Search Results (10,022)

The detailed n-heptane mechanism, which is widely used today, is suitable for a wide range of operating conditions. However, due to the large model involved, it is difficult to use this mechanism for computational fluid dynamics (CFD) simulation. In addition, the prediction accuracy of the existing simplified mechanism cannot meet simulation requirements with respect to low-temperature combustion and the negative temperature coefficient region. In this study, we sought to solve these problems by constructing a new simplified mechanism (NC2024) of the n-heptane chemical reaction based on the mechanism of Kuiwen Zhang using path analysis and sensitivity analysis. The mechanism involves 72 substances and 126 reactions. A comparison with the commonly used mechanism and an analysis of experimental data revealed that the NC2024 mechanism delivers high accuracy in predicting the ignition delay period under the low- to high-temperature conditions of 600–1100 K and a large pressure range of 13.5–42 bar and thus meets the accuracy requirements for CFD simulation of diesel low-temperature combustion. Full article

Advances in numerical modeling are essential for heat-transfer applications in electronics cooling, renewable energy, and sustainable construction. This review explores key methods like Computational Fluid Dynamics (CFD), the Finite Element Method (FEM), the Finite Volume Method (FVM), and multiphysics modeling, alongside emerging strategies such as Adaptive Mesh Refinement (AMR), machine learning (ML), reduced-order modeling (ROM), and high-performance computing (HPC). While these techniques improve accuracy and efficiency, they also increase computational energy demands, contributing to a growing carbon footprint and sustainability concerns. Sustainable computing practices, including energy-efficient algorithms and renewable-powered data centers, offer potential solutions. Additionally, the increasing energy consumption in numerical modeling highlights the need for optimization strategies to mitigate environmental impact. Future directions point to quantum computing, adaptive models, and green computing as pathways to sustainable thermal management modeling. This study systematically reviews the latest advancements in numerical heat-transfer modeling and, for the first time, provides an in-depth exploration of the roles of computational energy optimization and green computing in thermal management. This review outlines a roadmap for efficient, environmentally responsible heat-transfer models to meet evolving demands. Full article

Because of the introduction of significant amounts of electricity from intermittent energy, such as solar and wind, on power grids, hydraulic turbines undergo more transient operation with varying rotation speeds. Start and stop sequences are known to induce significant mechanical stress in the runner, decreasing its lifespan. Complex fluid–structure interactions are responsible for those high-stress levels, but the precise mechanisms are still elusive, even if many experimental and numerical studies were devoted to the subject. One possible mechanism identified through limited measurements on large turbines operating in powerhouses is rotor–stator interactions. It is already known that rotor–stator interaction (RSI) in constant-speed operating conditions can lead to runner failure when the RSI frequency is close to the natural frequencies of specific structural modes. Start and stop sequence investigations show that RSI can induce a transient resonance while the runner is accelerating/decelerating, which generates a frequency sweep that excites the structure. Studying transient RSI-induced resonance of structural modes associated with hydraulic turbine runners is complex because of the geometry and the potential impacts from other flow-induced excitations. This paper presents the development and validation of an experimental setup specifically designed to reproduce RSI-induced resonances in a rotating circular structure with cyclic periodicity mimicking the structural behavior of a Francis runner. Such a setup does not exist in the literature and will be beneficial for studying RSI during speed variations, with the potential to provide valuable insights into the dynamic behavior of turbines during transient conditions. The paper outlines the different design steps and the construction and validation of the experiment and its simplified runner. It presents important results from preliminary analyses that outline the approach’s success in investigating transient RSI in hydraulic turbines. Full article

This study investigated the complex interactions among tsunamis, debris, and coastal building structures under extreme hydrodynamic conditions. We performed numerical simulations to explore the influence of varying wave conditions, debris, and building designs to identify the most vulnerable parts of a building structure. The three-dimensional coupled fluid–structure–sediment–seabed interaction model (FS3M) was employed to simulate these interactions and validated against physical experimental data to ensure accuracy. The results revealed that debris significantly altered the wave impact dynamics, increasing the force exerted on buildings regardless of their structural features. This study provides relevant insights into the effectiveness of different building layouts in mitigating damage, highlighting the critical role of buildings with internal walls perpendicular to the wave direction, which significantly mitigated the tsunami’s impact at specific regions. Full article

