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Records with Subject: Numerical Methods and Statistics
2100. 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]
2101. 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]
2102. 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]
2103. 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]
2104. LAPSE:2023.0902
Enhanced Multiphase Flow Measurement Using Dual Non-Intrusive Techniques and ANN Model for Void Fraction Determination
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: ANN, capacitance, flow measurement, flow regimes, gamma-ray, multiphase flow, neural networks, sensors, void fraction
There are many petrochemical industries that need adequate knowledge of multiphase flow phenomena inside pipes. In such industries, measuring the void fraction is considered to be a very challenging task. Thus, various techniques have been used for void fraction measurements. For determining more accurate multiphase flow measurements, this study employed dual non-intrusive techniques, gamma-ray and electrical capacitance sensors. The techniques using such sensors are considered non-intrusive as they do not cause any perturbation of the local structure of the phases’ flow. The first aim of this paper is to analyze both techniques separately for the void fraction data obtained from practical experiments. The second aim is to use both techniques’ data in a neural network model to analyze measurements more efficiently. Accordingly, a new system is configured to combine the two techniques’ data to obtain more precise results than they can individually. The simulations and analyzing procedur... [more]
2105. LAPSE:2023.0869
Numerical Approach Regarding the Effect of the Flight Shape on the Performance of Rotary Dryers from Asphalt Plants
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: aggregates, asphalt, discrete element method, flights shape, rotary dryer
Thedistribution of aggregates in the cross-section of the drum, in the case of equipment used for the production of asphalt mixtures, essentially influences the performance of rotary dryers. In the research carried out in this article, the optimization of the distribution of particles in the active region of the drum was pursued by modifying the geometric shape of the flights, taking into account at the same time the influence of the technological parameters of operation such as drum rotation speed and drum filling degree. The studies were performed using the discrete element method (DEM), and the obtained results revealedthat flight geometry strongly influences drying efficiency. The efficiency of rectangular double-angled type flights is strongly influenced by the drum rotation speed, especially at high levels of filling degree (20%), with the mass of aggregates exposed to drying increasing by 41.11% when drum rotation speed increases from 10 rpm to 15 rpm. Similarly, hook-type fligh... [more]
2106. LAPSE:2023.0860
Design, Heat Transfer, and Visualization of the Milli-Reactor by CFD and ANN
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: flow chemistry, neural network algorithm, PLS, reactor design, reactor stability
This paper proposes a milli-reactor design method incorporating reactor runaway criteria. Based on Computational Fluid Dynamic (CFD) simulation, neural networks are applied to obtain the optimal reactor structure according to the target reaction requirements. Varma’s theory, the critical Nusselt number for stable operation of the flow reactor, is derived. Inserts of the multi-blade structure are designed and investigated to enhance mixing and heat transfer performance. The flow field and heat transfer capacities are obtained by CFD calculations in the range of Re 50−1800. The internal components increase the heat transfer performance up to 21 times, and the pressure drop up to 16 times. The inclined angle of the blade is recommended to be 45°, which can effectively improve heat transfer without generating excessive pressure drop. By partial least squares regression (PLS) analysis, Re and the number of blades are the most critical factors affecting heat transfer, and the five blades and... [more]
2107. LAPSE:2023.0814
Targeted Metabolic Analysis and MFA of Insect Cells Expressing Influenza HA-VLP
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: baculovirus, influenza, insect cells, metabolic flux analysis, VLPs
Virus-like particles (VLPs) are versatile vaccine carriers for conferring broad protection against influenza by enabling high-level display of multiple hemagglutinin (HA) strains within the same particle construct. The insect cell-baculovirus expression vector system (IC-BEVS) is amongst the most suitable platforms for VLP expression; however, productivities vary greatly with particle complexity (i.e., valency) and the HA strain(s) to be expressed. Understanding the metabolic signatures of insect cells producing different HA-VLPs could help dissect the factors contributing to such fluctuations. In this study, the metabolic traces of insect cells during production of HA-VLPs with different valences and comprising HA strains from different groups/subtypes were assessed using targeted metabolic analysis and metabolic flux analysis. A total of 27 different HA-VLP variants were initially expressed, with titers varying from 32 to 512 HA titer/mL. Metabolic analysis of cells during the produc... [more]
2108. LAPSE:2023.0811
An Analysis of Energy and Internal Flow Characteristics of Open Inlet Channel Axial Flow Pumping Devices
