The paper presents in an applicative manner a parameter-based methodology about design, modeling and optimization of a spur gear pump, currently under production in a Romanian company. Wanting to expand their product range, the company asked for a parameter-based design of this type of pump, FEM simulations and optimization of its conception to cover a wider range of flow rates, as required by current beneficiaries. The purpose of this research was to find improved alternative solutions via parametric design, mathematical validation and finite element simulation of the manufacturing solutions. The pump model is well known and has been manufactured for decades in many countries, under various licenses and constructive variants. The research process analyzed the functional role of the gear pump, its structure, its 3D model, which was reconstructed from the last manufactured solution, while identifying certain dimensions to be optimized and used in parametric design relations. The author... [more]

This paper developed a 3D physical model of the hydraulic end of a high-pressure liquid hydrogen reciprocating pump to research the dynamic characteristics of the pump valve system. Based on dynamic mesh technology, we analyzed the coupling characteristics of pump valve and plunger motion and spool force considering the leakage model, closure model of valve gap, and compressibility of liquid hydrogen. Further, we analyzed the effect of the spring stiffness and preload force on the laws of motion of the pump valve. Finally, a liquid hydrogen pressurization test was conducted to revise the simulation model and verify the accuracy of the simulation. The results of the simulation and test show that the simulation method in this paper can simulate the liquid hydrogen pressurization process more accurately and obtain the motion law of the suction and discharge valves. Both the suction and discharge valves have an opening hysteresis angle of about 40°, and there is a strong coupling relations... [more]

Previous micro-scale studies of the effect of pore structure on spontaneous imbibition are mainly limited to invariable-diameter capillaries. However, in real oil and gas reservoir formations, the capillary diameters are changing and interconnected. Applying the lattice Boltzmann color gradient two-phase flow model and the parallel computation of CPUs, we simulated the spontaneous imbibition in variable-diameter capillaries. We explored the reasons for the nonwetting phase snap-off and systematically studied the critical conditions for the snap-off in spontaneous imbibition. The effects of pore-throat aspect ratio, throat diameter, and the pore-throat tortuosity of the capillary on spontaneous imbibition were studied. Through analyzing the simulated results, we found that the variation in the capillary diameter produces an additional resistance, which increases with the increase in the pore-throat ratio and the pore-throat tortuosity of a capillary. Under the action of this additional... [more]

Accurately detecting oil leakage from a power transformer is important to maintain its normal operation. Deep learning (DL) methods have achieved satisfactory performance in automatic oil detection, but challenges remain due to the small amount of training data and oil targets with large variations in position, shape, and scale. To manage these issues, we propose a dual attention residual U-net (DAttRes-Unet) within a U-net architecture that extensively uses a residual network as well as spatial and channel-wise attention modules. To overcome the vanishing gradient problem due to deeper layers and a small amount of training data, a residual module from ResNet18 is used to construct the encoder path in the U-net framework. Meanwhile, to overcome the issue of training difficulty for the network, inspired by the advantage of transfer learning, initial network parameters in the encoder are obtained from the pre-trained ResNet18 on the ImageNet dataset. Further, in the decoder path, spatial... [more]

Flue gas produced by biomass fuel combustion contains various chlorine-containing substances and is an important factor causing biomass boiler corrosion. The corrosion processes of chlorine, hydrogen chloride and water on iron covered with an intact/damaged oxide film were investigated under the high temperature of 1300 K through reactive molecular dynamics simulation. The results show that the diffusion processes of oxygen and chlorine are similar and can be divided into three stages: rapid diffusion, continuous diffusion, and no oxide film (stable). Oxygen diffusion in Fe2O3 into a pure iron layer is the main cause of gas corrosion in iron/iron oxide systems. A complete oxide film can hinder iron corrosion by chlorine and hydrogen chloride. Damage in an oxide film significantly affects oxygen and chlorine diffusion and iron corrosion. However, such influence is gradually reduced. The integrity of a protective film is the key to alleviating corrosion. Water facilitates the dissociatio... [more]

The air leakage in sintering machines affects the technological and economic indexes of the sintering process. It is of great significance to monitor and estimate the key areas. Mathematical models of sintering air leakage through holes in the steady-state process are given based on the fluid mechanics to predict the flow rate and effect on the key area. It was found that the hole model is the application of constant orifice outflow in the computation of sintering air leakage. The counter-flow bed model is suitable for predicting the flow rate through a complete break in sintering wind boxes. Furthermore, This paper proposes a new hole−bed generalized model to cover all the possible hole diameters for further high-precision application. The model connects the leakage hole diameter with the sintering process for the first time and establishes their coupling relationship. The pressure state in the sintering system depends on the ratio of the leakage hole area to the sintering bed area. T... [more]

