Browse
Subjects
Records with Subject: Numerical Methods and Statistics
2126. LAPSE:2023.1138
Numerical Analysis of the Free-Falling Process of a Water Droplet at Different Temperatures
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: deformation, heat transfer and phase change, two-phase flow, water droplet
The collision behavior and ice formation of a water droplet are affected by its falling process. In this paper, the two-phase flow of air and a water droplet at a specific temperature is adopted to investigate the processes of falling and freezing of a single water droplet. To track the air−water droplet interface and the temperature distribution, the level-set method and the non-isothermal flow coupling method are used, and the freezing model is added into the water’s control equations. The numerical results indicated that with the initial temperature at 283.15 K and the spherical shape, the water droplet changes to the shape of a straw hat at 293.15 K and a drum at 293.15 K but an oval face in freezing temperatures at 0.10 s. There is an obvious drop in the downward velocity when the water droplet falls in mild temperatures at 0.09 s. The downward velocity of the water droplet in air at sub-zero temperatures has a continuous increase during the time span from 0 s to 0.10 s. There is... [more]
2127. LAPSE:2023.1128
An Experimental Study of Wall Effect on a Hot Settling Sphere in a Newtonian-Fluid-Contained Block Using Photography
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: heat transfer, image processing, sphere fall
In this study, the effect of temperature on the velocity and trajectory of a hot sphere falling in a water block was experimentally investigated. The sphere, 12 mm in diameter, was thrown through the water inside an enclosure at the ambient temperature by an electromagnetic attachment mechanism, and the particle velocity was recorded by a high-speed camera at 2000 fps. Then, using an image-processing algorithm, the real-time particle location was extracted and its velocity was measured. The results of the cold sphere falling test were compared with those obtained from the numerical solving by the governing equations. An electric heater was used to heat the sphere up to 100, 200, and 300 °C in order to investigate the effect of temperature on the sphere. The sphere was thrown upon reaching the desired temperature. By increasing the temperature, the sphere’s velocity was increased up to around 40% of the velocity of the cold sphere. Further, the sphere was thrown from a point in the vici... [more]
2128. LAPSE:2023.1124
Overview of Fire Prevention Technologies by Cause of Fire: Selection of Causes Based on Fire Statistics in the Republic of Korea
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: cable, control system, energy storage system, ESS, fire, fire prevention technology, gas detection, next generation electricity, safety
Every year, diverse types of safety accidents cause major damage to human life and property. In particular, failure to suppress safety accidents caused by fires during the early stages can lead to large-scale accidents, which in turn can cause more serious damage than other types of accident. Therefore, this paper presents an analysis of the prevailing research trends and future directions for research on preventing safety accidents due to fire. Since fire outbreaks can occur in many types of places, the study was conducted by selecting the places and causes involved in frequent fires, using fire data from Korea. As half of these fires were found to occur in buildings, this paper presents an analysis of the causes of building fires, and then focuses on three themes: fire prevention based on fire and gas detection; fire prevention in electrical appliances; and fire prevention for next-generation electricity. In the gas detection of the first theme, the gas referred to does not denote a... [more]
2129. LAPSE:2023.1123
The Influence of Tip Clearance on the Performance of a High-Speed Inducer Centrifugal Pump under Different Flow Rates Conditions
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: cavitation, numerical calculation, pressure pulsation, tip clearance
The influence mechanism of the blade tip clearance (TC) of an inducer on the performance of a centrifugal pump at high speed was researched under different flow rate conditions in this work. An experiment on the pump’s external performance was carried out, and numerical calculation was also performed under four different TCs. The full characteristic performance curves, static pressure and pressure pulsation distributions of the pump were obtained. Through the research and analysis, it was found that the influence of the TC on the efficiency and the head of the centrifugal pump are related to the flow rate. Under the influence of a large flow rate, the increase in the TC is helpful to improve the efficiency and the head of the pump. The increase in the TC helps to weaken the gap jet effect on the inducer. The inlet jet of the inducer, caused by TC leakage, will form a low-pressure vortex zone at the inlet of the inducer. The splitter-bladed inducer’s pressure pulsation is affected by th... [more]
2130. LAPSE:2023.1118
Prediction Model for the Chemical Futures Price Using Improved Genetic Algorithm Based Long Short-Term Memory
