bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerically Stable form of Green’s Function for a Free-Free Uniform Timoshenko Beam
Authors: Mazilu Traian
Published: December 2022

Beam models are widely applied in civil engineering, transport, and industry because the beams are basic structural elements. When dealing with the high-order modes of beam in the context of applying the modal analysis method, the numerical instability issue affects the numeric simulation accuracy in many boundary conditions. There are two solutions in literature to overcome this shortcoming, namely refinement of the asymptotic form for the high order modes and reshaping the terms within the equation of the modes to eliminate the source of the numerical instability. In this paper, the numerical instability issue is signalled when the standard form of Green’s function, which includes hyperbolic functions, is applied to a free-free Timoshenko length-long beam. A new way is proposed based on new set of eigenfunctions, including an exponential function, to construct a new form of Green’s function. To this end, it starts from a new general form of Green’s function and the characteristic equation is obtained; then, based on the boundary condition, the Green’s function associated to the differential operator of the free-free Timoshenko beam is distilled. The numerical stability of the new form of the Green’s function is verified in a numerical application and the results are compared with those obtained by using the standard form of the Green’s function.
Advances in Financial Leasing Mechanism Designs
Authors: Cananà Lucianna , De Cesare Luigi , Ferrara Massimiliano
Published: December 2022

Financial leasing contracts usually include specific clauses for early termination of the agreement in the event that the lessee defaults. The lessor might, therefore, not immediately ask for termination of the financial lease agreement in order to take advantage of the increment in fees accrued due to the default interest. The analysis presented in this work aims to find the conditions determining the optimal time to rescind the contract, when the arrears’ interest rate is higher than the outstanding fees’ interest rate established in the contract and when the return of alternative investments is deterministic. In this paper, we study the optimal time for advanced termination of a leasing contract to maximize the wealth of the lessor against the natural expiry of the contract. We prove that the optimal time can be found through the intersection of the instantaneous force of interest of a lessor’s credit at a certain date and the instantaneous force of interest of the opportunity cost of capital, or at the initial date or maturity date. To this end, we provide a detailed list of cases in which it is appropriate to terminate the contract or not. The problem is formulated in the case where the opportunity cost follows deterministic and semi-deterministic dynamics.
On the Degree Distribution of Haros Graphs
Authors: Calero-Sanz Jorge
Published: December 2022

Haros graphs are a graph-theoretical representation of real numbers in the unit interval. The degree distribution of the Haros graphs provides information regarding the topological structure and the associated real number. This article provides a comprehensive demonstration of a conjecture concerning the analytical formulation of the degree distribution. Specifically, a theorem outlines the relationship between Haros graphs, the corresponding continued fraction of its associated real number, and the subsequent symbolic paths in the Farey binary tree. Moreover, an expression that is continuous and piecewise linear in subintervals defined by Farey fractions can be derived from an additional conclusion for the degree distribution of Haros graphs.
A Lightweight Deep Learning Approach for Liver Segmentation
Authors: Bogoi Smaranda , Udrea Andreea
Published: December 2022

Liver segmentation is a prerequisite for various hepatic interventions and is a time-consuming manual task performed by radiology experts. Recently, various computationally expensive deep learning architectures tackled this aspect without considering the resource limitations of a real-life clinical setup. In this paper, we investigated the capabilities of a lightweight model, UNeXt, in comparison with the U-Net model. Moreover, we conduct a broad analysis at the micro and macro levels of these architectures by using two training loss functions: soft dice loss and unified focal loss, and by substituting the commonly used ReLU activation function, with the novel Funnel activation function. An automatic post-processing step that increases the overall performance of the models is also proposed. Model training and evaluation were performed on a public database—LiTS. The results show that the UNeXt model (Funnel activation, soft dice loss, post-processing step) achieved a 0.9902 dice similarity coefficient on the whole CT volumes in the test set, with 15× fewer parameters in nearly 4× less inference time, compared to its counterpart, U-Net. Thus, lightweight models can become the new standard in medical segmentation, and when implemented thoroughly can alleviate the computational burden while preserving the capabilities of a parameter-heavy architecture.
Dynamical Analysis and Adaptive Finite-Time Sliding Mode Control Approach of the Financial Fractional-Order Chaotic System
Authors: Johansyah Muhamad Deni , Sambas Aceng , Mobayen Saleh , Vaseghi Behrouz , Al-Azzawi Saad Fawzi , Sukono  , Sulaiman Ibrahim Mohammed
Published: December 2022