The power system is undergoing significant changes so as to accommodate an increasing amount of renewably generated electricity. In order to facilitate these changes, a shift from the currently employed zonal pricing to nodal pricing is a topic that is receiving increasing interest. To explore alternative pricing mechanisms for the European electricity market, one needs to solve large-scale nodal optimization problems. These are computationally intensive to solve, and a parallelization or sequencing of the models can become necessary. The seasonality of hydro inflows and the issue of myopic foresight that does not display the value in storing water today and utilizing it in the future is a known problem in power system modeling. This work proposes a heuristic step-wise methodology to obtain state of charge profiles for hydro storage units for large-scale nodal and zonal models. Profiles obtained from solving an aggregated model serve as guidance for a nodal model with high spatial and... [more]

For the first time, the Weather Research and Forecast (WRF) model with the Wind Farm Parameterization (WFP) modeling method is utilized for a short-range wind power forecast simulation of 48 h of an offshore wind farm with 100 turbines located on the east coast of the China Yellow Sea. The effects of the horizontal multi-grid downsize method were deployed and investigated on this simulation computation. The simulation was validated with the field data from the Supervisory Control and Data Acquisition (SCADA) system, and the results showed that the horizontal mesh downsize method improved the accuracy of wind speed and then wind power forecast. Meanwhile, the wind power plant aerodynamics with turbine wake and sea−land shore effects were investigated, where the wake effects from the wind farm prolonged several miles downstream, evaluated at two wind speeds of 7 m/s and 10 m/s instances captured from the 48 h of simulation. At the same time, it was interesting to find some sea−land atmos... [more]

Motivated by the growing demand for distributed energy resources (DERs), peer-to-peer (P2P) electricity markets have been explored worldwide. However, such P2P markets must be balanced in much smaller regions with a lot fewer participants than centralized wholesale electricity markets; hence, the market has inherent problems of low liquidity and price instability. In this study, we propose applying a market maker system to the P2P electricity market and developing an efficient market strategy to increase liquidity and mitigate extreme price fluctuations. To this end, we construct an artificial market simulator for P2P electricity trading and design a market agent and general agents (photovoltaic (PV) generators, consumers, and prosumers) to perform power bidding and contract processing. Moreover, we introduce market-maker agents in this study who follow the regulations set by a market administrator and simultaneously place both sell and buy orders in the same market. We implement two t... [more]

Smart buildings that utilize innovative technologies such as artificial intelligence (AI), the internet of things (IoT), and cloud computing to improve comfort and reduce energy waste are gaining popularity. Smart buildings comprise a range of sensors to measure real-time indoor environment variables essential for the heating, ventilation, and air conditioning (HVAC) system control strategies. For accuracy and smooth operation, current HVAC system control strategies require multiple sensors to capture the indoor environment variables. However, using too many sensors creates an extensive network that is costly and complex to maintain. Our proposed research solves the mentioned problem by implementing a machine-learning algorithm to estimate unmeasured variables utilizing a limited number of sensors. Using a six-month data set collected from a three-story smart building in Japan, several extreme gradient boosting (XGBoost) models were designed and trained to estimate unmeasured room temp... [more]

Energy management and utilization for commercial users is becoming increasingly intelligent and refined, fostering a closer and growing connection with the electricity market. In this paper, a novel energy management optimization theoretical framework for commercial users is proposed based on the hybrid simulation of electricity market bidding. The hybrid simulation model based on Multi-Agent Simulation (MAS) with reinforcement learning and System Dynamic Simulation (SDS) is established to solve the problem using a single simulation method: it cannot adjust the clearing price when considering the whole market; considering the uncertainty of Electric Vehicles (EVs) travel and Lighting Loads (LLs), the multi-objective optimization model of energy management for commercial users is constructed to minimize the total energy cost of commercial users, as well as maximize the lighting comfort of indoor office staff, which compensates for the lack of the single-objective optimization of the pow... [more]

In the present work, uncertainty quantification of a venturi tube simulation with the cavitating flow is conducted based on Bayesian inference and point-collocation nonintrusive polynomial chaos (PC-NIPC). A Zwart−Gerber−Belamri (ZGB) cavitation model and RNG k-ε turbulence model are adopted to simulate the cavitating flow in the venturi tube using ANSYS Fluent, and the simulation results, with void fractions and velocity profiles, are validated with experimental data. A grid convergence index (GCI) based on the SLS-GCI method is investigated for the cavitation area, and the uncertainty error (UG) is estimated as 1.12 × 10−5. First, for uncertainty quantification of the venturi flow simulation, the ZGB cavitation model coefficients are calibrated with an experimental void fraction as observation data, and posterior distributions of the four model coefficients are obtained using MCMC. Second, based on the calibrated model coefficients, the forward problem with two random inputs, an inle... [more]