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: Genetic Algorithm, LSTM neural network, price forecasting
In this paper, a new prediction model for accurately recognizing and appropriately evaluating the trends of domestic chemical products and for improving the forecasting accuracy of the chemical products’ prices is proposed. The proposed model uses the minimum forecasting error as the evaluation objective to forecast the settlement price. Active contracts for polyethylene and polypropylene futures on the Dalian Commodity Futures Exchange for the next five days were used, the data were divided into a training set and test set through normalization, and the time window, batch processing size, number of hidden layers, and rejection rate of a long short-term memory (LSTM) network were optimized by an improved genetic algorithm (IGA). In the experiments, with respect to the shortcomings of the genetic algorithm, the crossover location determination and some gene exchange methods in the crossover strategy were improved, and the predicted results of the IGA−LSTM model were compared with those... [more]
2131. LAPSE:2023.1115
Introducing the Effective Features Using the Particle Swarm Optimization Algorithm to Increase Accuracy in Determining the Volume Percentages of Three-Phase Flows
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: Artificial Intelligence, feature extraction, frequency domain, MLP neural network, PSO, volume fraction, wavelet
What is presented in this research is an intelligent system for detecting the volume percentage of three-phase fluids passing through oil pipes. The structure of the detection system consists of an X-ray tube, a Pyrex galss pipe, and two sodium iodide detectors. A three-phase fluid of water, gas, and oil has been simulated inside the pipe in two flow regimes, annular and stratified. Different volume percentages from 10 to 80% are considered for each phase. After producing and emitting X-rays from the source and passing through the pipe containing a three-phase fluid, the intensity of photons is recorded by two detectors. The simulation is introduced by a Monte Carlo N-Particle (MCNP) code. After the implementation of all flow regimes in different volume percentages, the signals recorded by the detectors were recorded and labeled. Three frequency characteristics and five wavelet transform characteristics were extracted from the received signals of each detector, which were collected in... [more]
2132. LAPSE:2023.1092
Hybrid Techniques of Analyzing MRI Images for Early Diagnosis of Brain Tumours Based on Hybrid Features
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: ANN, brain tumours, CNN, FFNN, handcrafted features, MRI, SVM
Brain tumours are considered one of the deadliest tumours in humans and have a low survival rate due to their heterogeneous nature. Several types of benign and malignant brain tumours need to be diagnosed early to administer appropriate treatment. Magnetic resonance (MR) images provide details of the brain’s internal structure, which allow radiologists and doctors to diagnose brain tumours. However, MR images contain complex details that require highly qualified experts and a long time to analyse. Artificial intelligence techniques solve these challenges. This paper presents four proposed systems, each with more than one technology. These techniques vary between machine, deep and hybrid learning. The first system comprises artificial neural network (ANN) and feedforward neural network (FFNN) algorithms based on the hybrid features between local binary pattern (LBP), grey-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT) algorithms. The second system comprises pre-t... [more]
2133. LAPSE:2023.1075
Anti-SARS-CoV-2 IgG ELISA: Replacing the Absorbance Plate Reader by a Regular Scanner with Open-Source Software
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: COVID-19, ELISA test, image scan data, statistical analysis
The COVID-19 global pandemic is still affecting the world, even considering vaccine applications in most countries, especially due to new variant outbreaks and the possibility that they may present immunological escape. Therefore, mass testing is relevant in infection monitoring and restriction policy evaluations, making low-cost and easy-to-use tests essential. Serological tests might also be useful in monitoring immune response after vaccination. The present work proposes a less-expensive ELISA test route, using a scanner instead of a spectrophotometer and using the saturation of the image as a surrogate for the absorbance of each sample. Images from multiple experiments were selected and correlated with their spectrophotometric absorbance. ELISA plate images were digitized by a simple table scanner and, then, preprocessed using Hue, Saturation, Value (HSV) transformation, aiming to determine which correlates best with the obtained absorbance. Saturation correlated better with absorb... [more]
2134. LAPSE:2023.1072
Synthesis of 2-DOF Decoupled Rotation Stage with FEA-Based Neural Network
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: 2-DOF rotation stage, compliant mechanisms, micro manipulation, transfer printing
