Tank Process Research Articles

Dynamic Response and Damage Analysis of a Large Steel Tank Impacted by an Explosive Fragment

Abstract The fragments generated by explosions of storage tanks in chemical industrial parks may cause perforations or dents in adjacent tanks and trigger a domino effect. This paper determined reasonable fragment parameters based on the statistical laws of accidents and empirical formulas. The dynamic response process of large steel tanks impacted by fragments was simulated with ls-dyna. The typical impact process and results were analyzed in detail, and the damage laws of the tanks were discussed under various filling coefficients, volumes, fragment velocities, and impact angles. The results indicate that the inertial resistance of the inner liquid shortens the impact duration. Multiple collisions occur between the fragment and tank during impact, and the impact process involves three stages: initial collision, crushing and collision, and separation flight. The impact center displacement shows a fast and then slow reduction trend as the liquid level height increases, and the damage to the tank is negatively correlated with the liquid level height. The damage is lower when the tank volume is larger in an empty tank or at a high liquid level, while the damage instead increases when the volume exceeds 5000 m3 at a low liquid level. The peak impact force of the end-cap fragment is greatest when frontal impact occurs. Fragment flipping and curling occur at 45 deg and 90 deg impact, respectively. As the vertical impact angle increases from 0 deg to 90 deg, the fragment impact mode changes from initial frontal impact to flip detachment and finally to curling deformation.

Numerical analysis on phase change material melting process of a conical spiral tube energy storage tank

Numerical analysis on phase change material melting process of a conical spiral tube energy storage tank

Preventive Maintenance Strategy Prediction of the Firewater Systems Based on the Pythagorean Fuzzy Cost–Benefit–Safety Analysis and Fuzzy Dematel

The firewater system is a complex system associated with the safety process of Hydrogen storage tanks. Predicting preventive maintenance strategies is essential to ensure the long-term reliability of this system. Therefore, it is necessary to evaluate the multistate reliability of the firewater system in order to predict preventive maintenance strategies and provide safety measures. A polymorphic fuzzy fault tree analysis (PFFTA) for the risk analysis of complex systems has attracted much attention because of its powerful evaluation capability and its ability to analyze relationships among basic events. However, obtaining multistate failure probability (MFP) data for basic events in PFFTA has always been a major challenge. It is also difficult to quantify the minimum cut set (MCS) in PFFTA and determine the critical components for selecting a preventive maintenance strategy. In this study, we propose the Pythagorean fuzzy cost–benefit–safety analysis by using the PFFTA, an improved consistency aggregation method (I-CAM), and fuzzy Dematel for a predictive preventive maintenance strategy. In the proposed approach, the I-CAM method was used to collect and aggregate weights of experts’ opinions to evaluate the MFP of basic events in PFFTA. As a result, a triptych cost–benefit–safety analysis based on Pythagorean fuzzy sets (PFSs) and the sum-product method (SPM) was estimated to reduce expert subjectivity, support an improved cost-effectiveness index to rank critical components, and fuzzy Dematel to evaluate influence of proposed preventive maintenance actions. To clarify the effectiveness and feasibility of the proposed methodology, a case study of the firewater system related to the plant is located in SONELGAZ electricity power plant (OUMACHE Unit) was demonstrated. Both evaluations of the cost–benefit–safety analysis of the critical component were performed, and selected the influence of preventive maintenance strategy of the firewater system was predicted.

Investigation of Interlayer Thermal Coupling of Multilayer Insulation in Spacecraft Equipment

In general, for installing multilayer insulation (MLI) blankets on curved spacecraft equipment, creating a pattern that has multiple sectors is necessary because of the impossibility of establishing a single piece of MLI. The sector area of the MLI contains numerous seams and sewing. Therefore, prediction of overall performance or effective emittance is not simply possible, and they need to be tested in some experimental ways. The aim of the current research is to present a methodology for determining the conductivity between layers in both nonsewing and sewing regions of MLI to correctly estimate the effective emittance coefficient and the thermal behavior of MLI. Firstly, by conducting two experimental tests, both sewn and nonsewn square MLIs’ effective emittance coefficients are computed. In the second step, the conductive thermal coupling coefficients of nonsewing and sewing regions are determined as 1.615 and 1.95 W/(m2⋅K) respectively, utilizing experimental data. In the third step, a spherical geometry fuel tank is selected as a case study, and these coefficients are utilized in the simulation process of an MLI tank. Finally, the overall effective emittance coefficient of that tank is determined. The results indicate that the effective emittance is reduced by about 8%.

