Key Performance Indexes Research Articles

Introducing a new model for solid-state batteries: Parameter estimation and sensitivity analysis on diffusion, concentration, and electrochemical kinetics

Despite their potential, solid-state batteries (SSBs) are challenging to optimize due to the complexity of their materials and the early stage of their modeling, especially compared to liquid-electrolyte technologies. Many existing models rely on empirical equations that cannot represent internal mass-transport and kinetic phenomena. Even studies based on mechanistic models often focus on theoretical explanations of experimental phenomena or generating hard-to-obtain experimental data. In this work, a simple yet versatile mechanistic model – able to simulate any battery composed of a metallic anode, solid electrolyte and intercalation cathode – is proposed and used in a parameter estimation routine to identify the material properties of a Li/LiPON/LiCoO2 battery. After validation, a parametric study is made to address how each material property impacts concentration profiles, discharge curves, overpotentials, and core key-performance indexes (KPIs) related to energy efficiency and battery capacity. Findings reveal that cathode diffusion is critical to enhancing Extraction Efficiency, in some cases reaching 98.9% of the theoretical capacity without enhancing any other parameter. In the case of Energy Efficiency being a priority over capacity, electrolyte diffusion and concentration showed a pivotal role, in the range of parameters studied, to increase Voltaic Efficiency up to 97.8%. Despite not directly affecting the Extraction Efficiency, it is discussed how high overpotentials caused by Electrolyte Concentration and Kinetic Constants still can harm battery capacity, for charge–discharge cycles limited by boundaries in electrical potential. Finally, studies simultaneously varying two or more parameters show that, despite extreme property enhancements (up to ca 500x higher than the standard case) indeed lead to exceptional results (up to 96.4% for Voltaic Efficiency and 98.9% for Extraction Efficiency), to use such materials at its full potential will result in other zones of the device usually neglected – such as the overpotentials from the metal anode or even the current collector – may become the new stumbling block, underscoring the significance of considering the battery as a holistic system that will inherently exhibit bottlenecks. This also implies, however, in the perpetual potential for enhancement across its components.

High-Strength Controllable Resin Plugging Agent and Its Performance Evaluation for Fractured Formation.

Lost circulation is a common and complicated situation in drilling engineering. Serious lost circulation may lead to pressure drop in the well, affect normal drilling operations, and even cause wellbore instability, formation fluid flooding into the wellbore, and blowout. Therefore, appropriate preventive and treatment measures need to be taken to ensure the safe and smooth operation of drilling operations. So, it is necessary to conduct in-depth research on the development and performance of the plugging materials. In this study, urea formaldehyde resin with high temperature resistance and strength was used as the main raw material, and the curing conditions were optimized and adjusted by adding a variety of additives. The curing time, compressive strength, temperature resistance, and other key performance indexes of the resin plugging agent were studied, and a resin plugging agent system with excellent plugging performance was prepared. The formula is as follows: 25% urea formaldehyde resin +1% betaine +1% silane coupling agent KH-570 + 3% ammonium chloride +1% hexamethylenetetramine +1% sodium carboxymethyl cellulose. The optimal curing temperature is between 60 and 80 °C, with a controllable curing time of 1-3 h. Experimental studies examined the rheological and curing properties of the resin plugging agent system. The results showed that the viscosity of the high-strength curable resin system before curing remained stable with increasing shear rates. Additionally, the storage modulus and loss modulus of the resin solutions increased with shear stress, with the loss modulus being greater than the storage modulus, indicating a viscous fluid. The study also investigated the effect of different salt ion concentrations on the curing effect of the resin plugging system. The results showed that formation water containing Na+ at concentrations between 500 mg/L and 10,000 mg/L increased the resin's curing strength and reduced curing time. However, excessively high concentrations at lower temperatures reduced the curing strength. Formation water containing Ca2+ increased the curing time of the resin plugging system and significantly impacted the curing strength, reducing it to some extent. Moreover, the high-strength curable resin plugging agent system can effectively stay in various fracture types (parallel, wedge-shaped) and different fracture sizes, forming a high-strength consolidation under certain temperature conditions for effective plugging. In wedge-shaped fractures with a width of 10 mm, the breakthrough pressure of the high-strength curable resin plugging agent system reached 8.1 MPa. As the fracture width decreases, the breakthrough pressure increases, reaching 9.98 MPa in wedge-shaped fractures with an outlet fracture width of 3 mm, forming a high-strength plugging layer. This research provides new ideas and methods for solving drilling fluid loss in fractured loss zones and has certain application and promotion value.

