bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Calcination Temperature on the Physicochemical Properties and Electrochemical Performance of FeVO4 as an Anode for Lithium-Ion Batteries
Authors: Ghani Faizan , An Kunsik , Lee Dongjin
Published: January 2023

Several electrode materials have been developed to provide high energy density and a long calendar life at a low cost for lithium-ion batteries (LIBs). Iron (III) vanadate (FeVO4), a semiconductor material that follows insertion/extraction chemistry with a redox reaction and provides high theoretical capacity, is an auspicious choice of anode material for LIBs. The correlation is investigated between calcination temperatures, morphology, particle size, physicochemical properties, and their effect on the electrochemical performance of FeVO4 under different binders. The crystallite size, particle size, and tap density increase while the specific surface area (SBET) decreases upon increasing the calcination temperature (500 °C, 600 °C, and 700 °C). The specific capacities are reduced by increasing the calcination temperature and particle size. Furthermore, FeVO4 fabricated with different binders (35 wt.% PAA and 5 wt.% PVDF) and their electrochemical performance for LIBs was explored regarding the effectiveness of the PAA binder. FV500 (PAA and PVDF) initially delivered higher discharge/charge capacities of 1046.23/771.692 mAhg−1 and 1051.21/661.849 mAhg−1 compared to FV600 and FV700 at the current densities of 100 mAg−1, respectively. The intrinsic defects and presence of oxygen vacancy along with high surface area and smaller particle sizes efficiently enhanced the ionic and electronic conductivities and delivered high discharge/charge capacities for FeVO4 as an anode for LIBs.
Inter-Critically Reheated CGHAZ of Ultra-High-Strength Martensitic Steel with Different Cooling Rates
Authors: Liu Wen-Jian , Li Hong-Ying , Zhou Wen-Hao , Luo Deng , Liu Dan , Liang Liang , Xiao Ai-Da
Published: January 2023

The mechanical properties of steel’s inter-critically reheated coarse-grained heat-affected zone (ICR CGHAZ) directly affects the service life of machinery equipment. The hardness and toughness of ICR CGHAZ can be optimized simultaneously through tailoring microstructure where cooling rate plays a key role. In this work, the samples with different cooling rates was prepared using thermal simulation. The granite bainite (GB), bainite ferrite (BF) and MA were formed at a 1 °C/s (CR1) cooling rate, while BF and MA were formed at 10 °C/s (CR2) and 30 °C/s (CR3) cooling rates. With the increase of cooling rate, the effective grain size decreased and the number of hard phases increased, resulting in monotonic increase of hardness (260HV3, 298HV3 and 323HV3). CR1 had sparsely distributed coarse slender MA and CR3 possessed tail-head connected MA along PAGBs, which was detrimental to toughness. Therefore, CR2 possessed the best toughness(25J). The microstructural evolution mechanism of ICR CGHAZ with different cooling rates is investigated, corresponding hardening and toughening mechanisms are discussed.
Crack Width Evaluation of Cracked Mortar Specimen Using Gas Diffusion Characteristics
Authors: Lee Do-Keun , Shin Kyung-Joon , Lee Kwang-Myong
Published: January 2023

Several methods have been proposed currently for evaluating the crack width of a mortar specimen. Among these, the water permeability test is widely used to estimate crack width because water permeability is directly related to the average crack width of a specimen through which water passes. However, the viscosity of water makes precise crack width measurement challenging. The possible inflow (outflow) of foreign (healing) substances could affect the test results. To circumvent this limitation, this study proposes a gas diffusion test using oxygen rather than water as the medium. The proposed method includes a process that could compensate for gas diffusion from specimen parts other than the crack, allowing for a more precise estimation of crack width. The crack width can indeed be estimated with an error of 4% or less.
Superfunctional Materials by Ultra-Severe Plastic Deformation
Authors: Edalati Kaveh
Published: January 2023

Superfunctional materials are defined as materials with specific properties being superior to the functions of engineering materials. Numerous studies introduced severe plastic deformation (SPD) as an effective process to improve the functional and mechanical properties of various metallic and non-metallic materials. Moreover, the concept of ultra-SPD—introducing shear strains over 1000 to reduce the thickness of sheared phases to levels comparable to atomic distances—was recently utilized to synthesize novel superfunctional materials. In this article, the application of ultra-SPD for controlling atomic diffusion and phase transformation and synthesizing new materials with superfunctional properties is discussed. The main properties achieved by ultra-SPD include: (i) high-temperature thermal stability in new immiscible age-hardenable aluminum alloys; (ii) room-temperature superplasticity for the first time in magnesium and aluminum alloys; (iii) high strength and high plasticity in nanograined intermetallics; (iv) low elastic modulus and high hardness in biocompatible binary and high-entropy alloys; (v) superconductivity and high strength in the Nb-Ti alloys; (vi) room-temperature hydrogen storage for the first time in magnesium alloys; and (vii) superior photocatalytic hydrogen production, oxygen production, and carbon dioxide conversion on high-entropy oxides and oxynitrides as a new family of photocatalysts.
Fracture Closure Empirical Model and Theoretical Damage Model of Rock under Compression
Authors: Chen Yifan , Lin Hang , Xie Shijie , Cao Rihong , Sun Shuwei , Zha Wenhua , Wang Yixian , Zhao Yanlin , Hu Huihua
Published: January 2023