Transfer printing technology has developed rapidly in the last decades, offering a potential demand for 2-DOF rotation stages. In order to remove decoupling modeling, improve motion accuracy, and simplify the control method, the 2-DOF decoupled rotation stages based on compliant mechanisms present notable merits. Therefore, a novel 2-DOF decoupled rotation stage is synthesized of which the critical components of decoupling are the topological arrangement and a novel decoupled compound joint. To fully consider the undesired deformation of rigid segments, an FEA-based neural network model is utilized to predict the rotation strokes and corresponding coupling ratios, and optimize the structural parameters. Then, FEA simulations are conducted to investigate the static and dynamic performances of the proposed 2-DOF decoupled rotation stage. The results show larger rotation strokes of 4.302 mrad in one-axis actuation with a 1.697% coupling ratio, and 4.184 and 4.151 mrad in two-axis actuatio... [more]
2135. LAPSE:2023.1067
An Appropriate Approach to Recognize Coke Size Distribution in a Blast Furnace
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: blast furnace ironmaking, faster R-CNN, HOG + SVM, MW, online detection method, size distribution of coke, YOLOv3
The size distribution of coke is important in order to decide the burden layer structure and the burden porosity in the shaft of a blast furnace (BF), which fluctuates daily and can be determined by several parameters. It is measured two or three times per shift by screening the raw material. However, the screening method used is random and takes a lot of time and manpower, resulting in the susceptive size distribution of the raw material and delayed operation of the BF. Therefore, in this paper, a new online approach used to measure the size distribution of particles was selected through comparison. Four common algorithms were used to detect the coke particles from images, including the Marker-based Watershed (MW), Histogram of Oriented Gradient + Support Vector Machine (HOG + SVM), Faster Region-based Convolutional Neural Networks (Faster R-CNN), and You Only Look Once (YOLOv3). The results show that the MW and HOG + SVM were not suitable for coke image detection. The average mean av... [more]
2136. LAPSE:2023.1058
Multimode Wind Tunnel Flow Field System Monitoring Based on KPLS
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: KPLS, multimode, nonlinear, wind tunnel
In a wind tunnel process, Mach number is the most important parameter. However, it is difficult to measure directly, especially in the multimode operation process, leading to difficulty in process monitoring. Thus, it is necessary to measure the Mach number indirectly by utilizing data-driven methods, and based on which, to monitor the operation status of the wind tunnel process. In this paper, therefore, a multimode wind tunnel flow field system monitoring strategy is proposed. Since the wind tunnel system is a strongly nonlinear system, the kernel partial least squares method, which can efficiently handle the nonlinear regression problem, is utilized. Firstly, the Mach number is predicted utilizing the kernel partial least squares method. Secondly, process monitoring statistics, i.e., the Hotelling T2 statistic and the square prediction error, the SPE statistic, and their control limits, are proposed to be applied to monitor the wind tunnel process on the basis of the prediction of t... [more]
2137. LAPSE:2023.1054
Research on Gas Concentration Prediction Based on the ARIMA-LSTM Combination Model
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: ARIMA algorithm, data fitting, gas prediction, LSTM algorithm
The current single gas prediction model is not sufficient for identifying and processing all the characteristics of mine gas concentration time series data. This paper proposes an ARIMA-LSTM combined forecasting model based on the autoregressive integrated moving average (ARIMA) model and the long short-term memory (LSTM) recurrent neural network. In the ARIMA-LSTM model, the ARIMA model is used to process the historical data of gas time series and obtain the corresponding linear prediction results and residual series. The LSTM model is used in further analysis of the residual series, predicting the nonlinear factors in the residual series. The prediction results of the combined model are compared separately with those of the two single models. Finally, RMSE, MAPE and R2 are used to evaluate the prediction accuracy of the three models. The results of the study show that the metrics of the combined ARIMA-LSTM model are R2 = 0.9825, MAPE = 0.0124 and RMSE = 0.083. The combined model has... [more]
2138. LAPSE:2023.1036
Effect of Hop β-Acids Extract Supplementation on the Volatile Compound Profile of Roasted Chicken Meat
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: central composite design, principal component analysis, roasted chicken meat, volatiles
The increased interest in greener sources of antioxidants has spurred the research on natural alternatives to enhance poultry production. This study aimed to investigate the effects of natural antioxidant extracts’ (hop β-acids extract) diet supplementation at different concentrations (0, 30, 60, and 120 mg kg−1) on the volatile compound profile of roasted chicken meat. A method based on headspace solid-phase micro-extraction coupled to gas chromatography-mass spectrometry (HS-SPME-GC-MS) was optimized by response surface design to extract the volatile compounds. The optimum extraction conditions were 80 °C and 45 min. A total of 95 volatile compounds were identified in roasted chicken meat, especially aldehydes, alkanes, alcohols, esters, and pyrazines. Principal component analysis (PCA) separated the samples as a function of β-acid supplementation, indicating that increased levels of supplementation lead to distinct volatile profiles in roasted chicken meat. Aldehydes such as octanal... [more]
