One of the most difficult challenges in medicine is predicting heart disease at an early stage. In this study, six machine learning (ML) algorithms, viz., logistic regression, K-nearest neighbor, support vector machine, decision tree, random forest classifier, and extreme gradient boosting, were used to analyze two heart disease datasets. One dataset was UCI Kaggle Cleveland and the other was the comprehensive UCI Kaggle Cleveland, Hungary, Switzerland, and Long Beach V. The performance results of the machine learning techniques were obtained. The support vector machine with tuned hyperparameters achieved the highest testing accuracy of 87.91% for dataset-I and the extreme gradient boosting classifier with tuned hyperparameters achieved the highest testing accuracy of 99.03% for the comprehensive dataset-II. The novelty of this work was the use of grid search cross-validation to enhance the performance in the form of training and testing. The ideal parameters for predicting heart disea... [more]

The evolution of mesoscale structures of particle packing in binary composite packed beds and their effects on flow characteristics and wall effects were investigated using the discrete element method (DEM) and computational fluid dynamics (CFD). The DEM model was used to build a series of randomly mixed packing structures of particles in accordance with the dynamic change of mass ratio between particles in two size ranges, which were then confirmed by the findings of an X-ray tomography (CT) scan. The results show that the packing structure of b25s75 was conducive to reducing the influence of wall effect in packed bed reactors. For b25s75, the dimensionless distance of radial porosity fluctuation from the wall is 0.3705, which is the smallest among the five packing models, indicating that this structure plays a suppressive role on the wall effect. In addition, the uniformity of velocity and temperature distributions in both the radial and axial directions of different packing structur... [more]

This work seeks to contribute to the study of techniques for level control considering a nonlinear plant model. To achieve this goal, different approaches are applied to classical control techniques and their results are analyzed. Fuzzy Logic Control (FLC), Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Model Predictive Control (MPC) and Nonlinear Auto-Regressive Moving Average (NARMA-L2) controllers are designed for the level control of a spherical tank. Subsequently, several tests and scenarios similar to those present in industrial processes are established, while the transient response of the controllers, their performance indices for monitoring the reference value, the rejection of disturbances, the presence of parameter uncertainties and the effects of noise are analyzed. The results show good reference tracking, with a settling time of approximately 5 s for 5 cm and a rise time of less than 4 s. No evidence for steady-state error or overshoot was... [more]

In this study, the temperature and thermal stress fields of an internal combustion hot blast stove were calculated and analysed. Turbulent, species transport, chemical reaction, radiation, and porous media models were implemented in a computational fluid dynamics model. Thermal boundary conditions on the structure of the hot blast stove were calculated based on the analytic adiabatic Y-plus method. A method to interpolate the thermal boundary conditions to a finite element mesh was developed, and the boundary conditions were mapped through the proposed method. In the on-gas period, the vortex was generated in the dome, and it made the variation of the temperature field in the checker chamber. The maximum temperature of the flue gas reached 1841 K in the on-gas period. In the on-blast period, the flow was considerably even compared to the on-gas period, and the average blast temperature reached 1345 K. The outer region of the checker chamber is shown to be continuously exposed to a high... [more]

The high-pressure polyethylene process uses cyclone separators to separate ethylene gas, polyethylene, and its oligomers. The oligomers larger than 10 microns that cannot be separated must be filtered through a filter to prevent them from entering the compressor and affecting its normal operation. When the separation efficiency of the cyclone separator is low, the filter must be cleaned more frequently, which will reduce production efficiency. Research shows that improving the separation efficiency of the separator is beneficial for the separation of small-particle oligomers and reduces the frequency of filter cleaning. For this reason, Computational Fluid Dynamics simulations were performed for 27 sets of cyclone separators to determine the effects of eight structural factors (cylinder diameter, cylinder height, cone diameter, cone height, guide vane height, guide vane angle, exhaust pipe extension length, and umbrella structure height) on separation efficiency and pressure drop. The... [more]