The rock or rock mass in engineering often contains joints, fractures, voids, and other defects, which are the root cause of local or overall failure. In response to most of the current constitutive models that fail to simulate the nonlinear fracture compaction deformation in the whole process of rock failure, especially brittle rocks, a piecewise constitutive model was proposed to represent the global constitutive relation of rocks in this study, which was composed of the fracture compaction empirical model and the damage statistical constitutive model. The fracture empirical compaction model was determined by fitting the expressions of fracture closure curves of various rocks, while the rock damage evolution equation was derived underpinned by the fracture growth. According to the effective stress concept and strain equivalence hypothesis, the rock damage constitutive model was deduced. The model parameters of the fracture compaction empirical model and damage statistical constitutive model were all calculated by the geometrical characteristics of the global axial stress–strain curve to guarantee that the models are continuous and smooth at the curve intersection, which is also simple and ready to program. Finally, the uniaxial compression test data and the triaxial compression test data of different rocks in previous studies were employed to validate the models, and the determination coefficient was used to measure the accuracy. The results showed great consistency between the model curves and test data, especially in the pre-peak stage.
Optimization Design of Asphalt Mixture Composite Reinforced with Calcium Sulfate Anhydrous Whisker and Polyester Fiber Based on Response Surface Methodology
Authors: Fan Taotao , Si Chundi , Zhang Yi , Zhu Yuefeng , Li Song
Published: January 2023

In order to improve the properties of calcium sulfate anhydrous whisker (ACSW) and polyester fiber composite reinforced asphalt mixture (ACPRA) to meet the service requirements of pavement materials in low-temperature environments, the central composite circumscribed design (CCC), a kind of response surface methodology, was chosen to optimize the design parameters. Three independence variables, asphalt aggregate ratio, ACSW content, and polyester fiber content were adopted to evaluate the design parameters. Four responsive variables, air voids, Marshall stability, splitting tensile strength, and failure tensile strain, were chosen to study the volumetric and mechanical characteristics, and the low-temperature behavior of ACPRA by the Marshall test and indirect tensile test at −10 °C. The results showed that, taking low-temperature behavior optimization as the objective, the CCC method was practicable to optimize design of ACPRA, and the optimization design parameters were asphalt aggregate ratio of 4.0%, ACSW content of 10.8%, and polyester fiber content of 0.4%. Furthermore, the impact of three independence variables interactions on four response variables was also discussed, and it was identified that the interaction between asphalt aggregate ratio and ACSW content, and between asphalt aggregate ratio and polyester fiber content, has greater bearing on the splitting tensile strength and failure tensile strain of APCRA. Meanwhile, ACSW and polyester fiber enhancing the low-temperature behavior of APCRA was primarily connected with their contents.
Nanocomposite Electrode of Titanium Dioxide Nanoribbons and Multiwalled Carbon Nanotubes for Energy Storage
Authors: BinSabt Mohammad , Shaban Mohamed , Gamal Ahmed
Published: January 2023

TiO2 is one of the most investigated materials due to its abundance, lack of toxicity, high faradaic capacitance, and high chemical and physical stability; however, its potential use in energy storage devices is constrained by its high internal resistance and weak van der Waals interaction between the particles. Carbon nanotubes are especially well suited for solving these issues due to their strong mechanical strength, superior electrical conductivity, high electron mobilities, excellent chemical and thermal stability, and enormous specific nanoporous surface. The hydrothermal approach was followed by chemical vapor deposition to produce a network composite of titanium dioxide nanoribbons (TNRs) and multi-walled carbon nanotubes (MWCNTs). The nanocomposite was characterized using a variety of methods. One phase of TiO2-B nanoribbons has porous pits on its surface, and MWCNTs are grown in these pits to produce a network-like structure in the nanocomposite. With a two-electrode supercapacitor configuration, the TNR/CNT gave a gravimetric capacitance of 33.33 F g−1, which was enhanced to 68.18 F g−1 in a redox-active electrolyte containing hydroquinone (HQ). Additionally, the areal capacitance per footprint was increased from 80 mF cm−2 in H2SO4 to 163.63 mF cm−2 in H2SO4/HQ. The TNR/CNT supercapacitor has superior cyclic stability than the previously reported TiO2-based electrodes, with 97.5% capacitance retention after 5000 cycles. Based on these results, it looks like the TNR/CNT supercapacitor could provide portable electronic power supplies with new ways to work in the future.
Compression Strength Estimation of Corrugated Board Boxes for a Reduction in Sidewall Surface Cutouts—Experimental and Numerical Approaches
Authors: Fehér Lajos , Pidl Renáta , Böröcz Péter
Published: January 2023