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: axial flow pump device, energy characteristics, internal flow characteristics, numerical calculation, open inlet channel
For the purpose of studying the dynamic and inner flow features of an open inlet channel axial flow pump unit, in the present study, numerical calculations using the SST k-ω turbulence model are applied to an open inlet channel axial flow pumping unit based on the NS equation, and experimental validation is then performed. The experimental output indicates that the designed working conditions are Q = 350 L/s, head H = 5.065 m, efficiency η = 79.56%, and the maximum operating head is H = 9.027 m, which is about 1.78 times that of the design head; further, the pump device can operate in a wide range of working conditions. In addition, the design working conditions are within the range of high-efficiency operating conditions. The calculated values and the experimental comparison are all within a 5.0% margin of error; further, the numerical calculations are reliable. The hydraulic loss of the inlet channel under the design condition Q = 350 L/s is 0.0676 m, which satisfies the relationship... [more]
2109. LAPSE:2023.0797
Causal Plot: Causal-Based Fault Diagnosis Method Based on Causal Analysis
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: contribution plot, data-driven fault diagnosis, linear non-Gaussian acyclic model, Machine Learning, multivariate statistical process control, vinyl acetate monomer manufacturing process
Fault diagnosis is crucial for realizing safe process operation when a fault occurs. Multivariate statistical process control (MSPC) has widely been adopted for fault detection in real processes, and contribution plots based on MSPC are a well-known fault diagnosis method, but it does not always correctly diagnose the causes of faults. This study proposes a new fault diagnosis method based on the causality between process variables and a monitored index for fault detection, which is referred to as a causal plot. The proposed causal plot utilizes a linear non-Gaussian acyclic model (LiNGAM), which is a data-driven causal inference algorithm. LiNGAM estimates a causal structure only from data. In the proposed causal plot, the causality of a monitored index of fault detection methods, in addition to process variables, is estimated with LiNGAM when a fault is detected with the monitored index. The process variables having significant causal relationships with the monitored indexes are iden... [more]
2110. LAPSE:2023.0775
Performance Improvement of Micro-Abrasive Jet Blasting Process for Al 6061
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: analysis of variable parameter, micro-abrasive jet blasting, optimal process condition, surface roughness
Aluminum 6061 is a precipitation-hardened alloy, containing magnesium and silicon as its major alloying element, and it is widely used in industries due to its remarkable mechanical properties and weld ability. Several types of machining manners are researched for aluminum 6061 alloys, and micro-abrasive jet blasting (μ-AJM) is one of the most developed processes for improving surface roughness. When operating μ-AJM on aluminum alloys, sufficient consideration of environmental variables such as particle types, nozzle diameter, pressure, standoff distance, and injection time is a prerequisite for the appropriate degree of roughness. To find the optimal conditions, a statistical method of analysis of variables was used to investigate the maximum value for depth, diameter, width, etc., of the blasting surface. According to experimental results, multiple factors have a great influence on the condition of surface roughness. The blasting processes were conducted as square and cylindrical exp... [more]
2111. LAPSE:2023.0756
Analysis of Heat Transfer and Flow Characteristics of a Helically Coiled Tube with Twisted Elliptical in a Low Reynolds Number Flow
February 21, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: corrugated wall, flow characteristics, heat transfer, helically coiled tube, nanofluid
In this paper, the heat transfer and flow characteristics of a helically coiled tube with twisted elliptical in a low Reynolds number (Re = 500−3000) flow were investigated numerically. The working fluid flowed in a laminar regime. Numerical results were compared with empirical correlations in the existing literature, demonstrating the accuracy of the analysis in this study. Firstly, we investigated the effects of geometric parameters and Reynolds number on the heat transfer and flow characteristics. The results showed that lower twist pitch length and semi-major axis length could induce sufficient fluid mixing and a larger temperature gradient near the tube wall, enhancing the heat exchange and producing larger friction resistance. Overall, the heat transfer performances were improved by about 1.04−1.21 times and 1.02−1.23 times for different semi-major axis lengths and different twist pitch lengths, respectively, compared to the smooth helical coil. Secondly, by changing the working... [more]
2112. LAPSE:2023.0663
Monitoring the Recombinant Adeno-Associated Virus Production using Extended Kalman Filter
February 20, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: Bayesian inference, extended Kalman filter, neural ordinary differential equation, parameter estimation, rAAV production supervision, unstructured mechanistic kinetic model
