Search Results (30)

Aiming at the wind-blown snow disasters plaguing tunnel portals along the China-Tajikistan Highway Phase II Project, this study optimizes the protective parameters of wind deflectors through numerical simulation to improve the disaster prevention efficiency of tunnel portals in alpine mountainous areas. Three core control parameters of wind deflectors, namely horizontal distance from the tunnel portal (L), plate inclination angle (β), and top installation height (h), were selected as the research objects. Single-factor numerical simulation scenarios were designed for each parameter, and an L9(3³) orthogonal test was further adopted to formulate 9 groups of multi-parameter combination scenarios, with the snow phase volume fraction at 35 m on the leeward side of the tunnel portal set as the core evaluation index. A computational fluid dynamics (CFD) model was established to systematically investigate the influence laws of each parameter on the wind field structure and snow drift deposition characteristics at tunnel portals and clarify the flow field response rules under different parameter configurations. Single-factor simulation results show that the wind deflector exerts distinct regulatory effects on the wind-snow flow field with different parameter settings: when L = 6 m, the disturbance zone of the wind deflector precisely covers the main wind flow development area in front of the tunnel portal, which effectively lifts the main incoming flow path, compresses the recirculation zone (length reduced from 45.8 m to 22.3 m), and reduces the settlement of snow particles, achieving the optimal comprehensive prevention effect; when β = 60°, the leeward wind speed at the tunnel portal is significantly increased to 10–12 m/s (from below 10 m/s), which effectively promotes the transport of snow particles and mitigates the accumulation risk, being the optimal inclination angle; when h = 2 m, the wind speed on both the windward and leeward sides of the tunnel portal is significantly improved, and the snow accumulation risk at the portal reaches the minimum. Orthogonal test results further quantify the influence degree of each parameter on the snow prevention effect, revealing that the horizontal distance from the tunnel portal is the most significant influencing factor. The optimal parameter combination of the wind deflector is determined as L = 6 m, β = 60°, and h = 2 m. Under this optimal combination, the snow phase volume fraction at 35 m on the leeward side of the tunnel portal is 0.0505, a 12.3% reduction compared with the non-deflector condition; the high-concentration snow accumulation zone is shifted 25 m leeward, and the high-value snow phase volume fraction area (>0.06) disappears completely, which can effectively alleviate the adverse impact of wind-blown snow disasters on the normal operation of tunnel portals. The research results reveal the regulation mechanism of wind deflector parameters on the wind-snow flow field at alpine tunnel portals and determine the optimal protective parameter combination, which can provide important theoretical reference and technical support for the prevention and control of wind-blown snow disasters at tunnel portals in similar alpine mountainous areas. Full article

This paper presents a side-by-side study of CFD predictions and experimental measurements for a novel counter-flow heat exchanger installed in the sidewall of a dishwasher (HEBS). The work aims to improve appliance efficiency by transferring heat from discharged hot wastewater to the incoming cold supply. Motivated by sustainability goals and tightening EU energy rules, the research targets the high losses typical of conventional machines. This approach combines detailed ANSYS Fluent 2022R2 simulations with controlled laboratory tests on a bespoke test rig. The measured data show a repeatable rise in the cold-water temperature of roughly 8 K, corresponding to an approximate 15% gain in thermal performance for the heat-recovery stage. While the simulations and experiments efficiently agree based on trends and qualitative behavior, there are noticeable quantitative differences in the total energy transfer, indicating the models need further refinement. The validation carried out here forms a solid basis for design optimization and for reducing energy consumption in household dishwashers. This work overcomes the limitations of previous studies which typically rely on external storage tanks or static heat recovery analysis. The primary novelty of this paper lies in the empirical validation of a high-efficiency heat exchanger integrated into the extremely constrained sidewall volume of the appliance, tested under transient, on-the-fly flow conditions, providing a verified methodology for constrained industrial applications. Full article