Development of a rapid analysis system for pre-cooling process of large LNG full-capacity storage tank

Abstract In this paper, a quick analysis system for the pre-cooling process of large LNG tank was developed, based on ANSYS-Python. The system has the functions of establishing geometric model automatically, dividing grid automatically and solving automatically. Operation of the system is simple with high efficiency. Comparison with the field data results found that the quick analysis system is accurate to meet the requirements of engineering application. The quick analysis system is helpful to optimize the pre-cooling process and the structure of large LNG full-capacity tanks

Selection of optimal schemes for the inerting process of cargo tanks of gas carriers

Selection of optimal schemes for the inerting process of cargo tanks of gas carriers

Joint state and process inputs estimation for state-space models with Student’s t-distribution

This paper proposes a joint state and unknown inputs (UIs) discrete-time estimation method for industrial processes, represented by a state-space model. To cope with the outliers in process data, the measurement noise is characterized by the Student’s t-distribution. The identification of UIs is accomplished through the recursive expectation–maximization (REM) approach. Specifically, in the E-step, a recursively calculated Q-function is formulated by the maximum likelihood criterion, and the states and the variance scale factor are estimated iteratively. In the M-step, UIs are updated analytically together with the degree of freedom is updated approximately. The effectiveness of the proposed algorithm is validated using a quadruple water tank process and a continuous stirred tank reactor. It shows that the proposed method significantly enhances the robustness and estimation accuracy of state and UIs in industrial processes, effectively handling outliers and reducing computational demands for real-time applications.

Heat transfer characteristics of oil receiving and delivering process in crude oil storage tanks

The study used numerical simulation methods to investigate the influence of different oil receiving and delivering cases on the non-uniform physical field within the storage tank. The results showed that the evolution of the physical field can be divided into three stages: diffusion, suppression, and equilibrium. The computational domain was divided into three zones based on the crude oil heating rate: significant influence zone, indirect influence zone, and minimal influence zone, and the indirect influence zone exhibits the most pronounced variations in velocity and temperature. The process of receiving oil with high-flow rate and low-temperature was found to be more conducive to the full use of heat in the tank when the heat exchanging quantity per unit time was the same. The synergistic effect of tubular heating and oil receiving and delivering resulted in a 21 % higher average temperature increase rate than the sum of the two processes. Finally, the study quantitatively described the linear relationship between the average temperature in each region and factors such as oil inlet velocity, oil receiving temperature, oil receiving and delivering time, and heating tube temperature, providing theoretical guidance for process planning in actual oil storage tank receiving and delivering.

Retraction Note: Soft computing-based fuzzy integral sliding mode control: a real-time investigation on a conical tank process

Retraction Note: Soft computing-based fuzzy integral sliding mode control: a real-time investigation on a conical tank process

Exploring innovative strategies for precipitation extent enhancement in a downscaled Bayer process tank

AbstractThe Bayer process is a cornerstone of alumina production, and its precipitation stage holds the key to both efficiency and product quality. In this study, we embarked on a comprehensive exploration of strategies to enhance the precipitation extent of aluminium hydroxide, a pivotal step in the Bayer process. Utilizing a newly constructed reactor, along with experiments using reactors in series, we rigorously experimented with various factors, including the addition of hydrogen peroxide (H2O2) as an enhancer, seed activation methods, the integration of a hydrocyclone within the processing unit, the application of a magnetic field, and the injection of supersaturated liquor midway through the process. These diverse strategies were systematically assessed to decipher their individual and synergistic effects on precipitation extent. Our research aims to uncover the optimal conditions for maximizing alumina precipitation while maintaining product quality and seed particle stability. By offering new insights and practical solutions, this study contributes to the ongoing advancement of alumina production within the Bayer process.

Thermal Energy Storage With Horizontal Thermocline Tank for Sludge Drying Application

Solar thermal technologies can be an attractive option for the decarbonization of process heat applications; in particular, thermal energy storage is a high value proposition for continuous processes that may operate at a range of thermal conditions. A thermal-fluid model is developed to investigate the buoyant flow in a horizontal thermocline storage tank for a sludge-drying application. The process conditions and tank geometry considered are unique compared to the domestic water heating application typically considered in the literature and well suited for parabolic trough collectors. It was found that good separation of hot and cold fluids can be achieved with the long horizontal tank geometry depending on the inlet configuration. Uniform flow distribution along the length of the tank is required to establish a thermocline. Assuming desirable inlet conditions can be achieved, the tank outlet temperature predicted by the thermal-fluid model shows good agreement with the system-level performance model.