Corrugated cardboard boxes are generally used in modern supply chains for the handling, storage, and distribution of numerous goods. These packages require suitable strength to maintain adequate protection within the package; however, the presence and configuration of any cutouts on the sidewalls significantly influence the packaging costs and secondary paperboard waste. This study aims to evaluate the performance of CCBs by considering the influence of different cutout configurations of sidewalls. The compression strength of various B-flute CCB dimensions (200 mm, 300 mm, 400 mm, 500 m, and 600 mm in length, with the same width and height of 300 mm), each for five cutout areas (0%, 4%, 16%, 36%, and 64%) were experimentally observed, and the results were compared with the McKee formula for estimation. The boxes with cutout areas of 0%, 4%, 16%, 36%, and 64% showed a linear decreasing tendency in compression force. A linear relationship was found between compression strength and an increase in cutout sizes. Packages with 0% and 4% cutouts did not show significant differences in compression strength (p < 0.05). Furthermore, this study shows a possible way to modify the McKee estimation for such boxes after obtaining empirical test data since the McKee formula works with a relatively high error rate on corrugated cardboard boxes with sidewall cutouts. Utilizing the numerical and experimental results, a favorable estimation map can be drawn up for packaging engineers to better manage material use and waste. The results of the study showed that the McKee formula does not appropriately estimate the box compression strength for various cutout sizes in itself.
Stress–Dilatancy Behaviourof Fibre-Reinforced Sand
Authors: Szypcio Zenon , Dołżyk-Szypcio Katarzyna , Chmielewska Iwona
Published: January 2023

This paper analyses the stress–strain behaviour of fibre-reinforced sand using the results obtained by drained triaxial compression tests presented in the literature. The general stress–plastic dilatancy equation of the Frictional State Concept has been used to describe the behaviour of fibre-reinforced sand for different shear phases. The behaviour of pure sand is taken as a reference for the behaviour of sand with added fibres. It is shown that the characteristic shear phases can only be determined when the η−Dp relationships are used, which are very rarely demonstrated in the results of shear tests presented in the literature. It has been shown that tensile strains must occur in order to achieve the strengthening effect of fibre reinforcement. A reduction in the stiffness of the fibre–sand composite is observed in the absence of tensile strains below certain threshold values.
Mixed Electronic-Ionic Conductivity and Stability of Spark Plasma Sintered Graphene-Augmented Alumina Nanofibres Doped Yttria Stabilized Zirconia GAlN/YSZ Composites
Authors: Kurapova Olga , Glumov Oleg , Smirnov Ivan , Konakov Yaroslav , Konakov Vladimir
Published: January 2023

Graphene-doped ceramic composites with mixed electronic-ionic conductivity are currently attracting attention for their application in electrochemical devices, in particular membranes for solid electrolyte fuel cells with no necessity to use the current collector. In this work, composites of the Y2O3-ZrO2 matrix with graphene-augmented γ-Al2O3 nanofibres (GAlN) were spark plasma sintered. The conductivity and electrical stability in cyclic experiments were tested using electrical impedance spectroscopy. Composites with 0.5 and 1 wt.% GAlN show high ionic conductivity of 10−2–10−3 S/cm at 773 K. Around 3 wt.% GAlN percolation threshold was achieved and a gradual increase of electronic conductivity from ~10−2 to 4 × 10−2 S/cm with an activation energy of 0.2 eV was observed from 298 to 773 K while ionic conductivity was maintained at elevated temperatures. The investigation of the evolution of conductivity was performed at 298–973 K. Besides, the composites with 1–3 wt.% of GAlN addition show a remarkable hardness of 14.9–15.8 GPa due to ZrC formation on the surfaces of the materials.
Waste Polyurethane Foams as Biomass Carriers in the Treatment Process of Domestic Sewage with Increased Ammonium Nitrogen Content
Authors: Dacewicz Ewa , Lenart-Boroń Anna
Published: January 2023

In order to understand the mechanisms of microbial growth on waste polyurethane sponge materials, their effectiveness as biomass carriers in domestic sewage with increased ammonium nitrogen content treatment was assessed. Comparative experiments were carried out in microreactors under steady conditions of batch culture, which allowed for an assessment of different carriers, in the form of flexible foams, rigid foams, and flexible foams placed in full casings. In the studies conducted in continuous cultures, biomass carriers selected in batch culture were used as fillings in the column model. The structure of the microbial community inhabiting the spongy material was determined and the pollutant-removing process from real domestic sewage was assessed. Analyzes using the Illumina sequencing technique allowed for demonstrating that Nitrosomonas and Nitrospira were the predominant nitrifiers in the biomass carrier in the form of waste polyurethane foams (PUF). It was found that anammox bacteria, the presence of which—as unidentified Planctomycetes—was confirmed in the polyurethane sponge material, were also responsible for the high removal of N-NH4+. Burkholderia and Sphingopyxis phyla were identified as the dominant denitrifying bacteria involved in the treatment of domestic sewage with increased content of ammonium nitrogen. The biomass carrier in the form of waste PUF placed additionally in full casings proved to be more beneficial for the proliferation of bacteria involved in nitrification and denitrification processes. On the other hand, waste foams without casings proved to be more suitable for the growth of microorganisms known to perform partial denitrification and may accumulate nitrites (Staphylococcus, Dokdonella). Additionally, the presence of Devosia and Pseudonocardia, which participated in the phosphorus removal process, was found in the waste PUR foams.
Natural Deep Eutectic Solvents in the Synthesis of Inorganic Nanoparticles
Authors: Długosz Olga
Published: January 2023