Accurate and rapid forecasting of short-term loads facilitates demand-side management by electricity retailers. The complexity of customer demand makes traditional forecasting methods incapable of meeting the accuracy requirements, so a self-attention based short-term load forecasting (STLF) considering demand-side management is proposed. In the data preprocessing stage, non-parametric kernel density estimation is used to construct customer electricity consumption feature curves, and then historical load data are used to delineate the feasible domain range for outlier detection. In the feature selection stage, the feature data are selected using variational modal decomposition and a maximum information coefficient to enhance the model prediction accuracy. In the model prediction stage, the decomposed intrinsic mode function components are independently predicted and reconstructed using an Informer based on improved self-attention. Additionally, the novel AdaBlief optimizer is used to o... [more]

This paper proposes the full simulation model for the electrical analysis of all-electric ship (AES) based on a medium voltage DC power system. The AES has become popular both in the commercial and the military areas due to a low emission, a high fuel consumption efficiency, and a wide applicability. In spite of many advantages, it is complex and difficult to construct the whole system with many mechanical and electrical components onboard. Full electrical analysis is essentially required to simplify the design of the AES, a control and optimization of a ship electric system. The proposed full simulation model of the AES includes the mechanical and the electrical elements by using the MATLAB/Simulink. The mechanical elements are comprised of a steam turbine and a hydrodynamic model of a ship which is adopted by an average value model that is based on the characteristic equation of the mechanical system. The electrical elements are developed by full detailed models which consist of gene... [more]

The conversion of biomass to olefin by employing gasification has recently gained the attention of the petrochemical sector, and syngas composition is a keystone during the evaluation of process design. Process simulation software is a preferred evaluation tool that employs stoichiometric and kinetic approaches. Despite the available literature, the estimation errors of these simulation methods have scarcely been contrasted. This study compares the errors of stoichiometric and kinetic models by simulating a downdraft steam gasifier in PRO/II. The quantitative examination identifies the model that best predicts the composition of products for the gasification of Japanese wood waste. The simulation adopts reaction mechanisms, flowsheet topology, reactions parameters, and component properties reported in the literature. The results of previous studies are used to validate the models in a comparison of the syngas composition and yield of products. The models are used to reproduce gasificat... [more]

In the course of the switch to renewable energy sources, there is a shift from a few large energy sources (power plants) to a large number of small, distributed energy sources (e.g., photovoltaic systems) and energy storage devices (e.g., electric vehicles). This results in the need to know and identify these energy sources and sinks as soon as new devices are installed, in order to ensure grid stability. This paper presents an approach to identify energy sources and energy storage in smart meter data, using photovoltaic systems and electric vehicles as examples. For this purpose, the Pecan Street dataset is used, which has been extended by charging processes from the ACN dataset. The presented approach comprises a combination of a Convolutional Neural Network and a Multilayer Perceptron, which decides separately, on the basis of the smart meter data of a household, whether an electric vehicle and a photovoltaic system are present. It is shown that the combination of both classifiers a... [more]

In this paper, heat transfer and airflow in the gap between the panes of a central part of a double-glazed window were investigated using mathematical modeling. It has been shown that the cyclical airflow regime, in the form of ascending and descending boundary layers, loses stability and changes to a vortex regime under certain conditions depending on the gap width, transverse temperature gradient, inclination angle and window height, as in Rayleigh−Bernard convection cells. The study made it possible to determine the critical values of the Rayleigh number (Ra) at which the air flow regime in the gap between the panes of a window changes (in the range of values 6.07 × 103 < Ra < 6.7 × 103). As a result of the modeling, the values of the thermal resistance of a central part of double-glazed window were determined as a function of the width of the gap between the panes, the angle of inclination and the transverse temperature gradient.

Given the spatial structures and functional requirements, there are a number of different types of obstacles in long and narrow confined spaces that will cause a premixed gas explosion to produce greater overpressure and influence the flame behavior for different obstacles. Because the volume fraction of unburned gas changes with the changing height of the U-type obstacles, we can further study the influence on the volume fraction of the unburned premixed gas for the characteristics of the overpressure and the flame behaviors in the closed tube with the obstacles. The results show that after the premixed gas is successfully ignited in the pipe, the overpressure in the pipe greatly increases as the unburned premixed gas burns between the adjacent plates. Moreover, the increase of the overpressure in the closed duct becomes faster when the decrease of unburned gas becomes faster. The high-pressure areas between the plates move inversely compared with the direction of flame propagation wh... [more]