2139. LAPSE:2023.1012
Photo-Ordering and Deformation in Azobenzene-Containing Polymer Networks under Irradiation with Elliptically Polarized Light
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: azobenzene-containing polymers, orientation ordering, photo-active materials, polymer networks, statistical physics
Azobenzene-containing polymers (azo-polymers) have been a subject of extensive investigations during the last two and half decades, due to their remarkable ability to undergo pronounced alignment and deformation under irradiation with light. The molecular ordering and deformation in azo-polymers of various structures under irradiation with linearly polarized light was described in a series of theoretical works, based on the effect of the reorientation of azobenzene moieties due to the anisotropic character of the photoisomerization processes. In the present study, we generalize the previous orientation approach to describe the photo-alignment and deformation of azo-polymer networks under irradiation with elliptically polarized light. We demonstrate that, in general, the light-induced ordering and deformation have a biaxial symmetry defined by the polarization ellipse. Azobenzene chromophores have a tendency to align along the direction of light propagation, the orientation in the other... [more]
2140. LAPSE:2023.1007
Combining Deep Neural Network with Genetic Algorithm for Axial Flow Fan Design and Development
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: axial fan design, axial flow fan, deep learning, deep neural network, Genetic Algorithm, Python
Axial flow fans are commonly used for a system or machinery cooling process. It also used for ventilating warehouses, factories, and garages. In the fan manufacturing industry, the demand for varying fan operating points makes design parameters complicated because many design parameters affect the fan performance. This study combines the deep neural network (DNN) with a genetic algorithm (GA) for axial flow design and development. The characteristic fan curve (P-Q Curve) can be generated when the relevant fan parameters are imported into this system. The system parameters can be adjusted to achieve the required characteristic curve. After the wind tunnel test is performed for verification, the data are integrated and corrected to reduce manufacturing costs and design time. This study discusses a small axial flow fan NACA and analyzes fan features, such as the blade root chord length, blade tip chord length, pitch angle, twist angle, fan diameter, and blade number. Afterwards, the wind... [more]
2141. LAPSE:2023.0989
Numerical Study on Pile Group Effect and Carrying Capacity of Four-Barreled Suction Pile Foundation under V-H-M Combined Loading Conditions
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: combined carrying capacity, finite element analysis, four-barreled suction pile foundation, group effect, undrained shear strength
Multi-barreled composite foundations are generally used in offshore oil platform structure. However, there is still a lack of theoretical analyses and experimental research. This paper presents the results of a three-dimensional finite element analysis of a four-barreled suction pile foundation in heterogeneous clay foundation. The pile group effect and carrying capacity are numerically simulated. The effects of different pile embedment depths, pile spacings and non-uniformity coefficients of clay on the pile group effect are studied. Considering the changes in the foundation carrying capacity under vertical, horizontal and bending moment coupling loads, the foundation carrying capacity envelopes under horizontal and moment (H-M) and vertical, horizontal and moment (V-H-M) loading modes are drawn. The results show that pile spacing and embedment depth have great influence on the pile group effect. The bearing capacity envelope of foundations under V-H-M loading mode is greatly affected... [more]
2142. LAPSE:2023.0985
Model Forecasting Development for Dengue Fever Incidence in Surabaya City Using Time Series Analysis
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: ARIMA model, dengue fever, forecasting, SARIMA model, time-series analysis
Dengue hemorrhagic fever (DHF) is one of the most widespread and deadly diseases in several parts of Indonesia. An accurate forecast-based model is required to reduce the incidence rate of this disease. Time-series methods such as autoregressive integrated moving average (ARIMA) models are used in epidemiology as statistical tools to study and forecast DHF and other infectious diseases. The present study attempted to forecast the monthly confirmed DHF cases via a time-series approach. The ARIMA, seasonal ARIMA (SARIMA), and long short-term memory (LSTM) models were compared to select the most accurate forecasting method for the deadly disease. The data were obtained from the Surabaya Health Office covering January 2014 to December 2016. The data were partitioned into the training and testing sets. The best forecasting model was selected based on the lowest values of accuracy metrics such as the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error... [more]