This study aims to develop combined methods with dual and triple use of different non-destructive test (NDT) methods and to examine the effectiveness of these methods. For this purpose, nine different high-strength concrete series were produced, and destructive and NDT methods were applied to these samples on the 3rd and 90th days. Surface hardness, ultrasonic pulse velocity, and penetration resistance were considered from NDT methods. Analyses were made on the response surface method using the NDT measurements and compressive strength values obtained, and four different mathematical models were developed. Models 1, 2, and 3 were designed with dual use of NDT methods, and model 4 was designed with triple use. The absolute relative deviation values for all the developed models’ early and final-age strengths were below 10%. It is of great importance to determine concrete quality with high accuracy and practicality, especially in places like Elazig, where there are thousands of newly cons... [more]

Downhole vibrations caused by rock breaking when drilling through pebbled sandstone formations negatively affect the rate of penetration (ROP) and the safety of downhole tools. Therefore, it is of great significance to study the cutting characteristics of pebbled sandstone and find a method of reducing the drilling vibrations of pebbled sandstone formations. Based on the DEM (discrete element method), a simulation model of pebbled sandstone considering the random filling of high-strength gravels was established by using the random polygon distribution method. The influence of gravel content on the strength parameters and the breaking state of the pebbled sandstone samples was analyzed. Additionally, a DEM model of PDC cutting rocks loaded by a spring−mass system was established, and the Stribeck effect of contact friction between the PDC cutter and the rock was analyzed. The periodic vibration and the stick−slip phenomenon of the cutting system during the drilling process were presente... [more]

Climate change is one of the main problems that humanity is currently facing due to carbon dioxide emissions caused by fossil fuel consumption. Organic Rankine cycles may play an important role in reducing these emissions since they can use industrial waste heat or renewable energies. This study presents the proposal and modeling of an organic Rankine cycle integrated into a double-effect absorption cooling system for the simultaneous production of power and cooling. The working fluids utilized were the ammonia−lithium nitrate mixture for the absorption system and benzene, cyclohexane, methanol, and toluene for the organic Rankine cycle. The influence of the primary operating parameters on the system performance was analyzed and discussed in terms of cooling load, turbine power, energy utilization factor, and exergy efficiency for a wide range of operating conditions. It was found that, for all cases, the cooling load was dominant over the turbine power since the minimum cooling load o... [more]

Over the years, Computational Fluid Dynamics (CFD) has been an integral part of most pump design processes. Unfortunately, as calculation schemes and flow investigations become more complicated, the cost of conducting numerical simulations also becomes more expensive in terms of computational time. To remedy this, cutting-edge technology, together with novel calculation techniques, are continuously introduced with the end target of producing more accurate results and faster computing time. In this paper, CFD simulations are run on a numerical model of a double-volute double-suction pump prepared using ANSYS Fluent Mosaic meshing technology. Poly-Hexcore, the first application of Mosaic technology, fills the bulk region with octree hexes, keeps a high-quality layered poly-prism mesh in the boundary layer, and conformally connects these two meshes with general polyhedral elements. This technology promises to provide a lower number of cells along with a significant increase in computing s... [more]

This review is focused on the thermochemical behaviour of fluxes in submerged arc welding (SAW). The English-language literature from the 1970s onwards is reviewed. It was recognised early on that the thermochemical behaviour of fluxes sets the weld metal total ppm O and the element transfer extent from the molten flux (slag) to the weld pool. Despite the establishment of this link between the flux-induced oxygen potential and element transfer, it is also well accepted that the slag−metal equilibrium does not control SAW process metallurgy. Instead, the gas phase must be taken into account to better describe SAW process metallurgy equilibrium calculations. This is illustrated in the gas−slag−metal equilibrium simulation model developed by Coetsee. This model provides improved accuracy in predicting the weld metal total ppm O values as compared to the empirical trend of Tuliani et al. Recent works on the application of Al metal powder with alloying metal powders provide new insights int... [more]