Natural deep eutectic solvents (NDESs), as a new type of green solvent, are used in many fields, including industry in extraction processes, medicine, pharmaceuticals, metallurgy, electrodeposition, separations, gas capture, biocatalysis and nanotechnology. Mainly due to their properties, such as simple preparation, environmental friendliness, biocompatibility and multifunctionality, they are being used in various fields of industry. This review aims to provide insight into the applications of natural deep eutectic solvents, specifically in nanotechnology processes. It focuses on the description of NDES and how their physicochemical properties are used to obtain functional nanomaterials, including metals, metal oxides and salts. It highlights how the use of NDESs to obtain a wide range of inorganic nanoparticles enables the elimination of disadvantages of traditional methods of obtaining them, including reducing energy consumption and functionalising nanoparticles in situ. In conclusion, recent advances and future directions in the development and applications of NDESs in nanotechnology are discussed with the aim of identifying unexplained scientific questions that can be investigated in the future.
Electrochemical, Biological, and Technological Properties of Anodized Titanium for Color Coded Implants
Authors: Hlinka Josef , Dostalova Kamila , Cabanova Kristina , Madeja Roman , Frydrysek Karel , Koutecky Jan , Rybkova Zuzana , Malachova Katerina , Umezawa Osamu
Published: January 2023

Anodization coloring of titanium tools or implants is one of the common methods for the differentiation of each application by its size or type. Commercial purity titanium grade 4 plates (50 × 20 × 0.1 mm) were tested to obtain their electrochemical and other technological properties. The coloring process was done using the potential of 15, 30, 45, 60, and 75 Volts for 5 s in 1 wt. % citric acid in demineralized water solution. Organic acids solutions generally produce better surface quality compared to inorganic acids. The contact angle of colored surfaces was measured by the sessile drop method. Electrochemical impedance spectroscopy and potentiodynamic polarization were used for the determination of selected electrochemical and corrosion parameters of the tested surfaces. It was found that the anodization process decreases corrosion potential significantly. It was also confirmed that a higher potential used for anodization results in higher polarization resistance but also a decrease in corrosion potential. The anodization process at 75 V produces surfaces with the lowest corrosion rate under 1 nm/year and the noblest corrosion potential. It was confirmed that the anodization process in citric acid does not affect titanium cytotoxicity.
Comparison of Standardized Methods for Determining the Diffusion Coefficient of Chloride in Concrete with Thermodynamic Model of Migration
Authors: Szweda Zofia , Gołaszewski Jacek , Ghosh Pratanu , Lehner Petr , Konečný Petr
Published: January 2023

This research paper is the result of observations made during tests according to various standards carried out on behalf of industry. The article presents diffusion coefficient values calculated according to the thermodynamic migration model for twenty different concrete mixes and some selected mixes of the codified approaches known as ASTM 1202, NT BUILD 443, NT BUILD 492, ASTM 1556. The method used here, according to the thermodynamic model of migration, allows determination of the value of the diffusion coefficient after short studies of the migration of chloride ions into concrete and was described in earlier works by one of the authors. Unfortunately, when using standard methods, the values of diffusion coefficients differ significantly from each other. In each concrete, diffusion tests were carried out in the conditions of long-term natural diffusion to verify the values determined by standard methods and according to the thermodynamic model of migration. The analysis conducted for this research paper reveals that the chloride permeability test method according to the standard ASTM C1202-97 has an almost 2.8-fold greater dispersion of the obtained results compared to the thermodynamic model of migration. It was observed that the standard NT BUILD 492 has a 3.8-fold dispersion of results compared to the method with the thermodynamic model of migration. The most time-consuming method is the standard method NT BUILD 443. The largest 3.5-fold dispersion of values concerning the reference value are observed in that method. Moreover, a method based on a thermodynamic migration model seems to be the best option of all analyzed methods. It is a quite quick, but laborious, method that should be tested for a larger number of concrete mixes. A great advantage of this method is that it is promising for a wide range of concrete mixtures, both plain concrete and concrete with various additives and admixtures, as well as high-performance concrete.
On Constraints and Parasitic Motions of a Tripod Parallel Continuum Manipulator
Authors: Altuzarra Oscar , Tagliavini Luigi , Lei Yuhang , Petuya Victor , Ruiz-Erezuma Jose Luis
Published: January 2023