Link failures are the most common type of fault in software-defined networking (SDN), which is an extremely crucial aspect of SDN fault tolerance. Existing strategies include proactive and reactive approaches. Proactive schemes pre-deploy backup paths for fast recovery but may exhaust resources, while reactive schemes calculate paths upon failure, resulting in longer recovery but better outcomes. This paper proposes a single link failure recovery strategy that combines these two schemes, termed as flow-aware pro-reactive (FAPR), with the aim of achieving high-speed recovery while ensuring high-quality backup paths. Specifically, the controller adopts pro-VLAN to install backup paths for each link into switches, and precalculates multiple backup paths for each link in the controller before any link failures. In case of a link failure, pro-VLAN, i.e., a method based on the proactive approach, is initially utilized for swift recovery automatically without the involvement of the controller. Simultaneously, the controller analyzes types of affected flows based on the transport layer data, obtains several key network indicators of the backup paths, and then selects the most suitable path for different flows on the basis of the current network view. Simulation results and theoretical analysis show that the recovery time of the FAPR scheme reduces by over $65\%$ compared with the reactive scheme. The interruption rate of flows after fault recovery is reduced by $20\%$ and $50\%$ compared with the reactive and proactive schemes, respectively. In addition, due to the principle of pro-VLAN, the number of backup flow rules required is at most $85\%$ less than that required by the proactive scheme. In conclusion, FAPR promises the highest failure recovery speed and the lowest interruption rate among three methods, and helps to improve the quality of network services. Full article

Japan’s rivers are shaped by distinctive topography and abundant rainfall, and they face flooding and sediment supply escalation concerns under climate change. Small- and medium-sized rivers tend to catch unprecedented forces that exceed planned levels, leading to substantial widening and excavation. Thus, there is a demand for a method that is capable of managing significant flood flows over an extended period. The spur dike can maintain channel clearance by promoting erosion as well as providing bank protection. However, the effectiveness of this spur dike function has not been well studied in small- and medium-sized rivers and curved reaches. In this study, we evaluate the function of spur dikes in improving channel sustainability based on examples of small- and medium-sized rivers that have maintained their channel for more than ten years after spur dike installation. First, the applicability of the empirical rule was evaluated by comparing it with actual cases of erosion depths in curved sections in Japan. Next, one-dimensional simulations were performed to evaluate the sustainability of the section over a long period. Finally, a depth-averaged morphodynamic simulation, including the secondary flow effect, was applied to evaluate the location of the flow core and elevation changes due to the spur dike. The results showed that a slight difference in the ratio of river curvature radius to river width (r/B) caused the river channel to be erosive and sedimentary. The reasons for the difference were the cross-sectional expansion caused by the excavation of the bend and the difference in the plane flow regime caused by the shift of the flow core to the inside of the bend. Although it is structurally challenging to reproduce localized scour around a spur dike in a depth-averaged simulation, it is essential for designing to apply the simulation model and combine empirical knowledge. Full article

Autonomous driving in urban areas is challenging because it requires understanding vehicle movements, traffic rules, map topologies and unknown environments in the highly complex driving environment, and thus typical urban traffic scenarios include various potentially hazardous situations. Therefore, training self-driving cars by using traditional deep learning models not only requires the labelling of numerous datasets but also takes a large amount of time. Because of this, it is important to find better alternatives for effectively training self-driving cars to handle vehicle behavior and complex road shapes in dynamic environments and to follow line guidance information. In this paper, we propose a method for training a self-driving car in simulated urban traffic scenarios to be able to judge the road conditions on its own for crossing an unsignalized intersection. In order to identify the behavior of traffic flow at the intersection, we use the CARLA (CAR Learning to Act) self-driving car simulator to build the intersection environment and simulate the process of traffic operation. Moreover, we attempt to use the DDPG (Deep Deterministic Policy Gradient) and RDPG (Recurrent Deterministic Policy Gradient) learning algorithms of the DRL (Deep Reinforcement Learning) technology to train models based on the CNN (Convolutional Neural Network) architecture. Specifically, the observation image of the semantic segmentation camera installed on the self-driving car and the vehicle speed are used as the model input. Moreover, we design an appropriate reward mechanism for performing training according to the current situation of the self-driving car judged from sensing data of the obstacle sensor, collision sensor and lane invasion detector. Doing so can improve the convergence speed of the model to achieve the purpose of the self-driving car autonomously judging the driving paths so as to accomplish accurate and stable autonomous driving control. Full article