Nanofluid, the fluid suspensions of a metallic nanoparticle, became a coolant fluid that is used when a promising enhancement in heat transfer is required. In the current study, the characteristics of fluid flow and heat transfer are numerically investigated using different nanofluids (Al2O3−H2O, TiO2−H2O, and SiO2−H2O) and different micro-channel heat sink (MCHS) configurations (rectangular, triangular, trapezoidal, and circular). In this numerical investigation, the effect of Re number ranged from 890 to 1500, and the effect of nanoparticle concentration ranged from 1% to 7% at constant heat flux q = 106 W/m2, and constant fluid inlet temperature of 288 K, were studied. The average heat transfer coefficient, h, and pressure drop, Δp, are used to quantify the fluid flow and heat transfer characteristics in each MCHS configuration and for each nanoparticle concentration. It is revealed that a better heat transfer coefficient is obtained for Al2O−H2O compared with other types of nanopar... [more]

Foam acidization has unique advantages such as low damage, low filtration, low friction, high efficiency, excellent retardation, and fast liquid discharge rate, which is suitable for stimulation and reconstruction of low-pressure oil and gas reservoirs that have been developed over many years. It is obtained that the main chemical components of downhole plugging materials include vegetable oil, fatty acids and their esters, silicone oil, amide polymers, and additional organic components, as well as non-organic components, elemental sulfur, ferrous sulfide, iron disulfide, silicon dioxide, mineral salts, etc. The performance of foam acid was investigated by experiments, including the effective range of action of active acids, reducing filtration, increasing temperature resistance and high-temperature stability of foam acid deep wells. The new foam acid system is developed and optimized to suitable for low-pressure deep well acidification operations. Experimental evaluation optimized the... [more]

This paper examines the impact of different chemistry−turbulence interaction approaches on the accuracy of simulations of coal gasification in entrained flow reactors. Infinitely fast chemistry is compared with the eddy dissipation concept considering the influence of turbulence on chemical reactions. Additionally, ideal plug flow reactor study and perfectly stirred reactor study are carried out to estimate the accuracy of chosen simplified chemical kinetic schemes in comparison with two detailed mechanisms. The most accurate global approach and the detailed one are further implemented in the computational fluid dynamics (CFD) code. Special attention is paid to the water−gas shift reaction, which is found to have the key impact on the final gas composition. Three different reactors are examined: a pilot-scale Mitsubishi Heavy Industries reactor, a laboratory-scale reactor at Brigham Young University and a Conoco-Philips E-gas reactor. The aim of this research was to assess the impact o... [more]

This paper presents a mathematical model that reflects the nature of the dynamic Young’s modulus of a dry sedimentary rock during nonstationary uniaxial loading. The model is based on an idealized model of a system suggested by Jaeger J.C. A rock sample is considered as a spring with stiffness, the bottom point of which is fixed, while the upper point carries a mass. A sample experiences dynamic load and the rock matrix response. Displacement of the mass from the equilibrium state sets the variation of the sample’s length. Displacement of all the sample’s points goes according to the same law regardless of the point location. The response of a rock to a disturbing nonstationary load is selected based on the combination of conditions of each experiment, such as the load frequency and amplitude and the mass, length, and diameter of a sample. The mathematical model is consistent with experimental data, according to which an increase in load frequency leads to an increase in the dynamic Yo... [more]

The article describes an elaboration of the X-in-the-loop (XiL) testing environment for a thermal management system (TMS) intended for the traction electric drive of an electric vehicle, which has each of its wheels driven by an in-wheel motor. The TMS features the individual thermal regulation of each electric drive using a hydraulic layout with parallel pipelines and electrohydraulic pumps embedded into them. The XiL system is intended as a tool for studying and developing the TMS design and controls. It consists of the virtual part and the physical part. The former simulates the vehicle operating in a driving cycle with the heat power dissipated by the electric drive components, which entails the change in their temperature regimes. The physical part includes the TMS itself consisting of a radiator, pipelines, and pumps. The physical part also features devices intended for simulation of the electric drive components in terms of their thermal and hydraulic behaviors, as well as devic... [more]