Study on Rapid Simulation of the Pre-Cooling Process of a Large LNG Storage Tank with the Consideration of Digital Twin Requirements

The pre-cooling of a large LNG storage tank involves complex phenomena such as heat transfer, low-temperature flow, gas displacement, and vaporization. The whole pre-cooling process could take up to 50 h. For large-scale, full-capacity storage tanks, it is particularly important to accurately control the pre-cooling temperature. Digital twin technology can characterize and predict the full life cycle parameters from the beginning of pre-cooling development to the end and even the appearance of damage in real time. The construction of a digital twin platform requires a large number of data samples in order to predict the operating state of the device. Therefore, a simulation method with high computational efficiency for the pre-cooling process of LNG tanks is of great importance. In this paper, the mixture model and discrete phase model (DPM) are applied to simulate the pre-cooling process of a large LNG full-capacity tank. Following Euler–Lagrange, the DPM greatly simplifies the solution process. Compared with the experimental results, the maximum error of the DPM simulation results is less than 11%. Such a highly efficient simulation method for the large LNG full-capacity storage tank can make it possible to build the digital twin platform that needs hundreds of data model samples.

Coupled modeling and simulation of tank self-pressurization and thermal stratification

Numerical analysis of thermo-fluid dynamics for cryogenic propellant storage primarily consists of nodal and computational fluid dynamics (CFD) modeling approaches. While nodal approaches prioritize faster computation over fidelity, CFD approaches promise accuracy and fidelity at the expense of significant computational resources. This paper presents an efficient coupling methodology developed to facilitate the simulation of a long-term self-pressurization process of a cryogenic propellant tank as well as associated thermal stratification phenomenon under both normal and reduced gravity conditions. Key highlight of the methodology is the development of a coupling scheme based on a domain decomposition approach that separates the tank into two computational regions at the liquid-vapor interface. SINDA/FLUINT, the nodal code, is utilized to simulate the liquid region, while ANSYS Fluent, the CFD code, handles the vapor region. A data exchange algorithm was developed to compute required boundary conditions for each region using the local thermodynamic properties of assumed infinitely thin interface. The coupling between the nodal and CFD codes was demonstrated by simulating a self-pressurization process in a small size tank using hydrogen as the working fluid. A sensitivity study on the grid sizing and coupling time step was conducted to determine appropriate spatial and ensure a divergent-free explicit data exchange time step size. Using the coupling approach, two numerical case studies were performed to study tank self-pressurization by considering two initial hydrogen fill levels. The effectiveness and efficiency of the coupling methodology was assessed by comparing the temperature and pressure evolution results of the coupled simulation with those obtained solely from the CFD simulation. Results showed that the coupling scheme and data exchange algorithm were successfully implemented, and the coupled simulation agreed well with the CFD simulations. In addition, a stratification number was used to characterize the transient dynamic development of the thermal stratification. Lastly, the computational costs associated with both approaches were compared. Significant reductions in simulation time were achieved for both cases.

Fluid-Solid-Thermal Coupled Freezing Modeling Test of Soil under the Low-Temperature Condition of LNG Storage Tank

Due to the extensive utilization of liquid nature gas (abbreviated as LNG) resources and a multitude of considerations, LNG storage tanks are gradually transitioning towards smaller footprints and heightened safety standards. Consequently, underground LNG storage tanks are being designed and constructed. However, underground LNG storage tanks release a considerable quantity of cold into the ground under both accidental and normal conditions. The influence of cold results in the ground freezing, which further compromises the safety of the structure. Existing research has neglected to consider the effects of this. This oversight could potentially lead to serious safety accidents. In this work, a complete set of experiments using a novel LNG underground storage tank fluid-solid-thermal coupled cryogenic leakage scale model were conducted for the first time to simulate the effect of the tank on the soil temperature field, stress field, and displacement field and to analyze the development of the three fields and the results of the effect. This research helps the related personnel to better design, construct, and evaluate the LNG underground storage tanks to avoid the catastrophic engineering risks associated with cryogenic leakage and helps to improve the design process of LNG underground storage tanks.