In this work, we studied the complex behaviors of the fractional-order financial chaotic system, consisting of a simple, relatively chaotic system with two quadratic nonlinearities (QN) and a sextic nonlinearity (SN). We completed and enriched the results presented in the study of Subartini et al. (2021). As a result of this, our study focused more on the fractional order and adaptive finite-time sliding mode control in the financial risk chaotic system. The dynamical behaviors of the financial chaotic system (FCS) with two QN and an SN were analyzed, and the stability was investigated via the Cardano method. The stability analysis showed that the real part of all the roots was negative, which confirmed the stability of the new system under the typical parameters. By using the MATLAB simulation, these properties were characterized, including the phase portraits, 0-1 test, Poincaré map, bifurcation diagram, and Lyapunov exponent. The analysis showed that the financial risk chaotic system of fractional order was able to exhibit chaotic behavior and periodical behavior. In spite of external perturbations and uncertainty, an adaptive finite-time sliding mode control strategy was devised to guide the states of the financial chaotic system to the origin in a finite amount of time. MATLAB phase plots were employed in this study to illustrate all the main results.
Three-Echelon Supply Chain Management with Deteriorated Products under the Effect of Inflation
Authors: Padiyar Surendra Vikram Singh , Vandana  , Singh Shiv Raj , Singh Dipti , Sarkar Mitali , Dey Bikash Koli , Sarkar Biswajit
Published: December 2022

A business can be properly managed globally when it is under a supply chain. When it is a global supply chain, inflation has a huge effect on supply chain profit. Another important factor is the deterioration of products. Products can deteriorate during storage or transportation, which badly affects each supply chain player. This study develops a three-echelon supply chain model through which products can be delivered to customers easily. In this model, one producer and multiple buyers are considered, and each buyer has a separate group in which multiple suppliers have been taken. Inflation is also added to the model for inflationary fluctuations. To understand this model in real life, a numerical example is discussed and the total profit from the supply chain is extracted. Sensitivity analysis is also shown at the end of the model to find out the effect on the model due to changes in some parameters that affect this model highly. After developing this model, it was found that if the inflation rate falls, then the total profit will increase continuously. On the contrary, if the inflation rate increases, then, in this situation, the total profit will decrease continuously. At present, vaccine makers’ total profit can support the economy of any country, and in this model, the inflation rate decreases as profit increases.
Detection of Unknown DDoS Attack Using Reconstruct Error and One-Class SVM Featuring Stochastic Gradient Descent
Authors: Shieh Chin-Shiuh , Nguyen Thanh-Tuan , Chen Chun-Yueh , Horng Mong-Fong
Published: December 2022

The network system has become an indispensable component of modern infrastructure. DDoS attacks and their variants remain a potential and persistent cybersecurity threat. DDoS attacks block services to legitimate users by incorporating large amounts of malicious traffic in a short period or depleting system resources through methods specific to each client, causing the victim to lose reputation, finances, and potential customers. With the advancement and maturation of artificial intelligence technology, machine learning and deep learning are widely used to detect DDoS attacks with significant success. However, traditional supervised machine learning must depend on the categorized training sets, so the recognition rate plummets when the model encounters patterns outside the dataset. In addition, DDoS attack techniques continue to evolve, rendering training based on conventional data models unable to meet contemporary requirements. Since closed-set classifiers have excellent performance in cybersecurity and are quite mature, this study will investigate the identification of open-set recognition issues where the attack pattern does not accommodate the distribution learned by the model. This research proposes a framework that uses reconstruction error and distributes hidden layer characteristics to detect unknown DDoS attacks. This study will employ deep hierarchical reconstruction nets (DHRNet) architecture and reimplement it with a 1D integrated neural network employing loss function combined with spatial location constraint prototype loss (SLCPL) as a solution for open-set risks. At the output, a one-class SVM (one-class support vector machine) based on a random gradient descent approximation is used to recognize the unknown patterns in the subsequent stage. The model achieves an impressive detection rate of more than 99% in testing. Furthermore, the incremental learning module utilizing unknown traffic labeled by telecom technicians during tracking has enhanced the model’s performance by 99.8% against unknown threats based on the CICIDS2017 Friday open dataset.
Health Status-Based Predictive Maintenance Decision-Making via LSTM and Markov Decision Process
Authors: Zheng Pan , Zhao Wenqin , Lv Yaqiong , Qian Lu , Li Yifan
Published: December 2022

Maintenance decision-making is essential to achieve safe and reliable operation with high performance for equipment. To avoid unexpected shutdown and increase machine life as well as system efficiency, it is fundamental to design an effective maintenance decision-making scheme for equipment. In this paper, we propose a novel maintenance decision-making method for equipment based on Long Short-Term Memory (LSTM) and Markov decision process, which can provide specific maintenance strategies in different degradation stages of the system. Specifically, the LSTM model is firstly applied to predict the remaining service life of equipment to distinguish its health state quantitatively. Then, based on the bearing residual life prediction curve, the degradation process model is constructed, and the corresponding parameters of the model are identified. Finally, the bearing degradation curve is obtained by the degradation process model, based on which the Markov decision process model is constructed to provide accurate maintenance strategies for different health conditions of system. To demonstrate the effectiveness of the proposed method, an experimental study with the full life cycle data set of rolling bearings is carried out. The experimental results show that the proposed method can achieve efficient maintenance decisions for bearings under different health states, which provides a feasible solution for the maintenance of bearing systems.
Imbalanced Multimodal Attention-Based System for Multiclass House Price Prediction
Authors: Li Yansong , Branco Paula , Zhang Hanxiang
Published: December 2022