Satisfying the needs for highly qualified engineering staff in a disruptively changing aircraft industry with special care for MRO sector

PurposeThe number of passengers in the aviation sector following COVID-19 has recovered in 2023 and is 5% higher than it was in 2019. The average annual growth of air travel is predicted to be 3.2% between 2019 and 2039. This means the need for aircraft maintenance, repair and overhaul (MRO) services will also increase. Moreover, the stakeholders require lower costs, higher effectiveness/market share and sustainability. These expectations can be realized only with the identification, development and implementation of new innovations while improving and optimizing the already used processes and procedures. Since only highly qualified graduates can reach these requirements, the need for profession-specific MSc and PhD level engineers has elevated significantly. The purpose of this paper is to introduce the development and implementation of a new MRO higher educational framework program in strong cooperation with enterprises and universities.Design/methodology/approachThe emphasis is placed on the program’s scouting, investigation, development, realization and evaluation by defining key performance indexes and aiming for the optimal solution for all participants.FindingsThe result of this study is the establishment of a new educational framework, the reinvention of the MSc curriculum and the integration of PhD-level researchers in the industry in a way that fulfills the needs and requirements of the MRO sector. In return, it will give various benefits to all parties involved.Originality/valueThe novelty of this work comes from creating a new educational MSc and PhD level framework that can push the MRO industry forward and fill the gap of missing engineers in this field. Plus, the newly developed program is highly flexible and can be used by other players in the economy after making some adaptions and modifications.

Optimisation of properties of multidimensional hybrid polymer nanocomposites for flexible pressure sensors

Flexible, wearable pressure sensors provide a convenient, timely, and portable solution for human motion detection. However, there is still a lack of reports on the synergistic effect of multidimensional hybrid polymer nanocomposites for modulating the sensor’s key performance indexes. Herein, we present a cost-effective and scalable approach to preparing multidimensional hybrid polymer composites for piezoresistive pressure sensors. Composite charge-transfer paths and contact types are presented for the first time and analyzed in relation to the sensor sensitivity and linearity. The sensor has good characteristics, such as 0 ∼ 70 kPa range, 369.39 kPa−1 sensitivity, a minimum resolving power of 18 Pa and 68 ms, and 76 ms response and recovery times, owing to the interconnecting porous structure of MS and the synergistic effect of the composites. The sensor exhibited a stable piezoresistive response and good reproducibility over 9000 + cycles. The sensor was then attached to different parts of the human body and evaluated for its ability to detect various human movements, including speech and elbow flexion. Finally, a prototype haptic sensing array and a prototype force measurement platform based on these pressure sensors were demonstrated.

Spray-based 3D concrete printing parameter design model: Actionable insight for high printing quality

A spray-based 3D concrete printing parameter design model to design and optimize printable concrete is proposed. The effects of different relatable printing parameters, such as nozzle travel speed (V), spray nozzle diameter (A), and spray standoff distance (D) on spray-based 3D printability and printing quality are investigated systematically. The hydration mechanism of spray-based 3D printed concrete is then explored in terms of mechanical performance, layer moisture content, micromorphology, and pore structure. The experimental results show that the printing quality of the printed concrete can be effectively improved by optimizing the relatable printing parameters. Based on the three key printing performance indexes of layer thickness, surface flatness, and rebound rate, the spray-based 3D concrete printing parameters design model β = f(V,A,D) is proposed. In the high-precision zone of β [0.7,1], the printing parameter V70A8D60 (β = 0.71) is selected to further verify the effectiveness of the model. It shows that the spray-based 3D printing process with appropriate printing parameters ensures the excellent hydration process of the printed concrete. Compared with those of the cast counterpart, the flexural, compressive, and splitting strengths of spray-based 3D printed V70A8D60 specimens increase by 5.67–14.48 %, 15.79–29.79 %, and 19.95–37.27 %, respectively. Further, high-pressure spraying in the spray-based 3D printing process optimizes the pore structure of the printed concrete with a 69.4 % decrease in total porosity. An “Olympic rings” convex structure with different accuracy grade parameters in the β model is designed and fabricated to demonstrate the feasibility and practical applicability of the currently proposed parametric design model.