A parallel continuum manipulator (PCM) is a mechanism of closed-loop morphology with flexible elements such that their deformation contributes to its mobility. Flexible hexapods are six-degrees-of-freedom (DoF) fully parallel continuum mechanisms already presented in the literature. Devices of reduced mobility, i.e., lower mobility than six DoF, have not been studied so far. An essential characteristic of lower mobility mechanisms is that reduced mobility is due to kinematic constraints generated by mechanical arrangements and passive joints. In rigid-link parallel manipulators, those constraints are expressed as a set of equations relating to the parameters representing the end effector’s pose. As a consequence, independent output pose variables are controllable with the position equations, while dependent output variables undergo parasitic motions. In this paper, the performance of a tripod-type parallel continuum manipulator, 3PF̲S, is compared with the operation of its rigid counterpart 3P̲RS. We will show that in PCMs there are no such geometric constraints expressible with algebraic equations, but it is difficult to perform some types of motion in the end effector with the input torques. Another goal of this paper is to evaluate such limitation of motion in a tripod-like PCM and compare it with the constraints of the rigid 3P̲RS. Finally, the paper shows that there are strong similarities in the reduced mobility of both mechanisms.
Effects of the Magnetic Model of Interior Permanent Magnet Machine on MTPA, Flux Weakening and MTPV Evaluation
Authors: Bianchini Claudio , Bisceglie Giorgio , Torreggiani Ambra , Davoli Matteo , Macrelli Elena , Bellini Alberto , Frigieri Matteo
Published: January 2023

Interior permanent-magnet synchronous machines are widely spreading in automotive and vehicle traction applications, because of their high efficiency over a wide speed range. This capability can be achieved by appropriated control strategies: Maximum Torque per Ampere (MTPA), Flux Weakening (FW) and Maximum Torque per Volt (MTPV). However, these control trajectories are often based on an simplified magnetic model of the electrical machine. In order to improve the evaluation of machine output capabilities, nonlinear magnetic behavior must be modeled. This is not only related to the final application with a given drive and control structure, but also during the design process of the electric machine. In the design process, the output torque Vs. speed characteristic must be calculated following MTPA, MTPV and FW in the most accurate way to avoid significant error. This paper proposes a set of algorithms to compute MTPA, FW and MTPV curves for interior permanent-magnet synchronous machines taking into account the machines’ nonlinearities caused by iron saturation and compares differed approaches to highlight the torque–speed capabilities for the same machine following different methods. The algorithms are based on the maps of the equivalent inductances of a reference interior permanent-magnet synchronous machine and inductances maps were obtained via 2-D Finite Element Analysis over the machine’s operating points in id−iq reference plane. The effects of different 2-D finite element methods are also computed by both standard nonlinear magnetostatic simulations and Frozen Permeability simulations. Results show that the nonlinear model computed via frozen permeability is more accurate than the conventional linear and nonlinear models computed via standard magnetostatic simulations; for this reason, during the electrical machine design, it is important to check the expected performance employing a complete inductance map and frozen permeability.
Optimization Design of Aspect Ratio and Solidity of a Heavy-Duty Gas Turbine Transonic Compressor Rotor
Authors: Liu Shuaipeng , Geng Shaojuan , Li Xinlong , Jin Yun , Zhang Hongwu
Published: January 2023

To investigate the influence of blade aspect ratio and solidity on the performance of heavy-duty gas turbine transonic compressors, a multi-objective optimization design platform was built by adopting the blade parameterization method based on the superposition of thickness distribution on the suction surface, the Kriging surrogate model, and the NSGA-II optimization method. The spanwise distribution of solidity and number of blades were the optimization variables. The multi-objective optimization was carried out with isentropic efficiency and stall margin as the objective parameters for the inlet stage transonic rotor of an F-class heavy-duty gas turbine compressor. The results show that the isentropic efficiency and stall margin at design condition with a constant mass flow rate can be improved by 0.96% and 18.7%, respectively, and the total pressure ratio can also increase. The analysis shows that, for regions where the shock wave–boundary layer interaction is obvious, increasing the solidity can reduce the shock wave loss, the shock wave–boundary layer interaction loss, and the end wall loss, and reducing the aspect ratio can reduce the blade boundary layer loss. The spanwise distributions of solidity and aspect ratio determine the stall margin by affecting the radial matching of the load of each blade section. Tip solidity near the tip region needs to be determined according to the pressure field established by the bulk of the flow.
Relativistic Effects from Heavy Main Group p-Elements on the NMR Chemical Shifts of Light Atoms: From Pioneering Studies to Recent Advances
Authors: Rusakova Irina L. , Rusakov Yuriy Yu.
Published: January 2023

This review represents a compendium of computational studies of relativistic effects on the NMR chemical shifts of light nuclei caused by the presence of heavy main group p-block elements in molecules. The narration starts from a brief discussion of the relativistic theories and quantum chemical methods for the calculation of NMR chemical shifts at the relativistic level of the electronic theory. The main part of the review contains a survey on the relativistic calculations of NMR shielding constants of the most popular NMR-active light nuclei such as 1H, 13C, 19F, 29Si, 15N, and 31P of compounds containing heavy p-elements. A special focus is placed on the relativistic effects initiated by the 16th and 17th group elements. Different factors governing the behavior of the relativistic effects on the chemical shifts of light atoms are discussed. In particular, the stereochemistry of the relativistic “heavy atom on the light atom” effect and the influence of the spin–orbit relativistic effects on the vibrational contributions to the shielding constants of light nuclei are considered.
On the General Sum Distance Spectra of Digraphs
Authors: Xi Weige , Cai Lixiang , Shang Wutao , Su Yidan
Published: January 2023