This study covers the critical concerns related to the sizing, selection, installation, maintenance, and testing of pressure safety valves (PSVs). The aim is to ensure the safety of pressurized systems, hydrostatic transmission systems, and hydraulic plants, including process plants, thermal power plants, and nuclear reactor systems. PSVs are devices that ensure the safety and reliability of pressurized vessels, lines, and systems during overpressure events. The task of selecting which PSV features are of greatest value for a specific purpose is complex—especially in the design of a high-pressure experimental thermal–hydraulic facility for hydrostatic and transient testing of the reactor system—when the systems are in the design and development phases and require qualification and demonstration to prove that they have reached a given level of technological readiness. The present study highlights the required steps for users to follow the associated rules, guidelines, and recommendations. As a part of this research, case studies are presented to help readers better understand the applicable strategy and standards. A discussion and a review of PSV performance degradation and failure are summarized to provide a better understanding of varied process applications and conditions, including fluid flow dynamics, boundary-layer formation and pressure drops, gas bubble formation and collapse, geometric configurations, inlet/outlet piping, abrupt pressure fluctuations, and acoustic resonance. Moreover, this study discusses the servicing and testing of PSVs in a multiphase pressurized system. Overall, it provides a basic overview of how PSVs ensure the safety of pressurized systems, supported by case studies and industrial practices. Full article

The proposal in the present research study is the result of a more than two-year process developed in a pallet manufacturing company for anchor enterprises in Southern Sonora, Mexico dedicated to beer production and export to the United States of America. Considering the high pallet demand for this supplier, a strategic plan was created in 2021, establishing an important project for developing technological solutions to improve decision making supported by graphical user interface and focused on sustainability. This study shows the application of system dynamics in all the wood and pallet manufacturing processes with a strategic sourcing supply chain. The method used for its development had the following stages: (1) developing the mapping process; (2) creating the causal loop diagram; (3) developing a flow and stock model with the representing mathematical equations; (4) simulating and validating current scenarios; (5) evaluating normal, optimistic, and pessimistic scenarios with multicriteria decision making using Technique to Order Preferences by Similarity and the Ideal Solution (TOPSIS) and Faire Un Choix Adéquat (FUCA); (6) building the graphical interface. The most relevant results for the company were having quantitative information regarding the pallet demand required by the main client for wood availability, which was the main restriction in the supply chain. The solution was based on four validation tests that allowed decision makers to support the production proposals considering the assistance of the dynamic models. The main conclusion demonstrated that using well-defined operation rules and policies—considering the installed capacity and pallet demand through the model solution—allows anticipating decisions on pallet quantity and reducing the risk of out-of-time deliveries. Full article

At present, there are very few vibration test designs for compressor stator blades in damped blade test research, and there is a lack of consideration of the holding ring structure of the blade installation. In recent years, compressor designs have become more elaborate, and their structures have become more compact. For improving compressor stator blade design, it is necessary to study the blade vibration response considering contact and friction. In this paper, a compressor stator blade vibration test system with a holding ring structure is designed and built. The composition of the system and the flow of vibration are tested. Then, the nonlinear vibration rules of the model stator blades are experimentally studied through the built test bench. The experimental conditions include excitation forces of 1 N, 2 N, 3 N and 4 N, respectively. At the same time, the normal load of the outer holding ring and the blade contact surface includes 10 N, 20 N, 30 N and 40 N working conditions. The nonlinear vibration law of the test model blade considering contact friction is analyzed using a numerical method and experimental data. The experimental data agree well with the numerical analysis results, and the relative error of measurement is basically less than 5%. It is concluded that the damping vibration rule of the test model blade is related to the exciting force applied by the exciter and the contact surface normal load applied by the adjusting bolt. When these two parameters change, the movement behavior of the contact surface will switch between macro-slip, fretting slip and even a viscous state. Therefore, the amplitude of the blade will change and show nonlinear vibration characteristics. The experimental data in this paper can provide a reference for research on stator ring vibration safety in compressors. Full article