2143. LAPSE:2023.0977
The Mixture of Probability Distribution Functions for Wind and Photovoltaic Power Systems Using a Metaheuristic Method
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: Mayfly algorithm, metaheuristic optimization methods, mixture probability distribution functions, probability distribution functions, statistical error
The rising use of renewable energy sources, particularly those that are weather-dependent like wind and solar energy, has increased the uncertainty of supply in these power systems. In order to obtain considerably more accurate results in the analysis of power systems, such as in the planning and operation, it is necessary to tackle the stochastic nature of these sources. Operators require adequate techniques and procedures to mitigate the negative consequences of the stochastic behavior of renewable energy generators. Thus, this paper presents a modification of the original probability distribution functions (PDFs) where the original PDFs are insufficient for wind speed and solar irradiance modeling because they have a significant error between the real data frequency distribution and the estimated distribution curve. This modification is using a mixture of probability distributions, which can improve the fitting of data and reduce this error. The main aim of this paper is to model wi... [more]
2144. LAPSE:2023.0964
A Novel Carbon Dioxide Phase Transition Rock Breaking Technology: Theory and Application of Non-Explosive Blasting
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: carbon dioxide phase transition blasting, fracture characteristics, fracture mechanism, rock fracture
As a non-explosive low-disturbance rock breaking technology, carbon dioxide phase transition blasting (CDPTB) is widely used in rock breaking projects such as pressure relief and permeability enhancement in coal mines, open-pit mining, road subgrade excavation, foundation pit excavation, etc. In this paper, the principle and equipment of CDPTB are systematically analyzed, and the characteristics of a reusable fracturing tube and disposable fracturing tube are determined. Different energy calculation methods are analyzed to determine the magnitude or equivalent explosive equivalent of CDPTB. According to the characteristics of impact stress wave and high-pressure gas, the cracking mechanism of CDPTB is proposed. Under the action of medium-impact stress, rock mass will produce multi-point cracking, and high-pressure gas will produce a gas wedge effect in the initial fracture, which determines the comprehensive action path of the stress wave and high-pressure gas. In terms of fracture cha... [more]
2145. LAPSE:2023.0938
A Dynamic Principal Component Analysis and Fréchet-Distance-Based Algorithm for Fault Detection and Isolation in Industrial Processes
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: DPCA, fault detection and isolation, Fréchet distance
Fault Detection and Isolation (FDI) methodology focuses on maintaining safe and reliable operating conditions within industrial practices which is of crucial importance for the profitability of technologies. In this work, the development of an FDI algorithm based on the use of dynamic principal component analysis (DPCA) and the Fréchet distance δdF metric is explored. The three-tank benchmark problem is studied and utilized to demonstrate the performance of the FDI method for six fault types. A DPCA transformation for the system was established, and fault detection was conducted based on the Q statistic. Fault isolation is also of critical importance for proper intervention to mitigate fault effects. To identify the type of detected faults, the fault responses within the PC subspace were analyzed using the δdF metric. The use of the Fréchet distance metric for the isolation of faults combined with DPCA for feature extraction is a novel technique to the best of the authors’ knowledge th... [more]
2146. LAPSE:2023.0929
Flow Characteristics and Anti-Vortex in a Pump Station with Laterally Asymmetric Inflow
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: combined rectification, laterally asymmetric intake pumping station, recirculation coefficient, symmetrical 川-shaped diversion pier, vortex elimination
In a laterally asymmetric intake pumping station, the flow direction in the forebay is not consistent with flow in the intake channel. Thus, the adverse flow patterns, such as bias flow, large-scale vortex and asymmetric flow occur frequently in the forebay and sump. Based on the Reynolds-averaged Navier-Stokes (RANS) equation and the RNG k-ε turbulence model, a recent flow pattern in a laterally asymmetric intake pumping station was numerically simulated and analyzed, and effective vortex elimination measures were proposed. For the original scheme, seriously biased flow combined with large-scale vortices were observed in the forebay and several vortices occurred in the sump. To suppress the clash inflow in the south and north intake channel, the “straight diversion pier + curved wing wall” and “straight diversion pier + curved wing wall + V-shaped diversion pier” were installed separately. The” symmetrical 川-shaped diversion pier” and “symmetrical 川-shaped diversion pier + circular co... [more]