House price prediction is an important problem for individuals, companies, organizations, and governments. With a vast amount of diversified and multimodal data available about houses, the predictive models built should seek to make the best use of these data. This leads to the complex problem of how to effectively use multimodal data for house price prediction. Moreover, this is also a context suffering from class imbalance, an issue that cannot be disregarded. In this paper, we propose a new algorithm for addressing these problems: the imbalanced multimodal attention-based system (IMAS). The IMAS makes use of an oversampling strategy that operates on multimodal data, namely using text, numeric, categorical, and boolean data types. A self-attention mechanism is embedded to leverage the usage of neighboring information that can benefit the model’s performance. Moreover, the self-attention mechanism allows for the determination of the features that are the most relevant and adapts the weights used according to that information when performing inference. Our experimental results show the clear advantage of the IMAS, which outperforms all the competitors tested. The analysis of the weights obtained through the self-attention mechanism provides insights into the features’ relevance and also supports the importance of using this mechanism in the predictive model.
Extremal Analysis of Flooding Risk and Its Catastrophe Bond Pricing
Authors: Li Jiayi , Cai Zhiyan , Liu Yixuan , Ling Chengxiu
Published: December 2022

Catastrophic losses induced by natural disasters are receiving growing attention because of the severe increases in their magnitude and frequency. We first investigated the extreme tail behavior of flood-caused economic losses and maximum point precipitation based on the peaks-over-threshold method and point process (PP) model and its extreme tail dependence. We found that both maximum point precipitation and direct economic losses are well-modeled by the PP approach with certain tail dependence. These findings were further utilized to design a layered compensation insurance scheme using estimated value-at-risk (VaR) and conditional VaR (CVaR) among all stakeholders. To diversify the higher level of losses due to extreme precipitation, we designed a coupon paying catastrophe bond triggered by hierarchical maximum point precipitation level, based on the mild assumption on the independence between flood-caused risk and financial risk. The pricing sensitivity was quantitatively analyzed in terms of the tail risk of the flood disaster and the distortion magnitude and the market risk in Wang’s transform. Our trigger process was carefully designed using a compound Poisson process, modeling both the frequency and the layered intensity of flood disasters. Lastly, regulations and practical suggestions are provided regarding the flood risk prevention and warning.
Factors Affecting Health-Related Quality of Life among Healthcare Workers during COVID-19: A Cross-Sectional Study
Authors: Jung Gyehyun , Oh Jihyun
Published: December 2022

Background and Objectives: Healthcare workers are threatened by psychological well-being and mental health problems in disasters related to new infectious diseases, such as COVID-19, and this can also have a negative impact on health-related quality of life. Health-related quality of life of healthcare workers should not be neglected because it is closely related to patient safety. This study aimed to identify the relationship between mental health problems, psychological safety, sleep quality, and health-related quality of life of healthcare workers and factors that influence health-related quality of life during the COVID-19 pandemic. Materials and Methods: Data were collected from 301 healthcare workers working in five general hospitals with more than 300 beds in two provinces from 5 July 2021 to 16 July 2021. Data were analyzed using SPSS WIN 27.0. The data were analyzed using t-test, one-way analysis of variance, and stepwise multiple regression. Results: Our results showed that there was a significant difference in regular exercise, religion, economic status, and sleep quality. The DASS-21 stress, economic status, and alcohol consumption were factors affecting the total health-related quality of life. In the subcategories, the physical component score was influenced by DASS-21 stress and economic status, while the mental component score was influenced by DASS-21 depression, economic status, alcohol consumption, and sleep quality. Conclusions: Health care workers need continuous and active monitoring of their health level and quality of life, as they are at a risk of increasing work burden and infection due to prolonged exposure to COVID-19 as well as mental health issues such as stress and depression. Additionally, at the individual level, active participation in various programs that can raise awareness of health-related quality of life along with physical health promotion activities should be encouraged. At the organizational level, it is necessary to prepare a compensation system, such as adjusting the workload of healthcare workers and ensuring break time; at the government level, disaster-related policies are needed to ensure a safe working environment for health care workers.
State-of-the-Art of Polymer/Fullerene C60 Nanocomposite Membranes for Water Treatment: Conceptions, Structural Diversity and Topographies
Authors: Kausar Ayesha , Ahmad Ishaq , Maaza Malik , Eisa M. H.
Published: December 2022