Power generation is an important part of air vehicle energy management when developing long-endurance and reusable hypersonic aircraft. In order to utilize an air turbine power generation system on board, fuel-based rotating cooling has been researched to cool the turbine’s rotor blades. For fuel-cooling air turbines, each blade corresponds to a separate cooling channel. All the separate cooling channels cross together and form a distributary cavity and a confluence cavity in the center of the disk. In order to determine the flow characteristics in the distributary and confluence cavities, computational fluid dynamics (CFD) simulations using the shear–stress–transport turbulence model were carried out under the conditions of different rotating speeds and different mass flow rates. The results showed great differences between non-rotating flow and rotating flow conditions in the distributary and confluence cavities. The flow in the distributary and confluence cavities has rotational velocity, with obvious layering distribution regularity. Moreover, a high-speed rotational flow surface is formed in the confluence cavity of the original structure, due to the combined functions of centrifugal force, inertia, and the Coriolis force. Great pressure loss occurs when fluid passes through the high-speed rotational flow surface. This pressure loss increases with the increase in rotating speed and mass flow rate. Finally, four structures were compared, and an optimal structure with a separated outlet channel was identified as the best structure to eliminate this great pressure loss. Full article

Geometrical solutions for aerodynamic limitations comprise a major development towards improving the wind energy capture efficiency and aerodynamic performance of wind turbines. However, the implementation of some mechanisms such as considerably thin airfoils have been a hurdle due to the available manufacturing methods and cost effectiveness. Moreover, the analysis has been mostly focused on analyzing and optimizing the aerodynamic aspect of wind turbines, independently of the structural performance necessary to support the optimized aerodynamic performance. Therefore, this paper analyzes the fluid–structure interaction (FSI) of a wind turbine with a relatively thin airfoil section using computational fluid dynamics (CFD) and finite element analysis (FEA) to evaluate the total displacement as well as the stresses acting on the blade as the results of the aerodynamic pressure distribution. Using the structural design, geometrical scales, and material properties of baseline model, the structural performance reflected by the thin airfoil design is isolated. Not only did the thin airfoil reduce the volume of the material and, therefore, the weight of the modified blade, but it was also able to provide high rigidity, which is necessary to support better aerodynamic performance. This was found to be influenced by the structural shape of the turbine blade, resulting in a maximum total deformation of less than 5.9 × 10⁻⁷ m, which is very negligible in comparison to the scale of the turbine blade in this analysis. Full article

To enhance oil and gas recovery, a novel hydrophobic terpolymer was synthesized via free radical polymerization. The terpolymer consists of acrylamide, acrylic acid, and hydrophobic monomers, and is used as a hydraulic fracturing fluid thickener for freshwater environments. Hydrophobic groups were introduced into terpolymer to improve its tackiness and temperature resistance. The conformation and key parameters of hydrophobic monomers at different temperatures were investigated through a combination of experiments and molecular dynamics simulations. These methods were employed to elucidate the mechanism behind its high-temperature resistance. The experiment results show that, at concentrations between 0.2% and 0.4%, significant intermolecular aggregation occurs, leading to a substantial increase in solution viscosity. Configuring the base fluid of synthetic polymer fracturing fluid with 1% doping, the apparent viscosities of the base fluid were 129.23 mPa·s and 133.11 mPa·s, respectively. The viscosity increase rate was 97%. The base fluid was crosslinked with 1.5% organozirconium crosslinker to form a gel. The controlled loss coefficient and loss velocity of the filter cake were C₃ = 0.84 × 10⁻³ m/min^1/2 and v_c = 1.40 × 10⁻⁴ m/min at 90 °C, meeting the technical requirements for water-based fracturing fluid. Molecular dynamics simulations revealed that the radius of gyration of the hydrophobically linked polymer chain segments decreases as the temperature increases. This is due to the increased thermal motion of the polymer chain segments, resulting in less stretching and intertwining of the chains. As a result, the polymer chains move more freely, which decreases the viscosity of the solution. In conclusion, the proposed fracturing fluid thickener system demonstrates excellent overall performance and shows significant potential for application in oil and gas recovery. Full article

In the field of electromagnetic design, it is sometimes necessary to search for the optimal design solution (i.e., the optimal solution) within a large solution space to complete the optimization. However, traditional optimization methods are not only slow in searching for the solution space but are also prone to becoming trapped in local optima, leading to optimization failure. This paper proposes a dual-population genetic algorithm to quickly find the optimal solution for electromagnetic optimization problems in large solution spaces. The method involves two populations: the first population uses the powerful dynamic decision-making ability of reinforcement learning to adjust the crossover probability, making the optimization process more stable and enhancing the global optimization capability of the algorithm. The second population accelerates the convergence speed of the algorithm by employing a “leader dominance” mechanism, allowing the population to quickly approach the optimal solution. The two populations are integrated through an immigration operator, improving optimization efficiency. The effectiveness of the proposed method is demonstrated through the optimization design of an electromagnetic metasurface material. Furthermore, the method designed in this paper is not limited to the electromagnetic field and has practical value in other engineering optimization areas, such as vehicle routing optimization, energy system optimization, and fluid dynamics optimization, etc. Full article