Study of Condensation during Direct Contact between Steam and Water in Pressure-Relief Tank

Direct contact condensation (DCC) is a phenomenon observed when steam interacts with subcooled water, exhibiting higher heat and mass transfer rates compared to wall condensation. It has garnered significant interest across industries such as nuclear, chemical, and power due to its advantageous characteristics. In the context of pressure-relief tanks, understanding and optimizing the DCC process are critical for safety and efficiency. The efficiency of pressure-relief tanks depends on the amount of steam condensed per unit of time, which directly affects their operational parameters and design. This study focuses on investigating the direct gas–liquid contact condensation process in pressure-relief tanks using computational fluid dynamics (CFD). Through experimental validation and a sensitivity analysis, the study provides insights into the influence of inlet steam parameters and basin temperature on the steam plume characteristics. Furthermore, steady-state and transient calculation models are developed to simulate the behaviour of the pressure-relief tank, providing valuable data for safety analysis and design optimization. There is a relatively high-pressure area in the upper part of the bubble hole of the pressure-relief tube, and the value increases as it is closer to the holes. The steam velocity in the bubbling hole near the 90° elbow position is higher. This study contributes to the understanding of steam condensation dynamics in pressure-relief tanks. When the steam emission and pressure are fixed, the equilibrium temperature increases linearly as the initial temperature increases (where a = 1, b = 20 in y = a x+ b correlation), the equilibrium pressure increases nearly exponentially, and the equilibrium gas volume decreases. When the steam emission and initial temperature are fixed, the equilibrium temperature does not change as the steam discharge pressure increases. The correlations between the predicted equilibrium parameters and the inlet steam parameters and tank temperature provide valuable insights for optimizing a pressure-relief tank design and improving the operational safety in diverse industrial contexts.

IoT based Water Tank Cleaner using STM32

Water tanks are essential for storing and supplying clean water in both residential and industrial settings. However, over time, these tanks can accumulate sediment, algae, and other contaminants that can compromise water quality. Cleaning and maintaining water tanks is a critical task to ensure the supply of safe and clean water to consumers. The IoT-Based Water Tank Cleaner using STM32 project aims to address this issue by developing an innovative solution that automates the cleaning process of water tanks. This project leverages the power of the Internet of Things (IoT) and the capabilities of the STM32 microcontroller to create an intelligent and efficient water tank cleaning system. This project presents an innovative solution for water tank cleaning using the STM32 microcontroller and IoT (Internet of Things) technology. The proposed system automates the process of cleaning and monitoring water tanks, ensuring efficient operation and minimizing manual intervention. Water scarcity is a pressing global issue, necessitating efficient management of water resources. One significant aspect of water management is maintaining the cleanliness of water storage tanks, which often harbor contaminants due to neglect or inadequate cleaning procedures. This project introduces an IoT-based solution leveraging the STM32 microcontroller to automate the cleaning process of water tanks. The system employs sensors to monitor water quality, an actuator for tank cleaning, and IoT connectivity for remote monitoring and control. Key Words: Water tank cleaning, IoT-based solution, STM32, Water quality, Sediment removal

Jilin city central wastewater treatment plant renovation design scheme

Jilin City is one of the top ten famous Chinese cities worth introducing to the world. To further improve the construction of urban infrastructure and meet the needs of the economic and social development of Jilin City, the Jilin City Government Joint Development and Reform Commission and the Ecological Environment Bureau decided to expand and renovate the former Jilin City wastewater treatment plant. This study designs a wastewater treatment plant by comprehensively considering the policy needs and the local basic background characteristics of Jilin to solve the wastewater overflow problem. The design modified the anaerobic tank and Carroussel oxidation ditch processes, which have more advantages than traditional treatment processes, mainly including better BOD, nitrogen and phosphorus removal efficiency, less power consumption, and lower operating costs. This treatment plant design contains two special characteristics: the design considers the overall plan and pipeline layout of the wastewater treatment plant, and the size data of each module are calculated through theoretical study conforming to the real case.

Optimized data driven fault detection and diagnosis in chemical processes

Fault detection and diagnosis (FDD) is crucial for ensuring process safety and product quality in the chemical industry. Despite the large amounts of process data recorded and stored in chemical plants, most of them are not well-labeled, and their conditions are not adequately specified. In this study, an optimized data-driven FDD model was developed for a chemical process based on automatic clustering algorithms. Due to data preprocessing importance, feature selection was performed by a non-dominated sorting genetic algorithm (NSGAII) based on k-means clustering. The optimal subset of features is selected by comparing clustering results for each subset. The performance of the proposed feature selection method was compared with the Fisher discriminant ratio (FDR), and XGBoost methods. The t-distributed stochastic neighbor embedding (t-SNE), Isomap, and KPCA dimension reduction methods were also employed for feature extraction. Finally, automatic clustering was performed based on metaheuristic algorithms for fault detection and diagnosis. Results were compared with non-automatic clustering methods. The performance of the proposed method was evaluated by examining the Tennessee Eastman and four water tank processes as case studies. The results showed that the proposed method is reliable and capable of online and offline chemical process fault detection and diagnosis. As a result, the findings of this study can be used to stabilize the operation of chemical processes.