To secure existing water resources is one of the imposing challenges to attain sustainability and ecofriendly world. Subsequently, several advanced technologies have been developed for water treatment. The most successful methodology considered so far is the development of water filtration membranes for desalination, ion permeation, and microbes handling. Various types of membranes have been industrialized including nanofiltration, microfiltration, reverse osmosis, and ultrafiltration membranes. Among polymeric nanocomposites, nanocarbon (fullerene, graphene, and carbon nanotubes)-reinforced nanomaterials have gained research attention owing to notable properties/applications. Here, fullerene has gained important stance amid carbonaceous nanofillers due to zero dimensionality, high surface areas, and exceptional physical properties such as optical, electrical, thermal, mechanical, and other characteristics. Accordingly, a very important application of polymer/fullerene C60 nanocomposites has been observed in the membrane sector. This review is basically focused on talented applications of polymer/fullerene nanocomposite membranes in water treatment. The polymer/fullerene nanostructures bring about numerous revolutions in the field of high-performance membranes because of better permeation, water flux, selectivity, and separation performance. The purpose of this pioneering review is to highlight and summarize current advances in the field of water purification/treatment using polymer and fullerene-based nanocomposite membranes. Particular emphasis is placed on the development of fullerene embedded into a variety of polymer membranes (Nafion, polysulfone, polyamide, polystyrene, etc.) and effects on the enhanced properties and performance of the resulting water treatment membranes. Polymer/fullerene nanocomposite membranes have been developed using solution casting, phase inversion, electrospinning, solid phase synthesis, and other facile methods. The structural diversity of polymer/fullerene nanocomposites facilitates membrane separation processes, especially for valuable or toxic metal ions, salts, and microorganisms. Current challenges and opportunities for future research have also been discussed. Future research on these innovative membrane materials may overwhelm design and performance-related challenging factors.
On the Permeation of Polychlorinated Dibenzodioxins and Dibenzofurans through Lipid Membranes: Classical MD and Hybrid QM/MM-EDA Analysis
Authors: Alvarado Raúl , Cárdenas Gustavo , Nogueira Juan J. , Ramos-Berdullas Nicolás , Mandado Marcos
Published: December 2022

The permeation of dioxin-like pollutants, namely, chlorinated dibenzodioxins and dibenzofurans, through lipid membranes has been simulated using classic molecular dynamics (CMD) combined with the umbrella sampling approach. The most toxic forms of chlorinated dibenzodioxin and dibenzofuran, 2,3,7,8-tetrachloro-p-dibenzodioxin (TCDD) and 2,3,7,8-tetrachlorodibenzofuran (TCDF), and a dioleyl-phosphatidylcholine (DOPC) lipid membrane of 50 Å wide have been chosen for our study. The free energy profile shows the penetration process is largely favoured thermodynamically (ΔG ≈ −12 kcal/mol), with a progressively decrease of the free energy until reaching the energy minima at distances of 8 Å and 9.5 Å from the centre of the membrane for, respectively, TCDD and TCDF. At the centre of the membrane, both molecules display subtle local maxima with free energy differences of 0.5 and 1 kcal/mol with respect to the energy minima for TCDD and TCDF, respectively. Furthermore, the intermolecular interactions between the molecules and the lipid membrane have been characterized at the minima and the local maxima using hybrid quantum mechanics/molecular mechanics energy decomposition analysis (QM/MM-EDA). Total interaction energies of −17.5 and −16.5 kcal/mol have been found at the energy minima for TCDD and TCDF, respectively. In both cases, the dispersion forces govern the molecule-membrane interactions, no significant changes have been found at the local maxima, in agreement with the classical free energy profile. The small differences found in the results obtained for TCDD and TCDF point out that the adsorption and diffusion processes through the cell membrane are not related to the different toxicity shown by these pollutants.
Hydrothermal Stability of Hydrogen-Selective Carbon–Ceramic Membranes Derived from Polybenzoxazine-Modified Silica–Zirconia
Authors: Lawal Sulaiman Oladipo , Nagasawa Hiroki , Tsuru Toshinori , Kanezashi Masakoto
Published: December 2022

This work investigated the long-term hydrothermal performance of composite carbon-SiO2-ZrO2 membranes. A carbon-SiO2-ZrO2 composite was formed from the inert pyrolysis of SiO2-ZrO2-polybenzoxazine resin. The carbon-SiO2-ZrO2 composites prepared at 550 and 750 °C had different surface and microstructural properties. A carbon-SiO2-ZrO2 membrane fabricated at 750 °C exhibited H2 selectivity over CO2, N2, and CH4 of 27, 139, and 1026, respectively, that were higher than those of a membrane fabricated at 550 °C (5, 12, and 11, respectively). In addition to maintaining high H2 permeance and selectivity, the carbon-SiO2-ZrO2 membrane fabricated at 750 °C also showed better stability under hydrothermal conditions at steam partial pressures of 90 (30 mol%) and 150 kPa (50 mol%) compared with the membrane fabricated at 500 °C. This was attributed to the complete pyrolytic and ceramic transformation of the microstructure after pyrolysis at 750 °C. This work thus demonstrates the promise of carbon-SiO2-ZrO2 membranes for H2 separation under severe hydrothermal conditions.
Study of Membranes with Nanotubes to Enhance Osmosis Desalination Efficiency by Using Machine Learning towards Sustainable Water Management
Authors: Amari Abdelfattah , Ali Mohammed Hasan , Jaber Mustafa Musa , Spalevic Velibor , Novicevic Rajko
Published: December 2022