Let G be a strongly connected digraph, and dG(vi,vj) denote the distance from the vertex vi to vertex vj and be defined as the length of the shortest directed path from vi to vj in G. The sum distance between vertices vi and vj in G is defined as sdG(vi,vj)=dG(vi,vj)+dG(vj,vi). The sum distance matrix of G is the n×n matrix SD(G)=(sdG(vi,vj))vi,vj∈V(G). For vertex vi∈V(G), the sum transmission of vi in G, denoted by STG(vi) or STi, is the row sum of the sum distance matrix SD(G) corresponding to vertex vi. Let ST(G)=diag(ST1,ST2,…,STn) be the diagonal matrix with the vertex sum transmissions of G in the diagonal and zeroes elsewhere. For any real number 0≤α≤1, the general sum distance matrix of G is defined as SDα(G)=αST(G)+(1−α)SD(G). The eigenvalues of SDα(G) are called the general sum distance eigenvalues of G, the spectral radius of SDα(G), i.e., the largest eigenvalue of SDα(G), is called the general sum distance spectral radius of G, denoted by μα(G). In this paper, we first give some spectral properties of SDα(G). We also characterize the digraph minimizes the general sum distance spectral radius among all strongly connected r-partite digraphs. Moreover, for digraphs that are not sum transmission regular, we give a lower bound on the difference between the maximum vertex sum transmission and the general sum distance spectral radius.
The Optimization of Working Time for a Consecutively Connected Production Line
Authors: Lei Bingyin , Ren Yue , Wang Ziyang , Ge Xinquan , Li Xiaolin , Gao Kaiye
Published: January 2023

Most factory production processes are completed by machines and workers on production lines. The operation schedule is arranged to reduce the cost of the enterprises to obtain the maximum economic profit for sustainable running. Previous studies usually investigated the working time while only considering the workers’ conditions. This study proposed a method to optimize the operation schedule by jointly considering the workers’ fatigue states and the operation states of machines. This method was proposed based on a system structure called the multistate consecutively connected system (MCCS), which has been widely applied in many areas, such as electronic communications. This structure is also an analogy of the production line. The corresponding model is constructed based on the universal generating function (UGF) since it is a powerful tool in modeling a consecutively connected system. The proposed model can be used to evaluate the different productivities of different types of workers in different states and to realize the screening of the whole scheme through simulation. According to the proposed method, we obtained the optimal operation schedule, including the working time, rest time and allocation strategy for a production line system. Some examples are provided to illustrate the proposed method.
The Vehicle Routing Problem with Simultaneous Pickup and Delivery Considering the Total Number of Collected Goods
Authors: Guo Qinge , Wang Nengmin
Published: January 2023

As a consequence of e-commerce development, large quantities of returned goods are shipped every day. The vehicle routing problem with simultaneous delivery and pickup (VRPSDP) has become one of the most important areas of logistics management. Most related studies are aimed at minimizing travel time. However, the total number of collected goods is also very important to logistics companies. Thus, only considering the traveling time cannot reflect actual practice. To effectively optimize these operations for logistics companies, this paper introduces the vehicle routing problem with simultaneous pickup and delivery considering the total number of collected goods. Based on the principles of considering the number of collected goods, a bi-objective vehicle routing model minimizing the total travel time and maximizing the total number of collected goods simultaneously is developed. A polynomial time approximation algorithm based on the ε-constraint method is designed to address this problem, and the approximation ratio of the algorithm is analyzed. Finally, the validity and feasibility of the proposed model and algorithm are verified by test examples, and several managerial insights are derived from the sensitivity analysis.
A Study on Fuzzy Resolving Domination Sets and Their Application in Network Theory
Authors: Vasuki Manimozhi , Shanmugapriya Ramachandramoorthi , Mahdal Miroslav , Cep Robert
Published: January 2023

Consider a simple connected fuzzy graph (FG) G and consider an ordered fuzzy subset H = {(u1, σ(u1)), (u2, σ(u2)), …(uk, σ(uk))}, |H| ≥ 2 of a fuzzy graph; then, the representation of σ − H is an ordered k-tuple with regard to H of G. If any two elements of σ − H do not have any distinct representation with regard to H, then this subset is called a fuzzy resolving set (FRS) and the smallest cardinality of this set is known as a fuzzy resolving number (FRN) and it is denoted by Fr(G). Similarly, consider a subset S such that for any u∈S, ∃v∈V − S, then S is called a fuzzy dominating set only if u is a strong arc. Now, again consider a subset F which is both a resolving and dominating set, then it is called a fuzzy resolving domination set (FRDS) and the smallest cardinality of this set is known as the fuzzy resolving domination number (FRDN) and it is denoted by Fγr(G). We have defined a few basic properties and theorems based on this FRDN and also developed an application for social network connection. Moreover, a few related statements and illustrations are discussed in order to strengthen the concept.
Discrete Model for a Multi-Objective Maintenance Optimization Problem of Safety Systems
Authors: Briš Radim , Tran Nuong Thi Thuy
Published: January 2023