This study systematically investigates the formation mechanism and development characteristics of the “foamy oil” phenomenon during pressure depletion development of high-viscosity crude oil through a combination of physical experiments and numerical simulations. Using Venezuelan foamy oil as the research subject, an innovative heterogeneous pore-etched glass model was constructed to simulate the pressure depletion process, revealing for the first time that bubble growth predominantly occurs during the migration stage. Experimental results demonstrate that heavy components significantly delay degassing by stabilizing gas–liquid interfaces, while the continuous gas–liquid diffusion effect explains the unique development characteristics of foamy oil—high oil recovery and delayed phase transition—from a microscopic perspective. A multi-scale coupling analysis method was established: molecular-scale simulations were employed to model component diffusion behavior. By improving the traditional Volume of Fluid (VOF) method and introducing diffusion coefficients, a synergistic model integrating a single momentum equation and fluid volume fraction was developed to quantitatively characterize the dynamic evolution of bubbles. Simulation results indicate significant differences in dominant controlling factors: oil phase viscosity has the greatest influence (accounting for ~50%), followed by gas component content (~35%), and interfacial tension the least (~15%). Based on multi-factor coupling analysis, an empirical formula for bubble growth incorporating diffusion coefficients was proposed, elucidating the intrinsic mechanism by which heavy components induce unique development effects through interfacial stabilization, viscous inhibition, and dynamic diffusion. This research breaks through the limitations of traditional production dynamic analysis, establishing a theoretical model for foamy oil development from the perspective of molecular-phase behavior combined with flow characteristics. It not only provides a rational explanation for the “high oil production, low gas production” phenomenon but also offers theoretical support for optimizing extraction processes (e.g., gas component regulation, viscosity control) through quantified parameter weightings. The findings hold significant scientific value for advancing heavy oil recovery theory and guiding efficient foamy oil development. Future work will extend to studying multiphase flow coupling mechanisms in porous media, laying a theoretical foundation for intelligent control technology development. Full article

In complex marine environments, accurate prediction of maneuvering motion is crucial for the precise control of intelligent ships. This study aims to enhance the predictive capabilities of maneuvering motion for intelligent ships in such environments. We propose a novel maneuvering motion prediction method based on Long Short-Term Memory (LSTM) and Multi-Head Attention Mechanisms (MHAM). To construct a foundational dataset, we integrate Computational Fluid Dynamics (CFD) numerical simulation technology to develop a mathematical model of actual ship maneuvering motions influenced by wind, waves, and currents. We simulate typical operating conditions to acquire relevant data. To emulate real marine environmental noise and data loss phenomena, we introduce Ornstein–Uhlenbeck (OU) noise and random occlusion noise into the data and apply the MaxAbsScaler method for dataset normalization. Subsequently, we develop a black-box model for intelligent ship maneuvering motion prediction based on LSTM networks and Multi-Head Attention Mechanisms. We conduct a comprehensive analysis and discussion of the model structure and hyperparameters, iteratively optimize the model, and compare the optimized model with standalone LSTM and MHAM approaches. Finally, we perform generalization testing on the optimized motion prediction model using test sets for zigzag and turning conditions. The results demonstrate that our proposed model significantly improves the accuracy of ship maneuvering predictions compared to standalone LSTM and MHAM algorithms and exhibits superior generalization performance. Full article

The CFD code C3d was used to investigate the operation of a routine utility flare at low and high gas firing rates in an oil field in Iraq. This code was developed for the analysis of transient flares, enables the simulation of flare operation, and offers detailed estimates of the flame shape and the emissions produced. In this work, the numerical simulations included two flare gas rates, 9 t/h (2.5 kg/s) and 45 t/h (12.5 kg/s), under three crosswind conditions (4 m/s, 8 m/s, and 14 m/ s) and using three stack heights (35 m, 45 m, and 55 m). The results of this work provided insights into the flame shape and size, pollutant types and dispersion, and ground heat radiation levels from the flare. The safety analysis found that ground-level heat increased with higher flare gas rates and decreased with higher stack heights. The stack height of 55 m and the lower gas firing rate of 9 t/h were identified as the safest operating conditions, as they provided lower ground-level heat compared to the higher flare gas rate of 45 t/h. The heat radiation at a stack height of 55 m during normal firing rates remained below 1600 W/m², which was within the safe continuous exposure limit for personnel not wearing protective clothing. This limit is in accordance with the recommended safety guidelines for personnel and equipment as outlined in API 521. Likewise, the environmental analysis showed that the plume size increased with increasing flare gas rate, while pollutant dispersion intensified with stronger crosswinds. When comparing the two gas firing rates, in the case of 9 t/h, there was a smaller plume and less pollutant dispersion, which illustrated a relatively lower impact on the environment. Full article