Water resources management is one of the most important issues nowadays. The necessity of sustainable management of water resources, as well as finding a solution to the water shortage crisis, is a question of our survival on our planet. One of the most important ways to solve this problem is to use water purification systems for wastewater resources, and one of the most necessary reasons for the research of water desalination systems and their development is the problem related to water scarcity and the crisis in the world that has arisen because of it. The present study employs a carbon nanotube-containing nanocomposite to enhance membrane performance. Additionally, the rise in flow brought on by a reduction in the membrane’s clogging surface was investigated. The filtration of brackish water using synthetic polyamide reverse osmosis nanocomposite membrane, which has an electroconductivity of 4000 Ds/cm, helped the study achieve its goal. In order to improve porosity and hydrophilicity, the modified raw, multi-walled carbon nanotube membrane was implanted using the polymerization process. Every 30 min, the rates of water flow and rejection were evaluated. The study’s findings demonstrated that the membranes have soft hydrophilic surfaces, and by varying concentrations of nanocomposite materials in a prescribed way, the water flux increased up to 30.8 L/m2h, which was notable when compared to the water flux of the straightforward polyamide membranes. Our findings revealed that nanocomposite membranes significantly decreased fouling and clogging, and that the rejection rate was greater than 97 percent for all pyrrole-based membranes. Finally, an artificial neural network is utilized to propose a predictive model for predicting flux through membranes. The model benefits hyperparameter tuning, so it has the best performance among all the studied models. The model has a mean absolute error of 1.36% and an R2 of 0.98.
Preparation and Characterization of Poly(Lactic Acid)/Poly (ethylene glycol)-Poly(propyl glycol)-Poly(ethylene glycol) Blended Nanofiber Membranes for Fog Collection
Authors: Aijaz Muhammad Omer , Yang Seong Baek , Karim Mohammad Rezaul , Othman Mohd Hafiz Dzarfan , Alnaser Ibrahim Abdullah
Published: December 2022

Fog is a resource with great potential to capture fresh water from the atmosphere, regardless of the geographical and hydrological conditions. Micro-sized fog collection requires materials with hydrophilic/phobic patterns. In this study, we prepared hydrophilic poly(lactic acid) (PLA)/poly(ethylene glycol)-poly(propyl glycol)-poly(ethylene glycol) (PEG-PPG-PEG) blended nanofiber membranes with various PEG-PPG-PEG concentrations by electrospinning. Changes in the morphological and chemical properties, surface wettability, and thermal stability of the PLA/PEG-PPG-PEG composite nanofiber membranes were confirmed using field-emission scanning electron microscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, contact angle testing, and thermogravimetric analysis. As the PEG-PPG-PEG content of the nanofiber membranes increased, their hydrophilicity increased. Water stability, membrane porosity, and water transport rate tests were also conducted to observe the behavior of the hydrophilic PLA nanocomposite membranes in aqueous media. Finally, we applied the PLA-based membranes as fog collectors. As the PEG-PPG-PEG content of the nanofiber membranes increased, their ability to collect fog increased by over 40% compared with that collected by a pure PLA membrane. The prepared membranes not only improve the ability of fog collectors to harvest water but also broaden the use of PLA-based membranes in multiple applications, including tissue engineering, drug delivery, scaffolds, and pharmaceuticals.
Analysis of the First Metallic Works That Represented a Geometric Innovation in Their Architectural Application: The Origin of the Architecture-Engineering Dichotomy
Authors: Rueda Márquez de la Plata Adela , Cruz Franco Pablo Alejandro
Published: December 2022

This research analyses the geometric modifications and improvements that the application of the technique of metallurgy meant for architecture. In the early days of engineering and without having the historical burden that architecture bore, the small variations in the classical definition of geometry meant the greatest advances at a structural and conceptual level in the world of metal structures. The use of metal as a structural element capable of containing new uses and responding to the great challenges that progress required was definitive for the development of the new architecture and paradigms of the new century. The new metallic materials and their mathematical and constructive models were the cause and effect of what would be the basis of the great change in modern architecture and engineering and would lay the foundations of today’s world. The interaction of these two new disciplines, architecture and engineering, and their relationship with metal is the basis of this research, which aims to find out where, when, and how these geometric changes took place that started to change the conception of metal structures.
An Improved Optimization Model to Predict the Deposition Rate and Smoothness of Ni Pulse-Reverse Electroplating Based on ANN and Experimental Results
Authors: Koochaksaraie Reza Ahmadian , Barazandeh Farshad , Akbari Mohammad
Published: December 2022

The metallic layers are an essential part of MEMS (micro electromechanical system) devices, and their deposition process must be accurately controlled; this may lead to difficulties as there are many input parameters for such a process. This research focuses on the input parameters’ effects on the Ni pulse-reverse electroplating. A neural network was constructed to characterize the pulse-reverse nickel electroforming process parameters. The sample training has accurately established the mapping relationship between input and output parameters. The nickel layer thickness and surface roughness prediction in the pulse-reverse electroplating process was realized and verified by experimental tests with a test error of 3.3%. Then, the effect of direct and reverse current density, deposition time, structure width, and stirring speed as input parameters on the thickness and surface roughness are investigated. Finally, a novel 4D diagram has been developed to derive the optimal values of direct and reverse current density relative to thickness, surface roughness, and deposition time. This diagram can help researchers and industries find suitable parameters to achieve the desired deposited Ni layer’s properties.
Numerical Simulation of Multi-Physics Fields in Fused Magnesia Furnace
Authors: Jiang Tianchi , Zhang Weijun
Published: December 2022