In order to improve the accuracy of wind power ramp forecasting and reduce the threat of ramps to the safe operation of power systems, a wind power ramp event forecast model based on feature extraction and deep learning is proposed in this work. Firstly, the Optimized Swinging Door Algorithm (OpSDA) is introduced to detect wind power ramp events, and the extraction results of ramp features, such as the ramp rate, are obtained. Then, a ramp forecast model based on a deep learning network is established. The historical wind power and its ramp features are used as the input of the forecast model, thereby strengthening the model’s learning for ramp features and preventing ramp features from being submerged in the complex wind power signal. A Convolutional Neural Network (CNN) is adopted to extract features from model inputs to obtain the coupling relationship between wind power and ramp features, and Long Short-Term Memory (LSTM) is utilized to learn the time-series relationship of the dat... [more]

Retailers and major consumers of electricity generally purchase an important percentage of their estimated electricity needs years ahead in the forward market. This long-term electricity procurement task consists of determining when to buy electricity so that the resulting energy cost is minimised, and the forecast consumption is covered. In this scientific article, the focus is set on a yearly base load product from the Belgian forward market, named calendar (CAL), which is tradable up to three years ahead of the delivery period. This research paper introduces a novel algorithm providing recommendations to either buy electricity now or wait for a future opportunity based on the history of CAL prices. This algorithm relies on deep learning forecasting techniques and on an indicator quantifying the deviation from a perfectly uniform reference procurement policy. On average, the proposed approach surpasses the benchmark procurement policies considered and achieves a reduction in costs of... [more]

It is critical to discover the behavior of piston wind induced by a braking train in a tunnel, but there is little research on the theoretical derivation for piston wind behavior. Predicting piston wind behavior as an unsteady airflow by a theoretical formula is hard work due to the complexity of train running states and airflow fields. Herein, we develop a mathematical model to investigate the behavior of piston wind as an unsteady airflow, considering the variation of wind direction in the annular area. In general, the theoretical model is validated by experiments. However, experimental studies about piston wind are scarce. In this study, we simulated the emergent braking process of a train to validate the mathematical model by establishing a 1/50 scaled experimental configuration. The piston wind data tested in the experiment have good agreement with the results calculated by theoretical formulas. In addition, sensitivity analysis of the effect parameters of piston wind (i.e., tunne... [more]

The integration of renewable generation adds complexity to the operation of the power system due to its unpredictable characteristics. Therefore, the development of methods to accurately model the uncertainty is necessary. In this paper, the spatio-temporal kriging and analog approaches are used to forecast wind power generation and used as the input to solve an economic dispatch problem, considering the uncertainties of wind generation. Spatio-temporal kriging captures the spatial and temporal information available in the database to improve wind forecasts. We evaluate the performance of using the spatio-temporal kriging, and comparisons are carried out versus other approaches in the framework of the economic power dispatch problem, for which simulations are developed on the modified IEEE 3-bus and IEEE 24-bus test systems. The results demonstrate that the use of kriging based spatio-temporal models in the context of economic power dispatch can provide an opportunity for lower operati... [more]

Accurate tidal current prediction plays a critical role with increasing utilization of tidal energy. The classical prediction approach of the tidal current velocity adopts the harmonic analysis (HA) method. The performance of the HA approach is not ideal to predict the high frequency components of tidal currents due to the lack of capability processing the non-astronomic factor. Recently, machine learning algorithms have been applied to process the non-astronomic factor in the prediction of tidal current. In this paper, a tidal current velocity prediction considering the effect of the multi-layer current velocity method is proposed. The proposed method adopts three machine learning algorithms to establish the prediction models for comparative investigations, namely long-short term memory (LSTM), back-propagation (BP) neural network, and the Elman regression network. In the case study, the tidal current data collected from the real ocean environment were used to validate the proposed me... [more]