Software-defined networking (SDN) enables dynamic management and flexible network control by employing reactive rule installation. Due to high power consumption and cost, current OpenFlow switches only support a limited number of flow rules, which is a major limitation for deploying massive fine-grained policies. This bottleneck can be exploited by attackers to launch saturation attacks to overflow the flow table. Moreover, flow table overflow can occur in the absence of malicious attackers. To cope with this, researchers have developed many proposals to relieve the load under benign conditions. Among them, the dynamic timeout mechanism is one of the most effective solutions. We notice that when the SDN controller adopts dynamic timeouts, existing flow table saturation attacks can fail, or even expose the attackers, due to inaccurate inferring results. In this paper, we extract the common features of dynamic timeout strategies and propose an advanced flow table saturation attack. We explore the definition of flow rule lifetime and use a timing-based side-channel to infer the timeout of flow rules. Moreover, we leverage the dynamic timeout mechanisms to proactively interfere with the decision of timeout values and perform an attack. We conduct extensive experiments in various settings to demonstrate its effectiveness. We also notice that some replacement strategies work differently when the controller assigns dynamic timeouts. The experiment results show that the attack can incur significant network performance degradation and carry out the attack in a stealthy manner. Full article

This article explores the use of battery energy storage in a transactive energy approach for a heavily solar-penetrated community. We hypothesize that the efficient market interactions between independently acting, fully automated agents (some equipped with battery energy storage) can result in both bill savings and improvements in power flow, without explicitly optimizing for power flow ahead of time. A test setting of nine typical residential prosumers and one heavily loaded prosumer is used. The heavily loaded prosumer initially experiences multiple undervoltage violations, and a 13.5 kWh battery is installed to alleviate the problem. Two profile-shaping strategies are compared. The first scenario uses greedy control that maximizes self-sufficiency, while the second scenario uses a local market to enable energy trading between participants and a rule-based trading and management agent for control. The results show that the first scenario made minimal improvements to power flow, but the second scenario eliminated all occurrences of under-voltage violations. Furthermore, the total amount of energy from the grid is reduced by 24.3%, and the amount of energy injected into the grid is reduced by 39.2%. This results in lower bills for every participant and a bill reduction of 16.7% for the community as a whole. Full article

Software-defined networking (SDN) has gained tremendous growth and can be exploited in different network scenarios, from data centers to wide-area 5G networks. It shifts control logic from the devices to a centralized entity (programmable controller) for efficient traffic monitoring and flow management. A software-based controller enforces rules and policies on the requests sent by forwarding elements; however, it cannot detect anomalous patterns in the network traffic. Due to this, the controller may install the flow rules against the anomalies, reducing the overall network performance. These anomalies may indicate threats to the network and decrease its performance and security. Machine learning (ML) approaches can identify such traffic flow patterns and predict the systems’ impending threats. We propose an ML-based service to predict traffic anomalies for software-defined networks in this work. We first create a large dataset for network traffic by modeling a programmable data center with a signature-based intrusion-detection system. The feature vectors are pre-processed and are constructed against each flow request by the forwarding element. Then, we input the feature vector of each request to a machine learning classifier for training to predict anomalies. Finally, we use the holdout cross-validation technique to evaluate the proposed approach. The evaluation results specify that the proposed approach is highly accurate. In contrast to baseline approaches (random prediction and zero rule), the performance improvement of the proposed approach in average accuracy, precision, recall, and f-measure is (54.14%, 65.30%, 81.63%, and 73.70%) and (4.61%, 11.13%, 9.45%, and 10.29%), respectively. Full article

This paper presents the impact of flow changes in the Warta River and water management rules regarding the Jeziorsko dam reservoir on the energy production by the hydropower plant in the period 1995–2021. The Jeziorsko dam reservoir was built in 1986. It is the second largest dam reservoir in Poland in terms of surface area. In 1994, a hydropower plant with an installed capacity of 4.89 MW started operation. The study results show the average annual energy production from 1995 to 2021 at a level of 18,718 MWh. On the other hand, energy production largely changed from year to year, from 12,432 MWh (in 2019) to 26,916 MWh (in 2001). The droughts that have occurred in the Warta River basin over the past two decades have had a major impact on energy production. As a consequence of the drought, it was not possible to maintain the required water level in the reservoir. Moreover, a change in the rules for the reservoir’s management that led to lower water levels in the reservoir by 1.5 m between April and June was important from the point of view of energy production. Improving the efficiency of energy production requires changing the rules of water management in the reservoir. More flexible reservoir operation schemes should be considered, including operational management based on meteorological and hydrological forecasts. Moreover, other criteria should also be considered, such as maintaining environmental flows, ensuring protection from flooding, and operating a nature reserve around the reservoir. Full article