With the development of power modules for high voltage, high temperature, and high power density, their size is becoming smaller, and the packaging insulation experiences higher electrical, thermal, and mechanical stress. Packaging insulation needs to meet the requirement that internal electric field, temperature, and mechanical stress should be as low as possible. Focusing on the coupling principles and optimization design among electrical, thermal, and mechanical stresses in the power module packaging insulation, a multi-objective optimization design method based on Spice circuit, finite element field numerical calculation, and multi-objective gray wolf optimizer (MOGWO) is proposed. The packaging insulation optimal design of a 1.2 kV SiC MOSFET half-bridge power module is presented. First, the high field conductivity characteristics of the substrate ceramic and encapsulation silicone of the packaging insulation material were tested at different temperatures and external field streng... [more]

Supervisory Control and Data Acquisition (SCADA) systems are essential for reliable communication and control of smart grids. However, in the cyber-physical realm, it becomes highly vulnerable to cyber-attacks like False Data Injection (FDI) into the measurement signal which can circumvent the conventional detection methods and interfere with the normal operation of grids, which in turn could potentially lead to huge financial losses and can have a large impact on public safety. It is imperative to have an accurate state estimation of power consumption for further operational decision-making.This work presents novel forecasting-aided anomaly detection using an CNN-LSTM based auto-encoder sequence to sequence architecture to combat against false data injection attacks. We further present an adaptive optimal threshold based on the consumption patterns to identify abnormal behaviour. Evaluation is performed on real-time energy demand consumption data collected from the Australian Energy M... [more]

In this paper, we explore the improvement of the aerodynamic characteristics of wind turbine blades under stall conditions using passive flow control with slots. The National Renewable Energy Laboratory (NREL) Phase II rotor, for which detailed simulations and experimental data are available, served as a baseline for assessing the flow control system effects. The position and configuration of the slot used as a flow control system were determined using CFD analysis. The 3D-RANS equations are solved with ANSYS FLUENT using the k-ω SST turbulence closure model. The pressure coefficient for different wind speeds for the baseline configuration is compared to the available experimental data. The comparison shows that CFD results were better for the attached flow. The current work consists of a 3-D CFD modeling of a rotating blade equipped with different flow control systems: single-slot (S-S) and two-slots (T-S). The computation provides a better understanding of the influence of these flow... [more]

The energy use intensity (EUI) of convenience stores was substantially higher than that of office buildings and hotels, due to a compact footprint but a high density of equipment yielded a higher EUI. As a result, it is critical to assess and maintain the state of the convenience store in order to obtain a lower EUI and reduce energy consumption. This study utilizes a convenience store to evaluate energy consumption and perform a CFD simulation to see how the environment influences by cold storage showcase (CSS) equipment. On the basis of field testing and on-site web-based monitoring data, a survey of baseline information through data collecting and energy benchmarking data has been provided and extensively examined. According to energy monitoring, the convenience store’s highest electricity use is 23,055 kWh in June, and the lowest power consumption is 15,216 kWh in February. The CFD simulation results revealed that the temperature near the CSS can be 3−5 °C lower than in other regio... [more]

The thermophysical properties of a working-fluid play an important role in the process of stirring-heating. The heating process of stirring is accompanied by two processes: the friction between the solid mechanism and the working-fluid and the viscous dissipation of the working liquid. Traditionally, the sensible heat of water-based working-fluids is low, while that of oil-based working-fluids is higher, but the load capacity is relatively low. In order to find a balance between the two, an optimal stirring working-fluid should be selected. In this study, an experimental method was used to study the heating process of 30 kinds of working-fluids. The numerical evaluation model of the effects of thermophysical properties on the comprehensive evaluation index of heat (CEIH) was established by multiple linear regression methods, and a computational fluid dynamics (CFD) tool was used to analyze the heat generation and flow field of different working-fluids in the stirring-heating device. Th... [more]

The generation of synthetic vibration signals enables the testing of novel machine diagnostic methods without the costly introduction of real failures. One of major goals of vibration-based condition monitoring is the early detection of bearing faults. This paper presents a novel modeling technique based on the combination of the known mechanical properties of a modeled object (phenomenological part) and observation of a real object (behavioral part). The model uses the real pulse response of bearing housing, along with the external instantaneous machine speed profile. The presented method is object-oriented, so it is applicable to a large group of machinery.

The transition toward high shares of non-programmable renewable energy sources in the power grid requires an increase in the grid flexibility to guarantee grid reliability and stability. This work, developed within the EU project Grasshopper, identifies hydrogen Fuel Cell (FC) power plants, based on low temperature PEM cells, as a source of flexibility for the power grid. A dynamic numerical model of the flexible FC system is developed and tested against experimental data from a 100-kW pilot plant, built within the Grasshopper project. The model is then applied to assess the flexible performance of a 1 MW system in order to optimize the scale-up of the pilot plant to the MW-size. Simulations of load-following operation show the flexibility of the plant, which can ramp up and down with a ramp rate depending only on an externally imposed limit. Warm-up simulations allow proposing solutions to limit the warm-up time. Of main importance are the minimization of the water inventory in the sy... [more]