2147. LAPSE:2023.0927
Application of Spatial Analysis to Determine the Effect of Insulation Thickness on Energy Efficiency and Cost Savings for Cold Storage
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: degree days, Energy, geostatistics, kriging
Cold storage facilities consume a considerable amount of energy, especially in hot climates, which can be decreased using thermal insulators to maintain a stable temperature. The primary aim of this research study was to determine the effect of insulation thickness on the energy efficiency and cost savings of exterior walls for cold storage facilities in all climatic zones of Türkiye. To this end, data from the meteorological databases of 81 provinces were analyzed, and four insulation materials (expanded polystyrene, extruded polystyrene, rock wool, and polyurethane) were selected for different cold storage reference temperatures. The spatial distributions of optimal insulation thickness, energy savings, and payback periods were derived using a geographic information system (Ordinary Kriging). The optimum insulation thickness and energy savings were found to be 0.020−0.137 m and 0.030−6.883 USD/m2, respectively. Depending on the insulation material and base temperature, the shortest p... [more]
2148. LAPSE:2023.0923
Analysis of Collected Data and Establishment of an Abnormal Data Detection Algorithm Using Principal Component Analysis and K-Nearest Neighbors for Predictive Maintenance of Ship Propulsion Engine
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: K-nearest neighbors, Machine Learning, predictive maintenance, principal component analysis, ship propulsion engine
Because ships are typically operated for more than 25 years after construction, they can be considered mobile factories that require economic maintenance before being scrapped. Therefore, for stable and efficient ship operation, continuous maintenance systems and processes are required. Ships cannot be operated when defects or failures occur in any of the numerous systems configured in them, and research is urgently needed to apply predictive maintenance to propulsion engines with high maintenance costs using machine learning. Therefore, this study analyzes the operation and control characteristics of the propulsion engine, acquires engine data from the alarm monitoring system of the ship in operation, and then preprocesses the data by constructing a data preprocessing algorithm that incorporates the engine control characteristics. In addition, principal component analysis and K-nearest neighbors were used to check whether preprocessing data were classified based on engine control char... [more]
2149. LAPSE:2023.0919
Effects of Low-Level Organic Mercury Exposure on Oxidative Stress Profile
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: low-level exposure, mercury, oxidative stress
Background: The fish-based diet is known for its potential health benefits, but it is less known for its association with mercury (Hg) exposure, which, in turn, can lead to neurological and cardiovascular diseases through the exacerbation of oxidative stress. The aim of this study was to evaluate the correlations between Hg blood concentration and specific biomarkers for oxidative stress. Methods: We present a cross-sectional, analytical, observational study, including primary quantitative data obtained from 67 patients who presented with unspecific complaints and had high levels of blood Hg. Oxidative stress markers, such as superoxide dismutase (SOD), glutathione peroxidase (GPX), malondialdehyde (MLD), lymphocyte glutathione (GSH-Ly), selenium (Se), and vitamin D were determined. Results: We found positive, strong correlations between Hg levels and SOD (r = 0.88, p < 0.0001), GPx (r = 0.92, p < 0.0001), and MLD (r = 0.94, p < 0.0001). We also found inverted correlations bet... [more]
2150. LAPSE:2023.0914
Vapor Overproduction Condition Monitoring in a Liquid−Vapor Ejector
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: degree of vapor overproduction, Energy Efficiency, experimental study, interchangeable geometry, liquid–vapor ejector, vacuum unit
We consider the influence of vapor content in the mixed flow leaving a liquid-vapor ejector on the energy efficiency of a vacuum unit. As shown by numerical studies of liquid-vapor ejectors, this issue is important as vapor overproduction, which accompanies the process of secondary flow ejection, directly impacts the efficiency of the working process of both the liquid-vapor ejector and the vacuum unit as a whole. The greater the degree of vapor overproduction, the greater the load on the vapor phase of the separator, which is part of the vacuum unit. In addition, the liquid phase must be returned to the cycle to ensure the constancy of the mass flow rate of the working fluid of the primary flow. Our numerical study results revealed the rational value of the degree of vapor overproduction at which the efficiency of the liquid−vapor ejector was maximized, and the amount of additional working fluid that needed to enter the cycle of the vacuum unit was minimal. Experimental condition moni... [more]
[Show All Subjects]
[0.08 s]