The recombinant adeno-associated virus (rAAV) is a viral vector technology for gene therapy that is considered the safest and most effective way to repair single-gene abnormalities in non-dividing cells. However, improving the viral titer productivity in rAAV production remains challenging. The first step to this end is to effectively monitor the process state variables (cell density, GLC, GLN, LAC, AMM, and rAAV viral titer) to improve the control performance for an enhanced productivity. However, the current approaches to monitoring are expensive, laborious, and time-consuming. This paper presents an extended Kalman filter (EKF) approach used to monitor the rAAV production using the online viable cell density measurements and estimating the other state variables measured at a low frequency. The proposed EKF uses an unstructured mechanistic kinetic model applicable in the upstream process. Three datasets were used for parameter estimation, calibration, and testing, and the data were c... [more]
2113. LAPSE:2023.0660
Statistical Optimisation of Used-Cooking-Oil Degradation by Burkholderia vietnamiensis AQ5-12 and Burkholderia sp. AQ5-13
February 20, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: biodegradation, Burkholderia sp., Burkholderia vietnamiensis, one-factor-at-time (OFAT), response-surface methodology (RSM), used cooking oil
Used cooking oil (UCO) is a hydrocarbon that causes significant environmental pollution globally. Oil is a difficult pollutant to remove from the environment due to its hydrophobic nature. Bioremediation is preferred over chemical and physical remediation approaches as it is more economical and environmentally friendly. Hence, the search for a microbe with outstanding degrading capability is imperative due to the nature of hydrocarbons as pollutants. The current study evaluates the ability of glyphosate degrader isolates, Burkholderia vietnamiensis AQ5-12 and Burkholderia sp. AQ5-13, to degrade UCO as the sole carbon source. The physico-cultural conditions affecting the activities of the isolates were studied using one-factor-at-a-time (OFAT) and response-surface methodology (RSM). The temperature, agitation speed, UCO concentration, nitrogen supply, yeast extract concentration, and inoculum size were optimised during a 7-day incubation period. Based on the OFAT results, the highest de... [more]
2114. LAPSE:2023.0650
Dynamic Risk Assessment of High Slope in Open-Pit Coalmines Based on Interval Trapezoidal Fuzzy Soft Set Method: A Case Study
February 20, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: dynamic risk assessment, high slope, open-pit coalmine, safety management and control
Effective high slope risk assessment plays an important role in the safety management and control of the open-pit coal mining process. Traditional slope stability risk assessment methods rarely consider the time factor or evaluate the dynamic change of high slope in an open-pit mine at a certain time in a sensitivity assessment. This paper develops an interval trapezoidal fuzzy soft set method to achieve the high slope dynamic risk evaluation. The proposed dynamic interval trapezoidal fuzzy soft set method for risk assessment of high slope in an open-pit coal mine is developed by integrating the time points and weights of slope risk factors. The extended interval trapezoidal fuzzy soft set was used to calculate the weights of risk factors at different times, and the Fuzzy Analytical Hierarchy Process (FAHP) method was applied to determine the weights of risk factors. The weight change of different risk factors with time can be easily achieved with the proposed method. As a case study,... [more]
2115. LAPSE:2023.0648
The Estimation of Centrifugal Pump Flow Rate Based on the Power−Speed Curve Interpolation Method
February 20, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: centrifugal pump, flow estimation, PN curves interpolation, sensorless
During the global energy crisis, it is essential to improve the energy efficiency of pumps by adjusting the pump’s control strategy according to the operational states. However, monitoring the pump’s operational states with the help of external sensors brings both additional costs and risks of failure. This study proposed an interpolation method based on PN curves (power−speed curves) containing information regarding motor shaft power, speed, and flow rate to achieve high accuracy in predicting the pump’s flow rates without flow sensors. The impact factors on the accuracy of the estimation method were analyzed. Measurements were performed to validate the feasibility and robustness of the PN curve interpolation method and compared with the QP and back-propagation neural network (BPNN) methods. The results indicated that the PN curve interpolation method has lower errors than the other two prediction models. Moreover, the average absolute errors of the PN curve interpolation method in th... [more]
2116. LAPSE:2023.0172
Study on the Fracturing of Rock by High-Speed Water Jet Impact
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: confining pressure, crack propagation, high-speed water jet, jet flow angle