Software-defined networking (SDN) is an innovative network architecture that splits the control and management planes from the data plane. It helps in simplifying network manageability and programmability, along with several other benefits. Due to the programmability features, SDN is gaining popularity in both academia and industry. However, this emerging paradigm has been facing diverse kinds of challenges during the SDN implementation process and with respect to adoption of existing technologies. This paper evaluates several existing approaches in SDN and compares and analyzes the findings. The paper is organized into seven categories, namely network testing and verification, flow rule installation mechanisms, network security and management issues related to SDN implementation, memory management studies, SDN simulators and emulators, SDN programming languages, and SDN controller platforms. Each category has significance in the implementation of SDN networks. During the implementation process, network testing and verification is very important to avoid packet violations and network inefficiencies. Similarly, consistent flow rule installation, especially in the case of policy change at the controller, needs to be carefully implemented. Effective network security and memory management, at both the network control and data planes, play a vital role in SDN. Furthermore, SDN simulation tools, controller platforms, and programming languages help academia and industry to implement and test their developed network applications. We also compare the existing SDN studies in detail in terms of classification and discuss their benefits and limitations. Finally, future research guidelines are provided, and the paper is concluded. Full article

Aiming at the problems of high missed-pickup rate and crushed rate caused by different types of peanut harvester pickup drums, by tracking a field comparative experiment from 2020 to 2021, the missed-pickup rate, missed-pickup quality distribution, crushed rate and quality distribution rule of pods with different degrees of crushing observed in two peanut varieties with different pickup drums were studied. Three kinds of pod-pickup drums were set up: axial flow (T1), tangential flow (T2) and tangential–axial flow (T3), and they were installed on the pickup harvester to form three kinds of pickup and harvest test stands. At the same time, a control test stand (CK) without pod-pickup drums was set up. Peanut varieties “Shanhua 9” and “Huayu22” and 10 water content levels were used. Using Origin2018 software, the missed-pickup rate, missed-pickup quality distribution, crushed rate and the quality distribution of pods with different degrees of crushing were statistically analyzed for the two peanut varieties harvested by different pickup drums. The results showed that the average missed-pickup rate was T1, T2 and T3, in order from small to large. The order of pickup quality from more to less was small pods, medium pods and large pods, which indicated that small pods were more likely to be missed. The average pod crushed rates for T1, T2 and T3 for Shanhua 9 were 2.06%, 2.19% and 2.45%, and those of T1, T2 and T3 for Huayu22 were 1.74%, 1.91% and 2.23%, so the order of pod crushed rates from small to large was T1, T2 and T3. At the same time, the crushed rate of T1, T2 and T3 to the two varieties decreased obviously with the decrease in water content. After the T1 test, the proportion of medium and severely crushed pods was the least, followed by T2, and the highest was T3. At the same time, the higher the water content, the higher the proportion of medium and severely crushed pods, and the proportion of medium and severely crushed pods after the Huayu22 test was less than that of the Shanhua 9 test. Full article

In reactive mode software-defined networking (SDN) networks, a new initiated flow requires back-and-forth communications between the controller and the switches along the forwarding route. As SDN is getting popularly accepted, many studies have reported on how to reduce the amount of communication traffic and to release the controller’s loading. Several techniques have been proposed, such as proactive and active mode integration, MPLS adoption, and various forwarding rule installation techniques. In this paper, we adopt the idea of the tunnel penetration technique, called the tunnel boring machine in SDN or SDN-TBM, to effectively cut down the traffic between switches and the controller as well as to speed up packet delivery. Using the TBM mechanism, the communication symmetry between the controller and the switches on the path is broken and transformed into asymmetry. Only the first and last switches of each application flow need to make forwarding queries to the controller, and all intermediate switches simply forward packets consisting of the forwarding information needed to determine the next-hop switch. An M/M/1 queueing model is developed to verify the feasibility and efficiency of the proposal. Under the simulation of more than a million flows with 3–8 intermediate switches, the packet sojourn time using SDN-TBM mechanism is less than that of adopting the conventional SDN and JumpFlow model. Additionally, by adopting SDN-TBM, both the number of packet-in and packet-out packets and the controller’s loading are significantly reduced. Full article