In this paper, a 3D transient multi-physical field model is developed to capture the complex processes inside a fused magnesia furnace. The multi-physics model integrates electromagnetism, thermodynamics, decomposition reactions, and flow. The three-phase submerged magnesia furnace includes an arc, magnesite ores, a melting pool, and a solidification ingot. For a more comprehensive analysis of the optimal design of industrial operations, the influence of the key index of electrode insertion depth on temperature and reaction is also discussed. The results show that the current density in the fused magnesia furnace is almost the same as the joule heat distribution, and there is an obvious area of low energy density affected by the skin effect, which leads to the waste of electric energy. The temperature at the center of the arc reaches 12,000 K, and the plasma areas formed at the end of the three electrodes are connected to each other to form a closed current path, which provides energy for the process of melting magnesia. The arc region is an ellipsoid with a length of ~30 mm and a diameter of ~49 mm. The decomposition reaction of magnesite mainly occurs in the arc area, and the radiation heat provided by the high-temperature arc is used as the heat source. There is almost no magnesite in the molten pool, and the molten pool only provides energy for the melting process of magnesia. When the electrode insertion depth is 0.4, 0.5, 0.6, and 0.7 m, the arc length is 0.049 m, 0.066 m, 0.068 m, and 0.059 m, respectively. According to the simulation results, there is an optimal electrode insertion depth.
Thermodynamic Simulation of Solidification of Ti-Containing Steels with Consideration for Possibility of Peritectic Transformation and Second Phase Precipitation
Authors: Gorbachev Igor , Popov Vladimir
Published: December 2022

An algorithm is proposed for predicting the phase composition of titanium-containing steels after solidification. The approach is based on thermodynamic calculations and provides for crystallization through the formation of ferrite and austenite, as well as a peritectic reaction. The algorithm takes into account the possibility of precipitation of TiN, TiS, MnS and TiC0.5S0.5 from the liquid phase upon crystallization. Two possible behaviors of ferrite upon crystallization are considered: frozen and fast diffusion of elements in the metal sublattice of this phase. Calculations illustrating the operation of the proposed algorithm have been performed.
Fatigue Limit Improvement and Rendering Surface Defects Harmless by Shot Peening for Carburized Steel
Authors: Tsuji Toshiya , Fujino Masashi , Takahashi Koji
Published: December 2022

Remanufacturing has become popular as a system for reducing CO2 emissions caused by the life cycle of products. Therefore, producing more components via remanufacturing is important. Shot peening can be used to render surface defects harmless owing to the compressive residual stress effects. This study investigated the effects of shot peening as a means of remanufacturing gears. In this study, carburized steel specimens containing artificial defects were used to investigate the effects of shot peening on the fatigue strength; the defect size was rendered harmless by shot peening. Shot peening was conducted after inducing semicircular slits with depths of a = 0.15, 0.20, and 0.30 mm. Subsequently, plane bending fatigue tests were carried out. A maximum compressive residual stress of 1400 MPa was induced after shot peening. The fatigue limit of the smooth specimen increased by approximately 31% after shot peening. A semicircular slit of at least 0.20 mm deep could be rendered harmless by shot peening (SP). The defect size reduced by SP was evaluated on the basis of fracture mechanics. The estimated results are consistent with the experimental results. On the basis of the results, the feasibility of shot peening as a remanufacturing method for gears is discussed.
Characteristic Flow Behavior and Processing Map of a Novel Lean Si Spring Steel for Automotive Stabilizer Bars
Authors: Pan Hongbo , Li Shiwei , Ding Jing , Liu Weiming , Fu Yanan , Shen Xiaohui , Wei Hailian , Wang Huiting , Yu Liang , Fang Qiang
Published: December 2022

The spring steel for automotive stabilizer bars has a great responsibility in that its quality directly affects the stability, safety, and comfort of vehicle operation. The isothermal thermal compression behavior of a novel lean Si spring steel that was used to manufacture an anti-roll bar was investigated with a DIL805A/D quenching thermal dilatometer in this research. A hyperbolic sine type of constitutive model was established, and hot processing maps were produced to evaluate the experimental steel’s hot workability properties. The experimental results suggest that dynamic recrystallization (DRX) preferentially occurs at a low strain rate and high thermal processing temperature, while the processing maps of the experimental steel are susceptible to strain. The instability regions increase as the strain increases. The processing maps’ stable and instable domains should be decided upon comprehensive analysis of the instability criterion, power dissipation efficiency, and strain rate sensitivity index. The optimum parameters of hot processing for the experimental steel at various strains are that the deformation temperature of 1000–1150 °C and the strain rate of 0.1, approximately.
Parametric Studies of Effect of Cavitation Jet Modes on Wear Rate of Surface of Structural Materials
Authors: Mednikov Alexey , Zilova Olga , Tkhabisimov Aleksandr , Dasaev Marat , Grigoriev Sergey
Published: December 2022