This study optimized Chinese cabbage (Brassica rapa L. ssp. pekinensis) storage design by integrating K-means clustering, heat transfer analysis, and respiratory heat effects. A morphological assessment identified three clusters: class 1 (73.32 ± 3.34 cm length, 46.73 ± 2.24 cm width, 1503.20 ± 118.39 g weight), class 2 (82.67 ± 1.17 cm, 51.89 ± 2.37 cm, 2132.48 ± 127.16 g), and class 3 (89.17 ± 2.45 cm, 58.67 ± 2.77 cm, 2826.37 ± 121.25 g), with a silhouette coefficient of 0.87 confirming robust clustering. The CO₂, relative humidity, and airflow analysis revealed hotspots and imbalances. Heat transfer modeling, incorporating respiratory heat, closely matched experimental data (RMSE < 0.54 °C), while excluding it caused deviations in storage. The validated model informed a modified geometry for scale-up CFD modeling, reducing the convergence time by 38% and the RAM usage by 30%. Three commercial storage designs were evaluated: fully filled, batch filled (50:50), and repositioned air conditioning with batch filling. The latter achieved a faster equilibrium (4.1 °C in 17 h 15 min vs. 21 h 30 min for fully packed) and improved airflow, reducing the hot zones. This study highlights the importance of integrating cabbage morphology, environmental factors, and respiratory heat into storage design to enhance cooling efficiency and product quality. Full article

Controlling oil well pressure during drilling is one of the most complex and hazardous processes in the exploration stage. The drilling system undergoes constant variations, influenced by factors such as drilling depth, which in turn affects other process parameters. Consequently, applying a time-invariant control strategy becomes impractical. This study aimed to identify the PID parameters necessary to regulate bottom-hole pressure during drilling across different operating depths, with the goal of maintaining system stability and robustness. To achieve this, the parameters were tested using a Gain Scheduling (GS) controller, which adjusted the control gains according to various operating points. In the first section, the development of a mathematical model of the process, based on fluid mechanics, is presented. Linearizing this model introduced an integrating element, which complicated the process dynamics. In the second section, we present the design of the controller using the Internal Model Control (IMC) tuning methodology to address the integration challenges. Finally, PID parameters for different drilling depths were obtained and integrated into the GS controller via Matlab Simulink. The controller’s performance was then evaluated through simulations of typical drilling issues, such as simulated disturbances, confirming its viability. The GS-controlled system was compared to a system using an adaptive controller, demonstrating superior performance in the former. Full article

The relevance is introducing fourth generation district heating (4GDH), which decreases operation and maintenance costs by utilizing the efficiency of low temperature district heating (LTDH). The aim is to develop a methodology allowing for a more flexible heat demand model and accurate function describing the relationship between outdoor temperature and heat demand. It is represented by a black-box model based on historical data collected from heating, ventilation, and air conditioning (HVAC) systems. Energy delivery/consumption is analyzed with the help of a set of statistical and regression formulas. The analysis of operational data is then transformed to methodology to regulate heat supply with combined heat-and-power (CHP) generation. The key features are that the model takes into account thermal capacity and type of substation; the district heating (DH) plant is not assumed to have a fixed return temperature and generation profile. The novelty is an emphasis on DH operation and introduction of statistics into a dynamic simulation model. With no abnormal buildings, higher accuracy of modeling is achieved. Most of the consumers are pretty similar in thermal response, even though specific energy demand and heated volume may differ. Heat demand of an old building is better simulated with discrete regression, while those with pump-equipped substations are modeled with linear regression. Full article

This study investigates the time-resolved aerodynamics in the cavity regions of a full-scale, high-speed, low-pressure turbine stage representative of geared turbofan engines. The turbine stage is tested in the von Karman Institute’s short-duration rotating facility at different purge rates (PR) injected through the upstream hub cavity. Spectra from the shroud and downstream hub cavity show perturbations linked to blade passing frequency and rotor speed. Asynchronous flow structures associated with ingress/egress mechanisms are observed in the rim seal of the purged cavity. At 0% PR, the ingress region extends to the entire rim seal, and pressure fluctuations are maximized. At 1% PR, the instability is suppressed and the cavity is sealed. At 0.5%, the rim-seal instability exhibits multiple peaks in the spectra, each corresponding to a state of the instability. Kelvin–Helmholtz instabilities are identified as trigger mechanisms. A novel technique based on the properties of the cross-power spectral density is developed to determine the speed and wavelength of the rotating structures, achieving higher precision than the commonly used cross-correlation method. Moreover, unlike the standard methodology, this approach allows researchers to calculate the structure characteristics for all the instability states. Spectral analysis at the turbine outlet shows that rim-seal-induced instabilities propagate into regions occupied by secondary flows. A methodology is proposed to quantify the magnitude of the induced fluctuations, showing that the interaction with secondary flows amplifies the instability at the stage outlet. Full article