Investigation on the Fatigue Crack Growth Behaviors of AISI 4340 Steel with Different Strength–Toughness Combinations

The strength, toughness, and fatigue crack growth (FCG) resistance of high‐strength steels are the key performance indexes concerned in the material selection of engineering components. It is considered that the FCG resistance of high‐strength steels can be optimized by simultaneous strengthening and toughening. In order to make clear whether the above view is correct or not, the strength–toughness combination and FCG resistance of AISI 4340 steel under different heat treatments are investigated and compared with those of 18Ni maraging steel in the present study. Meanwhile, the major fatigue damage mechanism of the AISI 4340 steel is analyzed and discussed. It is found that the FCG resistance of AISI 4340 steel enhances rapidly at first and then remains approximately the same with the decrement of strength (the improvement of toughness). Moreover, it is detected that simultaneously upgrading the strength and toughness of high‐strength steels cannot improve the FCG resistance. Finally, it is believed that the microscopic fatigue damage mechanism is the major factor determining the FCG resistance rather than the macroscopic strength–toughness combination, and the factors affecting the FCG resistance of AISI 4340 steel are mainly the pre‐existing dislocations and carbide precipitates.

Variation Regularity of Key Performance Indexes Against the Slot Number of Tooth-Coil PMSMs

Variation Regularity of Key Performance Indexes Against the Slot Number of Tooth-Coil PMSMs

코로나19 사태가 우리나라 기업의 직업재이동 현상에 미친 영향

Purpose: This paper aims to explore how job reallocation changes in response to the Covid-19 pandemic. More specifically, the paper calculates 5 job flows (job creation, destruction, reallocation, net employment growth and excess reallocation) and how they increase or decrease after the Covid-19 outbreak and examine whether the within-group reallocation is reinforced after the pandemic. Furthermore, the research estimates the key factors (variables) that bring a change in 5 job flows and what affects the most important job flow, namely excess job reallocation.
 Research design, data, and methodology: The research collects data necessary for empirical analysis from KISVALUE, the firm-level data source provided by NICE, a credit rating agency in Korea. And the paper adopts a standard methodology to generate 5 job flows, which was developed by Davis and Haltiwanger(1992). Also, i t also employs to Differences-in-Differences method to address what brings a change in 5 job flows after the outbreak of the pandemic.
 Results: The paper finds out evidence that there were a slight increase in job reallocation shortly after the pandemic unfolded and however job reallocation was alleviated in 2021 and 2022., which is inconsistent with previous studyies on financial crises (including 1997 financial crisis in Korea). Job reallocation between heterogeneous groups were intensified in the post-pandemic period. Furthermore, key performance indexes such as wage-to-sales ratio, leverage, average borrowing rate, ratio of financial expenditures to sales (or total costs) and net profit explain a increase or an decrease in 5 job flows. Notably, excess reallocation depends on leverage and financial expenditures, meaning that a change in the two variables have heterogeneous effects across industrial sectors.
 Implications: All in all, the main results indicate 3 important implications on job reallocation in the post Covid-19 period. First, Covid-19 is an economic shock that has a temporary effect on the magnitude of job reallocation. Second, although mild, it is a reallocative shock that brings reallocation of jobs across sectors or other groups of firms with different properties. Third, financial reasons such as leverage and financial expenditures are sources that results in job reallocation between 2-digit industrial sectors.

ES-net: An Integration Model Based on Encoder–Decoder and Siamese Time Series Difference Network for Grade Monitoring of Zinc Tailings and Concentrate

In froth flotation, the tailings grade and concentrate grade are the two key performance indexes. At present, the monitoring models of these two key grades mostly use the froth image or video from a flotation cell. However, flotation cells are closely related and coupled seriously. It is difficult to use a froth image or video from a flotation cell to represent the concentrate or tailings grade. Therefore, an encoder-decoder and Siamese time series network (ES-net) is proposed. First, an encoder-decoder (ED) model is designed to predict target grade (i.e., the zinc tailings or concentrate grade) by the video feature sequence of the first rougher and the measured target grade sequence. Meanwhile, a Siamese time series and difference network (STS-D net) is constructed to predict the target grade by the video feature sequences of target flotation cell (i.e., the last scavenger or cleaner) at current and previous moments and the previously measured target grade. After that, a multi-task learning strategy is proposed to integrate the ED model and STS-D net. Experiments show that the proposed ES-net can effectively integrate multiple froth visual features from different flotation cells and obtain more accurate concentrate and tailings grades than the existing models.