Due to the opaqueness of rock and the limitation of detection technology, it is impossible to accurately describe the crack growth process and determine the law of rock breakage. Based on smoothed particle hydrodynamics and the finite element method (SPH-FEM), a numerical model for high-speed water jet breaking was established in this work to simulate the fragmentation process of rock impacted by a high-speed water jet, and to study the effects of different jet angles on the propagation of microscopic cracks inside the rock. Additionally, we further analyzed the jet impact angle on the microscopic crack propagation trend of the rock by applying confining pressure to the rock. Theoretical and experimental analyses showed that the inclination angle of the jet determined the direction of axial crack propagation in the tension-type center. When the inclination angle of the jet exceeded 20°, the ability of water jet erosion was insufficient, and the efficiency of rock fragmentation was low.... [more]
2117. LAPSE:2023.0165
Prediction of Surface Subsidence of Deep Foundation Pit Based on Wavelet Analysis
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: deep foundation pit, noise reduction, RBF neural network, subsidence, wavelet
Predicting surface settlement in deep foundation pit engineering plays a central role in the safety of foundation pit construction. Recently, static or dynamic methods are usually applied to predict ground settlement in deep foundation pit projects. In this work, we propose a model combining wavelet noise reduction and radial basis neural network (XW-RBF) to reduce noise interference in monitoring data. The results show that the XW-RBF model predicts an average relative error of 0.77 and a root average square error of 0.13. The prediction performance is better than the original data prediction results with noise structure and has higher prediction accuracy. The noise data caused by the interference of construction and the surrounding environment in the original data can be removed via the wavelet noise reduction method, with the discreteness of the original data reducing by 30%. More importantly, our results show that the XW-RBF model can reflect the law of data change to predict the f... [more]
2118. LAPSE:2023.0121
Subcritical Water Extraction as an Effective Technique for the Isolation of Phenolic Compounds of Achillea Species
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: green extraction techniques, phenolic compounds, principal component analysis, yarrow
The genus Achillea has significant medical potential due to the presence of highly bioactive compounds in its chemical composition. To take advantage of plants’ biomedical potential, it is of great importance to use a proper extraction process. This study aimed to determine and compare the preliminary chemical composition of five different Achillea species extracted with two conventional (infusion and maceration) and two non-conventional (ultrasound-assisted extraction (UAE) and Subcritical water extraction (SWE)) techniques. The extracts were prepared using the previously described procedures for infusion, maceration, UAE and SWE extraction. For all extracts, the extraction yield (dry extract (DE)) was determined. The analyzed extracts were preliminarily chemically characterized spectrophotometrically in terms of total phenolic content (TPC) and total flavonoid content (TFC). The obtained results showed that non-conventional techniques delivered higher values of TPC and TFC than conve... [more]
2119. LAPSE:2023.0115
Screening of Azotobacter, Bacillus and Pseudomonas Species as Plant Growth-Promoting Bacteria
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: beneficial effects, non-sterile soil, plant growth-promoting bacteria (PGPB), sterile soil
In this study, bacteria from the genus of Azotobacter, Bacillus and Pseudomonas were isolated from the roots of Phaseolus vulgaris and used as plant growth-promoting bacteria for Sinapis alba L., Brassica napus L., Amaranthus retroflexus L., Linum usitatissimum L., Panicum miliaceum L. and Rumex patientia L. plants. The results showed that all three bacteria had different effects on plants growth considering both sterile and non-sterile soil. Bacillus sp. induced the greatest influence in terms of the root length of Sinapis alba L. grown in sterile soil (with 28%), while considering non-sterile soil, Pseudomonas sp. increased the root and shoot length by 11.43% and 25.15%, respectively, compared to the blank sample. Azotobacter sp. exerted the highest beneficial influence on Brassica napus L. growth in non-sterile soil, since the root and shoot lengths were stimulated with 27.64% and 52.60%, respectively, compared to uninoculated plants. Bacillus sp. had a positive effect on the growth... [more]
2120. LAPSE:2023.0084
Evaluation of the Performance of a Heat Pipe for Pre-Frozen Soil around a Solar Support by a Numerical Method
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: frozen soil, heat pipe, heat transfer, porous media
The base of solar collector systems is usually installed in soil that contains moisture. In cold regions, due to the low ambient temperature, the moisture in the soil freezes, creating a risk of frost heave. This study analyzed the frost heave mechanism of power transmission and transformation foundation, clarified the factors affecting soil frost heave and the way to solve soil layer frost heave, and proposed the use of heat transfer elements to pre-frozen soil layers to prevent the foundation of the solar collector system from freezing. A numerical model of the ground heat exchange pipes in soil was established. The effects of different soil types, soil moisture content, and the effective radius and operating time on the heat transfer performance of the system were investigated by the verified numerical model. The results show that the heat pipe pre-freezing technology can reduce the drop in soil temperature, thereby increasing the temperature difference between the ground heat excha... [more]
