ducted Fan (EDF) used for high velocity air assistance was capable of transporting charged spray droplets onto distant targets such as orchard trees and field crops with a spray throw of up to 5 m. The high-pressure atomization method produced fine droplets within a Volume Median Diameter (VMD) range of 90 to 100 µm, resulting in better charge induction and wrap-around effect. As the prototype features fewer moving mechanical components, reduced total noise and vibrations, it promises operator comfort in the long run while requiring less system maintenance. Environmental contamination can be minimized as the large quantity of harmful chemicals be prevented from drifting into the soil and nearby waterbodies. The competitive performance and lower investment could encourage majority of the Indian famers to upgrade with the developed air assisted electrostatic spraying system contributing to agro-socio-economic welfare.

Automatic Disease Detection from Strawberry Leaf Based on Improved YOLOv8.

Strawberries are susceptible to various diseases during their growth, and leaves may show signs of diseases as a response. Given that these diseases generate yield loss and compromise the quality of strawberries, timely detection is imperative. To automatically identify diseases in strawberry leaves, a KTD-YOLOv8 model is introduced to enhance both accuracy and speed. The KernelWarehouse convolution is employed to replace the traditional component in the backbone of the YOLOv8 to reduce the computational complexity. In addition, the Triplet Attention mechanism is added to fully extract and fuse multi-scale features. Furthermore, a parameter-sharing diverse branch block (DBB) sharing head is constructed to improve the model's target processing ability at different spatial scales and increase its accuracy without adding too much calculation. The experimental results show that, compared with the original YOLOv8, the proposed KTD-YOLOv8 increases the average accuracy by 2.8% and reduces the floating-point calculation by 38.5%. It provides a new option to guide the intelligent plant monitoring system and precision pesticide spraying system during the growth of strawberry plants.

UGV‐Based Precision Spraying System for Chemical Apple Blossom Thinning on Trellis Trained Canopies

ABSTRACTBlossom thinning is one of the key steps in apple crop load management that improves the quality of apples, reduces stress on the trees, and avoids the likelihood of biennial bearing. Conventional chemical blossom thinning such as air‐blast spraying can lead to excessive use of chemical thinner to ensure full coverage, which can also cause leaf damage fruit russeting. In addition, a well‐trained operator is required to use these chemical spraying systems. To address these challenges, a UGV‐based precision spraying system was developed for automated and targeted chemical blossom thinning for apples. The system is capable of automatically driving along the tree row in the orchard environment during blooming stage, locating apple flower clusters to be thinned using a real‐time machine vision system, and precisely spraying the chemical thinner to the targeted flower clusters. A set of field tests were conducted to evaluate the performance of the UGV‐based target spraying system by comparing it to a conventional air‐blast sprayer (ABS) and a previous prototype named the cartesian target sprayer (CTS). Tests showed that the flower cluster detection reached a precision of 93.8%. The UGV‐based spraying system used 2.2 L of chemical thinner to finish the chemical thinning for 30 apple trees, followed by the ABS and CTS with 4.2 and 2.4 L usage, respectively. The robotic system also obtained an average fruit set of 2.2 per cluster after thinning, which was comparable to that with the air blast sprayer. The findings indicated that the robotic thinning system demonstrated a 66.7% reduction in chemical usage compared to the ABS and exhibited a 43.0% faster operational pace than the CTS, while attaining a comparable fruit set per cluster. The outcomes of the study provided guidance for developing a full scale robotic chemical thinning system for modern apple orchards.

An Automated Sprinkler Cooling System Effectively Alleviates Heat Stress in Dairy Cows.

(1) Background: Heat stress detrimentally restricted economic growth in dairy production. In particular, the cooling mechanism of the spraying system effectively reduced both environmental and shell temperatures. This study was designed to investigate the underlying modulatory mechanism of an automatic cooling system in alleviating heat-stressed dairy cows. (2) Methods: A total of 1208 multiparous dairy cows was randomly allocated into six barns, three of which were equipped with automatic sprinklers (SPs), while the other three were considered the controls (CONs). Each barn was considered a replicate. (3) Results: Body temperatures and milk somatic cell counts significantly decreased, while DMI, milk yield, and milk fat content significantly increased under SP treatment. Rumen fermentability was enhanced, embodied by the increased levels of total VFA, acetate, propionate, and butyrate after SP treatment. The rumen microbiota results showed the relative abundances of fiber-degrading bacteria, including the Fibrobacters, Saccharofermentans, Lachnospira, Pseudobutyrivibrio, Selenomonas, and Succinivibrio, which significantly increased after receiving the SP treatment. (4) Conclusions: This study demonstrated that SP effectively alleviated heat stress and improved production performances and milk quality through modulating the rumen microbiota composition and fermentation function of dairy cows.