An analytical model for predicting the productivity of Radial-lateral wells (RLW) drilled using radial jet drilling technology was developed in this work. The model assumes uniformly distributed equal-geometry laterals draining oil or gas under pseudo-steady state flow conditions within the lateral-reached drainage area. A numerical simulation and production data from three field cases of RLW were used to compare and validate the model. The result indicates that the model overestimates the well production rates for wells by 7.7%, 3.25%, and 8.8%, respectively. The error is attributed to several sources including, lack of data for well skin factor, uncertainty of horizontal permeability (kH) in the well area, uncertainty of permeability anisotropy (Iani), and uncertainty in bottom hole pressure (pw). Error analysis of uncertainties in kH, Iani, and pw showed that the model could predict productivity well with an acceptable error (10%) over practical ranges of these parameter values. Par... [more]

Modern control strategies for district-level heating and cooling supply systems pose a difficult challenge. In order to integrate a wide range of hot and cold sources, these new systems will rely heavily on accumulation and much lower operating temperatures. This means that predictive models advising the control strategy must take into account long-lasting thermal effects but must not be computationally too expensive, because the control would not be possible in practice. This paper presents a simple but powerful systematic approach to reducing the complexity of individual components of such models. It makes it possible to combine human engineering intuition with machine learning and arrive at comprehensive and accurate models. As an example, a simple steady-state heat loss of buried pipes is extended with dynamics observed in a much more complex model. The results show that the process converges quickly toward reasonable solutions. The new auto-generated model performs 5 × 104 times f... [more]

The arc behaviour of short, low current switching arcs is not well understood and lacks a reliable model. In this work, the behaviour of an arc in the air is studied during contact separation at low DC currents (0.5 A to 20 A) and for small gap lengths (0 mm to 6 mm). The experiments are performed on a low voltage relay with two different electrode configurations. The arc voltage is measured during the opening of the contacts at constant current. The arc length is determined optically by tracing the mean path of the arc over time from a series of high-speed images. From the synchronised data of voltage vs. distance, first a sudden jump of the voltage at the start of contact opening is observed. Secondly, a sudden change in the voltage gradient occurs as the arc is elongated. Short arcs with a length up to approximately 1.25 mm show an intense radiation in the overall gap region and high voltage gradients. An unexpected behaviour never reported before was observed for longer arcs at low... [more]

A new reactor core multi-physics system addresses the pellet-to-cladding heat transfer modeling to improve full-core operational transient and accident simulation used for assessment of reactor core nuclear safety. The rigorous modeling of the heat transfer phenomena involves strong interaction between neutron kinetics, thermal-hydraulics and nuclear fuel performance, as well as consideration of the pellet-to-cladding mechanical contact leading to dramatic increase in the gap thermal conductance coefficient. In contrast to core depletion where parameters smoothly depend on fuel burn-up, the core transient is driven by stiff equation associated with rapid variation in the solution and vulnerable to numerical instability for large time step sizes. Therefore, the coupling algorithm dedicated for multi-physics transient must implement adaptive time step and restart capability to achieve prescribed tolerance and to maintain stability of numerical simulation. This requirement is met in the M... [more]

Gymnasium are typically large-span buildings with abundant solar energy resources due to their extensive roof surface. However, relevant research on this topic has not been thoroughly conducted to investigate the effect of the geometric shape of gymnasium buildings on their solar potential. In this paper, an investigation of the geometric shape effect on the solar potential of gymnasium buildings is presented. A three-dimensional radiation transfer model coupled with historical meteorological data was established to estimate the real-time solar potential of the roof of a gymnasium building. The rooftop solar potential of three typical building foundation shapes and different types of roof shapes that have evolved was systematically analyzed. An annual solar potential cloud map of each gymnasium building is generated. The monthly and annual average solar radiation intensities of the different types of roof shapes are investigated. Compared to the optimal tilt angle, the maximum decrease... [more]