The aim of this article was to solve a multi-objective maintenance optimization problem by minimizing both unavailability and cost through the use of an optimal maintenance strategy. The problem took into account three different system designs upon which the objective functions are dependent, and the time to start preventive maintenance (PM) was used as a decision variable. This variable was optimized for all system components using a discrete maintenance model that allows for the specification of several discrete values of the decision variable in advance to find the optimal one. The optimization problem was solved using innovative computing methodology and newly updated software in MATLAB, which was used to quantify the unavailability of a complex system represented through a directed acyclic graph. A cost model was also developed to compute the cost of different maintenance configurations, and the optimal configuration was found. The results for a selected real system (a real fluid injection system adopted from references) showed that unavailability was less sensitive to variations in maintenance configurations, while cost variations were more noticeable in relation to different maintenance configurations. Applying PM, the increasing value of the decision variable increased cost because it led to more frequent corrective maintenance (CM) actions, and recovery times due to CM were more expensive than recovery times due to PM.
Computational Analysis on Magnetized and Non-Magnetized Boundary Layer Flow of Casson Fluid Past a Cylindrical Surface by Using Artificial Neural Networking
Authors: Rehman Khalil Ur , Shatanawi Wasfi , Çolak Andaç Batur
Published: January 2023

In this article, we constructed an artificial neural networking model for the stagnation point flow of Casson fluid towards an inclined stretching cylindrical surface. The Levenberg–Marquardt training technique is used in multilayer perceptron network models. Tan–Sig and purelin transfer functions are carried in the layers. For better novelty, heat and mass transfer aspects are taken into account. The viscous dissipation, thermal radiations, variable thermal conductivity, and heat generation effects are considered by way of an energy equation while the chemical reaction effect is calculated by use of the concentration equation. The flow is mathematically modelled for magnetic and non-magnetic flow fields. The flow equations are solved by the shooting method and the outcomes are concluded by means of line graphs and tables. The skin friction coefficient is evaluated at the cylindrical surface for two different flow regimes and the corresponding artificial neural networking estimations are presented. The coefficient of determination values’ proximity to one and the low mean squared error values demonstrate that each artificial neural networking model predicts the skin friction coefficient with high accuracy.
Adaptive Differential Privacy Mechanism Based on Entropy Theory for Preserving Deep Neural Networks
Authors: Zhang Xiangfei , Yang Feng , Guo Yu , Yu Hang , Wang Zhengxia , Zhang Qingchen
Published: January 2023

Recently, deep neural networks (DNNs) have achieved exciting things in many fields. However, the DNN models have been proven to divulge privacy, so it is imperative to protect the private information of the models. Differential privacy is a promising method to provide privacy protection for DNNs. However, existing DNN models based on differential privacy protection usually inject the same level of noise into parameters, which may lead to a balance between model performance and privacy protection. In this paper, we propose an adaptive differential privacy scheme based on entropy theory for training DNNs, with the aim of giving consideration to the model performance and protecting the private information in the training data. The proposed scheme perturbs the gradients according to the information gain of neurons during training, that is, in the process of back propagation, less noise is added to neurons with larger information gain, and vice-versa. Rigorous experiments conducted on two real datasets demonstrate that the proposed scheme is highly effective and outperforms existing solutions.
The Extended David-Yechiali Rule for Kidney Allocation
Authors: Elalouf Amir , Rosenfeld Ariel , Rockach Ofir
Published: January 2023

The First Come First Served (FCFS) queuing policy is routinely assumed to be the benchmark policy for “fairness” in waiting-time performance. In this article, we propose a slight modification of the FCFS policy based on a natural extension of the well-established David and Yechiali (DY) rule and analyze it in the context of managing a waiting list for kidney transplants. In the proposed policy, the queuing agents are sequentially offered a stochastically arriving organ on a “first come, first served” basis while applying the individually optimal DY stopping rule. Through a realistic simulation, we show that the proposed policy, which we term Extended David and Yechiali (EDY), favorably compares to the FCFS policy in terms of medical efficiency while maintaining a comparable level of equity (i.e., fairness). Possible implications and practical aspects of the EDY are discussed.
Extended de Montmort-Prudnikov Sum
Authors: Reynolds Robert , Stauffer Allan
Published: January 2023

Using a contour integral method, the de Montmort-Prudnikov sum is extended to derive a new series representation involving the incomplete gamma function. The series is uniformly convergent and completely analytical, which can be evaluated for general complex ranges of the parameters involved. Applications and evaluations of this formula are discussed.
Generalised Additive Modelling of Auto Insurance Data with Territory Design: A Rate Regulation Perspective
Authors: Xie Shengkun , Shi Kun
Published: January 2023

Pricing using a Generalised Linear Model is the gold standard in the auto insurance industry and rate regulation. Generalised Additive Model applications in insurance pricing are receiving increasing attention from academic researchers and actuarial pricing professionals. The actuarial practice has constantly shown evidence of significantly different premium rates among the different rating territories. In this work, we build predictive models for claim frequency and severity using the synthetic Usage Based Insurance (UBI) dataset variables. First, we conduct territorial clustering based on each location’s claim counts and amounts by grouping those locations into a smaller set, defined as a cluster for rating purposes. After clustering, we incorporate these clusters into our predictive model to determine the risk relativity for each factor level. Through predictive modelling, we have successfully identified key factors that may be helpful for the rate regulation of UBI. Our work aims to fill the gap between individual-level pricing and rate regulation using the UBI database and provides insights on consistency in using traditional rating variables for UBI pricing. Our main contribution is to outline how GAM can address a more complicated functionality of risk factors and the interactions among them. We also contribute to demonstrating the territory clustering problem in UBI to construct the rating territories for pricing and rate regulation. We find that relativity for high annual mileage driven is almost three times that associated with low annual mileage level, which implies its importance in premium calculation. Overall, we provide insights into how UBI can be regulated through traditional pricing factors, additional factors from UBI datasets and rating territories derived from basic rating units and the driver’s location.
Automatic Compression of Neural Network with Deep Reinforcement Learning Based on Proximal Gradient Method
Authors: Wang Mingyi , Tang Jianhao , Zhao Haoli , Li Zhenni , Xie Shengli
Published: January 2023