Design and Development of a Side Spray Device for UAVs to Improve Spray Coverage in Obstacle Neighborhoods

Electric multirotor plant protection unmanned aerial vehicles (UAVs) are widely used in China for efficient and precise plant protection at low altitude for low volumes. Unstructured farmland in China has various types of obstacles, and UAVs usually use a detour path to avoid obstacles due to flight altitude limitations. However, existing UAV spray systems do not spray when in obstacle neighborhoods during obstacle avoidance, resulting in insufficient droplet coverage and reduced plant protection quality in the area. To improve the droplet coverage in obstacle neighborhoods, this article carries out a study of side spray technology with an electric quadrotor UAV, and proposes the design and development of a side spray device. The relationship between the obstacle avoidance path of the UAV and the spray pattern of the side spray device and their effect on droplet coverage in obstacle neighborhoods was explored. An accurate measurement method of the relative position between the UAV and obstacles was proposed. Spray angle calculations and nozzle selection for the side spray device were carried out in conjunction with the relative position. A rotor wind field simulation model was designed based on the lattice Boltzmann method (LBM), and the spatial layout of the side spray device on the UAV was designed based on the simulation results. To explore suitable spray patterns for the side spray device, comparative experiments of droplet coverage in obstacle neighborhoods were carried out under different environments, spray patterns, and flight parameter combinations. The relationship between the flight parameter combinations and the distribution uniformity of droplets and the effective swath width of the side spray device was explored. The experimental results were analyzed by an analysis of variance (ANOVA) and a relationship model was obtained. The results showed that the side spray device can effectively improve droplet coverage in obstacle neighborhoods compared to a device without side spray using the same flight parameter combinations. The effective swath width in obstacle neighborhoods can be increased by a minimum of 6.35%, maximum of 35.32%, and average of 15.25% using the side spray device. The error between the predicted values of the relational model and the field experiment results was less than 15%. The results verify the effectiveness and rationality of the method proposed in this article. This study can provide technical and theoretical references for improving the plant protection quality of UAVs in obstacle environments.

VIKTORIA experiments in the frame of R&D project on sump filtration during a loss of coolant accident

During a Loss of Coolant Accident (LOCA), in PWR’s, water is injected by the Emergency Core Cooling System (ECCS) to ensure the long-term core coolability and by the Containment Spray System (CSS) to remove residual heat and to maintain containment integrity. After the drainage of the Refueling Water Storage Tank (RWST), water is taken from sumps in the lower part of the reactor building. A filtering system is implemented to collect debris produced by the pipe break as well as other latent materials, such as fiberglass, paint and concrete particles, and to minimize the amount of debris entering in the ECCS and CSS systems. IRSN has launched an experimental R&D project investigating the clogging of sump filters by integral tests performed in the VIKTORIA loop. The main objectives are to investigate the head loss of the filter (physical and chemical clogging) for prototypic upstream debris source term in relevant thermal hydraulic conditions (water temperature and flow velocity on the filter surface) in compliance with the temperature profile and the chemistry of the water in sumps during a LOCA transient. For that, the VIKTORIA loop was equipped successively with two types of 2 m2 filters used in 900MWe NPP’s. The tests highlight the settling of the largest particles (concrete, painted chips) and part of the fibers; the transport of debris (roughly 55 to 65 % of the injected debris source term) leads to the physical clogging of the filter. The debris carried to the filter generate at 80 °C (with chemistry) a very quick increase of the pressure drop across the filter (≈7 kPa) that could be due to rapid chemical effects further to fibers corrosion. At the end of the 80 °C plateau, a pressure drop increase was observed due to the temperature decrease in agreement with the water viscosity evolution. The two types of filters (rectangular pockets or planar types) behave very differently with rather low head losses for the second type; ≈1.5 kPa. Nevertheless, downstream debris source term appears to be more significant with the planar filter (compared to the filter with pockets) during the first hour of injection before the fibrous debris bed formation. We have also observed a more stabilized “cake”, during the (7 days) medium term evolution compared to that for rectangular pockets filter due to motion of debris inside pockets. The recent experiments performed with less amount of fibers (by replacement of part of fibrous materials by RMI metallic insulation) led to significantly reduce the head loss without any consequences on the downstream behavior.

Rod bundle cooling by a spray system in spent fuel pool accident conditions

The knowledge of the phenomenology of loss of coolant/cooling scenarios in spent fuel pools is of prime interest since a huge amount of fission product can be released in accident conditions. In this context, the ASPIC facility is dedicated to the study of the heat transfers that occur at the scale of one rod bundle stored in a spent fuel pool cell. Investigations have been carried out on a full high assembly composed of 17 × 17 electrically heated rods. The water level in the cell is controlled and set, in this test series, so that about one meter of the assembly is uncovered. Therefore, the upper part of the assembly gets overheated unless some counter measure is undertaken. In this contribution, the ability of a spray system to limit the temperature rise of the uncovered part of the rod bundle is assessed. It has been observed that the water spray reduces the temperature level on the whole cross section of the assembly and lowers significantly the risk of degradation of the rod bundle. Besides, for a bundle heat power of 20kW, a spray mass flow rate of 10 gs−1 or higher leads to rod temperatures lower than 480°C.