2121. LAPSE:2023.0083
Numerical Study of the Purge Flow’s Effect on the Loss Mechanism of the Blocking and Shear Effects
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: blocking effect, purge flow, seal structure, sealing efficiency, shear loss, tangential velocity, tangential velocity gradient
The loss mechanism of shear and upstream blockage caused by the interaction of the purged flow and ingested gas needs to be systematically studied to optimize the flow near the rim. In order to study the causes and influence factors of blocking and shearing effects and quantify their losses reasonably, the three-dimensional unsteady numerical method validated by the experiment data was adopted to study the turbine with three kinds of sealing structures. The block and shear loss are quantified by integrating the dissipation coefficient in the volume where the specific aerodynamic loss occurs. The result indicated that there was a larger radial velocity and smaller tangential velocity of the purged flow relative to the main flow caused the blocking effect. Therefore, its loss is affected by the seal flow and seal structure. The shear effect is mainly affected by the tangential velocity gradient and the axial velocity gradient near the cavity exit. The contribution of the tangential veloc... [more]
2122. LAPSE:2023.0078
Annual Electricity and Energy Consumption Forecasting for the UK Based on Back Propagation Neural Network, Multiple Linear Regression, and Least Square Support Vector Machine
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: back propagation neural network, electricity and energy consumption, forecasting, least square support vector machine, machine learning algorithm, multiple linear regression, UK
The long-term demand forecast for annual national electricity and energy consumption plays a vital role in future strategic planning, power system installation programming, energy investment planning, and next-generation unit construction. Three machine learning algorithms of BP-NN, MLR, and LS-SVM were chosen for training forecasting models, with the data on population, GDP, mean temperature, sunshine, rainfall, and frost days in 1993−2019 serving as the input variables. The total data were divided by 70% into the training set (1993−2011) and 30% into the test set (2012−2019), in chronological order. RMSE, MAPE, and MaxError were adopted as the performance criteria. The statistical results show that the gross population of the UK increases year by year from 1993 to 2020. The GDP generally increases before 2007 but has a decline, and then varies with a large amplitude afterward. The electricity and energy consumption of the UK generally increase from 1993 and reach a peak around 2005.... [more]
2123. LAPSE:2023.0066
Scenario-Driven Methodology for Cascading Disasters Risk Assessment of Earthquake on Chemical Industrial Park
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: cascading disasters, cross-impact analysis (CIA) model, damping interpretation structural model (DISM), earthquake
With the increase in industrial accidents induced by natural disasters, the study of earthquake risk assessment has been widely considered by scholars. However, the cascade evolution of Natech (natural−technological) disasters has not been thoroughly studied, especially in chemical parks with complex technological processes. From the perspective of scenario deduction, combined with cross-impact analysis and a damping interpretation structural model, this paper analyzes the evolution process of cascade disaster in a chemical industrial park after the Wenchuan earthquake. At the same time, a visual network risk assessment model is constructed to identify the impact of earthquake cascade disasters on the park. The simulation results show that the scenario-driven risk assessment method proposed in this paper can directly reflect the coupling relationship and propagation path among the derived events and realize dynamic, intuitive and structured disaster expression to deal with the earthqua... [more]
2124. LAPSE:2023.0020
Robust State of Charge Estimation for Hybrid Electric Vehicles: Framework and Algorithms
February 17, 2023 (v1)
Subject: Numerical Methods and Statistics
Keywords: electric vehicles, H∞ filter, nonlinear diffusion filter, robust SoC estimation
State of Charge (SoC) estimation is one of the most significant and difficult techniques to promote the commercialization of electric vehicles (EVs). Suffering from various interference in vehicle driving environment and model uncertainties due to the strong time-variant property and inconsistency of batteries, the existing typical SoC estimators such as coulomb counting and extended Kalman filter cannot perform their theoretically optimal efficacy in practical applications. Aiming at enhancing the robustness of SoC estimation and improving accuracy under the real driving conditions with noises and uncertainties, this paper proposes a framework consisting of (1) an adaptive-κ nonlinear diffusion filter to reduce the noise in current measurement, (2) a self-learning strategy to estimate and remove the zero-drift, (3) a coulomb counting algorithm to realize open-loop SoC estimation, (4) an H∞ filter to implement closed-loop robust estimation, and (5) a data fusion unite to achieve the fi... [more]