In recent years, the model compression technique is very effective for deep neural network compression. However, many existing model compression methods rely heavily on human experience to explore a compression strategy between network structure, speed, and accuracy, which is usually suboptimal and time-consuming. In this paper, we propose a framework for automatically compressing models through the actor–critic structured deep reinforcement learning (DRL) which interacts with each layer in the neural network, where the actor network determines the compression strategy and the critic network ensures the decision accuracy of the actor network through predicted values, thus improving the compression quality of the network. To enhance the prediction performance of the critic network, we impose the L1 norm regularizer on the weights of the critic network to obtain a distinct activation output feature on the representation, thus enhancing the prediction accuracy of the critic network. Moreover, to improve the decision performance of the actor network, we impose the L1 norm regularizer on the weights of the actor network to improve the decision accuracy of the actor network by removing the redundant weights in the actor network. Furthermore, to improve the training efficiency, we use the proximal gradient method to optimize the weights of the actor network and the critic network, which can obtain an effective weight solution and thus improve the compression performance. In the experiment, in MNIST datasets, the proposed method has only a 0.2% loss of accuracy when compressing more than 70% of neurons. Similarly, in CIFAR-10 datasets, the proposed method compresses more than 60% of neurons, with only 7.1% accuracy loss, which is superior to other existing methods. In terms of efficiency, the proposed method also cost the lowest time among the existing methods.
Mixed-Integer Conic Formulation of Unit Commitment with Stochastic Wind Power
Authors: Zheng Haiyan , Huang Liying , Quan Ran
Published: January 2023

Due to the high randomness and volatility of renewable energy sources such as wind energy, the traditional thermal unit commitment (UC) model is no longer applicable. In this paper, in order to reduce the possible negative effects of an inaccurate wind energy forecast, the chance-constrained programming (CCP) method is used to study the UC problem with uncertainty wind power generation, and chance constraints such as power balance and spinning reserve are satisfied with a predetermined probability. In order to effectively solve the CCP problem, first, we used the sample average approximation (SAA) method to transform the chance constraints into deterministic constraints and to obtain a mixed-integer quadratic programming (MIQP) model. Then, the quadratic terms were incorporated into the constraints by introducing some auxiliary variables, and some second-order cone constraints were formed by combining them with the output characteristics of thermal unit; therefore, a tighter mixed-integer second-order cone programming (MISOCP) formulation was obtained. Finally, we applied this method to some systems including 10 to 100 thermal units and 1 to 2 wind units, and we invoked MOSEK in MATLAB to solve the MISOCP formulation. The numerical results obtained within 24 h confirm that not only is the MISOCP formulation a successful reformulation that can achieve better suboptimal solutions, but it is also a suitable method for solving the large-scale uncertain UC problem. In addition, for systems of up to 40 units within 24 h that do not consider wind power and pollution emissions, the numerical results were compared with those of previously published methods, showing that the MISOCP formulation is very promising, given its excellent performance.
Use of Nucleating Agent NA11 in the Preparation of Polyvinylidene Fluoride Dual-Layer Hollow Fiber Membranes
Authors: Kim Jihyeon , Lee Jinwon , Bezek Lindsey B. , Park Bumjin , Lee Kwan-Soo
Published: January 2023

Polyvinylidene fluoride (PVDF) dual-layer hollow fiber membranes were simultaneously fabricated by thermally induced phase separation (TIPS) and non-solvent induced phase separation (NIPS) methods using a triple orifice spinneret (TOS) for water treatment application. The support layer was prepared from a TIPS dope solution, which was composed of PVDF, gamma-butyrolactone (GBL), and N-methyl-2-pyrrolidone (NMP). The coating layer was prepared from a NIPS dope solution, which was composed of PVDF, N,N-dimethylacetamide (DMAc), and polyvinylpyrrolidone (PVP). In order to improve the mechanical strength of the dual-layer hollow fiber, a nucleating agent, sodium 2,2′-methylene bis-(4,6-di-tert-butylphenyl) phosphate (NA11), was added to the TIPS dope solution. The performance of the membrane was evaluated by surface and cross-sectional morphology, water flux, mechanical strength, and thermal property. Our results demonstrate that NA11 improved the mechanical strength of the PVDF dual-layer hollow fiber membranes by up to 42%. In addition, the thickness of the coating layer affected the porosity of the membrane and mechanical performance to have high durability in enduring harsh processing conditions.