Design and Development of Hydrogen Isotopes Extraction System at IPR

Tritium breeding, recovery and safe storage are very important for achieving self-sustainability in a nuclear fusion reactor. Indeed, it is one of the essential task in terms of safety and fuel cycle aspects. Usually, tritium breeding is performed in the blanket module. In Indian blanket module, there are mainly two types of tritium breeder materials, one is Lithium based ceramic pebbles Li2TiO3 (Lithium Titanate) as solid breeders and second is the lithium based alloy Pb-Li (Lead Lithium) as a liquid breeder. Tritium bred in solid breeders is extracted with purge helium gas, whereas tritium bred in liquid Pb-Li needs suitable gas-liquid contactor. It should be noted that, tritium recovery (i.e.,-extraction) from Pb-Li is very challenging due to low solubility of tritium in liquid Pb-Li and no such separation technology readily available commercially. Therefore, the necessity for developing a reliable and efficient tritium recovery technology (i.e.,- extractor) for liquid Pb-Li is of key interest.In present work, design and development of Hydrogen Isotopes Extraction System (HIES) for hydrogen recovery from liquid Pb-Li is discussed. As hydrogen and tritium are isotopes, hydrogen is used instead of tritium in present system due to several safety concerns with tritium. Recovery of hydrogen from liquid Pb-Li is carried out using structured packing as a Gas-Liquid Contactor (GLC). The design details of gas-liquid contactor (i.e.-extractor column) and various process tanks of HIES are discussed. In present design, configuration of vertically mounted extractor column makes overall HIES relatively tall (∼ 3 m height) and use of liquid Pb-Li as process fluid makes the system heavy weight (∼1500 kg) too. In addition to this, system needs to be operated above Pb-Li melting temperature (> 235 C) to keep Pb-Li in liquid form. Therefore, thermal analysis of piping as well as seismic analysis of whole system is carried out and discussed along with various operational stages of HIES.

Analysis of coupling characteristics of clean heating systems based on complementary solar, geothermal, and wind energy

In order to overcome the limitations of traditional clean energy utilization methods, this paper proposed an innovative technical solution for a combined heating system that cleverly integrated solar, wind, and geothermal energy to achieve complementarity and synergized among them, thereby ensuring stable and efficient energy utilization. First, a comprehensive mathematical model was developed for the entire heating system, encompassing solar thermal subsystem, geothermal subsystem, wind power generation subsystem, and a second-stage reheating subsystem. Subsequently, Ebsilon simulation software was utilized to cleverly couple these subsystems together, with corresponding boundary conditions set to ensure the overall efficiency and stability of the system. Based on meteorological data and geothermal resource parameters from a typical heating season in Zhengzhou, Henan Province, China, this paper thoroughly analyzed the variations in key performance indicators such as the photothermal conversion efficiency of solar thermal subsystem and the heating capacity of geothermal subsystem. This provided valuable insight for optimizing the design of heating system. The results indicated that during the daylight hours of the heating season, both the photothermal conversion efficiency and the heat supply from the solar thermal subsystem exhibited an increasing trend as solar radiation increased. Among them, the photothermal conversion efficiency peaked at 76.013%, while the maximum heat supply output reached 40.311 kW. When solar direct radiation was relatively weak, the system primarily relied on the heat release process of the thermal storage tank to maintain heating, with a minimum heat supply of 27.268 kW. During nighttime hours of the heating season, the geothermal subsystem dominated the heating process, with a maximum heat supply of 125.556 kW. Additionally, for every 5 °C increased in geothermal water temperature, the heat supply from the geothermal subsystem increased by an average of 6.553 kW, demonstrating excellent heating response performance. Therefore, the integrated clean heating system that combines solar, geothermal, and wind energy not only significantly improves the utilization efficiency of clean energy but also enhances the heating stability of the integrated clean energy coupling system to a certain extent. The clean heating technical solution proposed in the paper had a theoretical total heating capacity of 19 680 kW during the heating season. When converted, this equates to a substitution of 6.9 tons of standard coal, resulting in a reduction of carbon dioxide emissions by 17.94 tons. This demonstrates the considerable cleanliness and environmental benefits of the proposed heating system. This study provides a valuable reference for the engineering application of renewable energy in the field of clean heating.