In this study the kinetic curves of cavitation wear of cast steels 20 GL and 30 L used for production of critical elements of hydraulic machines were obtained. The typical predominance of growth rate of cavitation mark diameter over its depth was found on the surfaces of the investigated cast steels. The revealed phenomenon made it possible to offer a formula for estimating the volume removal of the examined cast steels in order to expand the scope of the method according to ASTM G134-17. This method uses profilometry and microscopy and allows to determine cavitation resistance both for homogeneous and heterogeneous materials, including materials after modification of their surface (with different types of coatings and hardenings).
Microstructure Evolution in a GOES Thin Strip
Authors: Volodarskaja Anastasia , Hradečný Kryštof , Palupčíková Renáta , Váňová Petra , Vodárek Vlastimil
Published: December 2022

This paper focuses on the evolution of the microstructure in a grain-oriented electrical steel (GOES) thin strip after casting. After solidification, the microstructure consisted of delta-ferrite. A small fraction of austenite was formed during the cooling of the thin strip in the two-phase region (gamma+delta). Fine Cr2CuS4 particles precipitated in the ferrite and along the delta/gamma interfaces. Laths of primary Widmanstätten austenite (WA) nucleated directly on the high-angle delta-ferrite grain boundaries. The formation of WA laths in both adjacent ferritic grains resulted in a zig-zag shape of delta-ferrite grain boundaries due to their local rotation during austenite nucleation. Based on the EBSD results, a mechanism of the formation of the zig-zag grain boundaries has been proposed. Besides the Widmanstätten morphology, austenite also formed as films along the delta-ferrite grain boundaries. Sulfide precipitation along the delta/gamma interfaces made it possible to prove that austenite decomposition upon a drop in temperature was initiated by the formation of epitaxial ferrite. Further cooling brought the decay of austenite to either pearlite or a mixture of plate martensite and some retained austenite.
Sulfur Removal and Iron Extraction from Natrojarosite Residue of Laterite Nickel Ore Processing by Reduction Roasting
Authors: Zulhan Zulfiadi , Adzana Zhahrina , Munawaroh Mona , Yusro Achmad Haerul , Christian Jonathan Dwiputra , Saputri Aura Dwi , Hidayat Taufiq
Published: December 2022

An alternative laterite nickel ore processing using sulfuric acid as a leaching agent to produce class 1 nickel as a raw material for electric vehicle batteries produces natrojarosite residue as a by-product during the precipitation of iron and aluminum step. The natrojarosite residue contained iron and high sulfur, which is challenging to utilize as an iron source for steel manufacturing since sulfur can contaminate the steel product. This study focuses on sulfur elimination and iron extraction from natrojarosite. The natrojarosite was roasted for sulfur removal isothermally at different temperatures ranging from 500 until 1100 °C for 4 h. Roasting at 1100 °C resulted a decrease in sulfur content from 12.18% to 3.81% and an increase in iron content from 16.23% to 28.54%. The sulfur released during roasting can, in principle, be recirculated to a sulfuric acid plant and reused as a leaching agent in the nickel ore processing plant. The unroasted and roasted natrojarosite residues were then reduced by coconut shell charcoal in the temperature range of 1000–1400 °C. The results showed that the metallic iron could be obtained from both unroasted and roasted natrojarosite residue at a temperature of 1200 °C and higher. The sulfur content in the oxide phase of unroasted natrojarosite residue was significantly higher than roasted natrojarosite residue. However, the roasting did not significantly influence the sulfur content in the metal phase. The sulfur content in the metal phase from unroasted and roasted natrojarosite residue was less than 1.2%. This result indicated that the removal of sulfur and metal oxide reduction in the natrojarosite residue could be carried out simultaneously in one stage where the natrojarosite residue is reduced by carbonaceous material at a temperature of 1200 °C or higher.
Effect of Solid Concentration and Particle Size on the Flotation Kinetics and Entrainment of Quartz and Hematite
Authors: Murhula Espoir , Hashan Mahamudul , Otsuki Akira
Published: December 2022

Despite the importance of solid concentration in froth flotation, its effect on flotation kinetics and entrainment has rarely been studied. In this study, the flotation kinetics and entrainment in quartz and hematite single-mineral flotation systems as a function of the solid concentration and particle size were investigated using dodecylamine acetate as a collector. Kinetics modeling showed that the Gamma distribution achieved the best agreement with the experimental data, whereas the Classical and Klimpel models poorly fit the data (e.g., RMSE). The flotation rate constants (k) of both quartz and hematite at a higher solid concentration showed a concave shape, with the inflexion point at the middle-size range, whereas this trend altered at lower solid concentrations. Overall, quartz exhibited higher equilibrium recoveries (R∞) than hematite, which indicates its better overall rate constants. The degree of water recovery in both the quartz and hematite systems was higher at higher solid concentrations, but the hematite system exhibited higher water R∞ than the quartz system, meaning that the entrainment of gangue could be higher in direct hematite flotation than the reverse one. Therefore, a higher solid concentration is associated with better overall quartz recovery and can reduce hematite loss by entrainment during reverse flotation. An inverse relationship was identified between the solid concentration and particle size in terms of the ratio of water recovery to the concentrate. In the reverse flotation of iron ore, refraining from achieving equilibrium recovery could help limit entrainment, but this was not necessarily the case in direct flotation. No entrainment model or method other than the Warren and Ross model approximated the overall trends of flotation at the finest size range (−38 µm). However, extending the Warren method to polynomial distribution led to an improved fit with the experimental results. In addition to the solid concentration, particle density and size were revealed to be key to developing new entrainment models. Finally, after the fast recovery period (true flotation) was over, the slow recoveries were mainly driven by the slow-floating water fraction.
Review on the Solid-State Welding of Steels: Diffusion Bonding and Friction Stir Welding Processes
Authors: Khedr Mahmoud , Hamada Atef , Järvenpää Antti , Elkatatny Sally , Abd-Elaziem Walaa
Published: December 2022

Solid-state welding (SSW) is a relatively new technique, and ongoing research is being performed to fulfill new design demands, deal with contemporary material advancements, and overcome welding defects associated with traditional welding techniques. This work provides an in-depth examination of the advancements in the solid-state welding of steels through diffusion bonding (DB) and friction stir welding (FSW). Considerable attention was given to DB of steel, which overcame the difficulties of segregation, cracking, and distortion stresses that are usually formed in liquid-phase welding techniques. The defects that affected DB included two types: two-dimensional defects of a metallic lattice, i.e., phases and grain boundaries, and three-dimensional defects, i.e., precipitation. FSW, on the other hand, was distinguishable by the use of relatively low heat input when compared to fusion welding processes such as tungsten inert gas (TIG), resulting in the formation of a limited heat-affected zone. Moreover, fine grain structures were formed in the FSW interface because of the stirring tool’s severe plastic deformation, which positively affected the strength, ductility, and toughness of the FSW joints. For instance, higher strength and ductility were reported in joints produced by FSW than in those produced by TIG. Nevertheless, the HAZ width of the specimens welded by FSW was approximately half the value of the HAZ width of the specimens welded by TIG. Some defects associated with FSW related to the diffusion of elements, such as C/Cr atoms, through the weld zone, which affected the local chemical composition due to the formation of rich/depleted regions of the diffused atoms. Moreover, the lack-of-fill defect may exist when inappropriate welding conditions are implemented. On the other hand, the stirring tool was subjected to extensive wear because of the high hardness values, which negatively affected the economical usage of the FSW process. A summary of the results is presented, along with recommendations for future studies aimed at addressing existing difficulties and advancing the solid-state technology for steel.
Influence of the Glassy Fraction Surface of a ZrCoAlAg Ribbon Alloy on the Bioactive Response to Simulated Body Fluid and Its Effect on Cell Viability
Authors: Escamilla Aish , Verduzco Jorge , Núñez Rosa , Figueroa Ignacio , García René
Published: December 2022

To purpose of this work is to determine the biocompatibility of the Zr58Co21Al9Ag12 alloy; vitreous ribbons of the Zr58Co21Al9Ag12 alloy were obtained by a chill block melt spinner. They were characterized by X-ray diffraction and transmission electron microscopy. Chemical homogeneity was examined by scanning electron microscopy. Similarly, thermal analysis was performed using differential scanning calorimetry. The nanoindentation test was performed with a Berkovich nanoindenter. Subsequently, the bioactivity was evaluated by chemical immersion in simulated body fluid. After immersion, it was characterized by XRD. A cell adhesion test was performed using mesenchymal stem cells from human dental pulp. Cell viability and proliferation were evaluated with a CCK-8 assay using human lymphocytes. The ribbons have crystalline phases close to 20%. The thermal parameters, Young’s modulus, and hardness were obtained. After the immersion test, Ca and P were identified. Ion release does not exceed critical levels for human cells. The alloy has a higher concentration of adhered cells compared to Ti6Al4V. The alloy remains bio-inert with respect to apatite formation; however, it exhibits excellent cell viability, proliferation, and adhesion behavior.
Microstructure Change, Nano-Hardness and Surface Modification of CN-G01 Beryllium Induced by Helium Ions
Authors: Cui Minghuan , Jin Peng , Shen Tielong , Zhu Yabin , Pang Lilong , Wang Zhiguang , Luo Xiaofang , Feng Yongjin , Gong Baoping
Published: December 2022

The helium effects in Chinese developed CN-G01 beryllium are important issues for its use in nuclear energy systems. In this work, the CN-G01 beryllium samples were irradiated with helium ions to fluences of 5.0 × 1016 ions/cm2 to 1.0 × 1018 ions/cm2 at room temperature and investigated by techniques of scanning electron microscopy (SEM), transmission electron microscopy (TEM) and nano-indentation. It was found that the irradiation induced hardening of beryllium and the nano-hardness of the samples increased with increasing fluence of 5.0 × 1016 ions/cm2 to 1.0 × 1017 ions/cm2. When the fluence reached 5.0 × 1017 ions/cm2 and 1.0 × 1018 ions/cm2, helium irradiation induced serious surface blistering and its burst. TEM observation found that helium bubbles in the damage peak region became visible when the fluence reached 1.0 × 1017 ions/cm2. With increasing fluence, helium bubbles became larger and connected into large cracks. The underlying physical mechanisms are discussed based on the helium behavior at low temperatures and the contributions of helium induced defects. This work will provide some new understanding on the irradiation resistance of CN-G01 beryllium and the helium effects in beryllium at low temperatures.