The low temperature liquid metal pressure sensors

Pressure measurement of geotechnical constructions subjected to low temperature plays significant roles in the safety and stability of geotechnical engineering activities. However, the research of pressure sensors in low temperature environment is lacked. In this work, a Galinstan liquid metal pressure sensor under low temperature condition is developed to detect pressure in geotechnical engineering. The elastomer PDMS (polydimethylsiloxane) is employed as the base material. Micro-channels are carved using microfluidic soft lithography technology. The liquid metal is filled as a conductor, and a spring steel case is used for encapsulation. The theoretical relationship between the resistance and pressure is derived, and the theoretical resistance values are compared with experimental resistance values to verify the accuracy of theoretical derivations. The key performance indexes of the designed sensor, such as the compliance, repeatability and hysteresis, are experimentally investigated. The numerical results show that the applied pressure can be uniformly transmitted to the internal PDMS chip with the help of the liquid buffer layer. The experimental results imply that this developed sensor with liquid buffer layer has high curve compliance, good repeatability and low hysteresis in low temperature environment, which provides effective tools for the pressure monitoring of geotechnical constructions subjected to low temperature.

Monitoring the Quality of Financial Management of Governmental Bodies: Analytical and Management Aspects of Application

One of the main results of reforming the budget process of the Russian Federation in the middle of the 2000s was the widespread implementation of the approach to the work of the executive power, in which budget funds are allocated in accordance with the expected results. Performance indexes are necessarily developed for government programs, national projects, and other strategic planning documents. Finally, monitoring by indexes is increasingly being used as a tool for evaluating the performance of executive authorities and officials. Is this approach expedient in any case? Is it always possible to use monitoring by indexes as a basis of the performance evaluating system for civil servants?This study considers the feasibility of including the results of assessing the quality of financial management of budget managers in the system of indexes for assessing the activities of executive bodies of state power of the Russian Federation constituent entity.The study is focused on distinctive features of monitoring the financial management quality of budget funds’ managers, which make it difficult to use for a sound judgment about the efficiency of the participants of the budget process. In the course of the study, an analysis was carried out by the method of comparison and correlation of Pearson using data from the following sources: the official website of the Committee of Finance of St. Petersburg, the state information system for information and analytical support of the activities of the executive bodies of state power in St. Petersburg and the automated system of the budget process of St. Petersburg.As a conclusion, arguments are provided not to use the results of monitoring the financial management quality, conducted by the financial authorities of the Russian Federation regions, due to its inherent specificity and its special role in the system of minimizing budgetary risks. The observations and conclusions made can be useful for further studies of key performance indexes’ systems for government bodies.

Exergy Loss Assessment Method for CNC Milling System Considering the Energy Consumption of the Operator

Modeling and assessing the sustainability of machining systems has been considered to be a crucial approach to improving the environmental performance of machining processes. As the most common machining system, the computer numerical control (CNC) milling system is a typical man–machine cooperative system where the activities of the machine tool and operator generate material and energy consumption. However, the energy consumption of the operator in the CNC milling system has often been ignored in most existing research. Therefore, existing methods fail to provide a comprehensive understanding of the sustainability of the CNC milling system. To fill this gap, an exergy loss assessment method is proposed to investigate the sustainability of the CNC milling system, where the energy consumption of the operator, the energy consumption of the machine tool, and material consumption are taken into consideration. The key performance indexes of the energy consumption of the operator, the energy consumption of the machine tool, the exergy loss, and the specific exergy loss (SEL) are analyzed and modeled. To demonstrate the feasibility of the proposed method, a case study was carried out on a three-axis machining center (XH714D), in which the energy consumption of the operator, the energy consumption of the machine tool, the exergy loss of energy consumption, the exergy loss of chips, the exergy loss of compressed air, the exergy loss of cutting tool wear, the exergy loss of cooling liquid dissipation, and the SEL were found to be 169,750 J, 758,211 J, 603,131 J, 2,031,404 J, 22,023 J, 301,868 J, 2673 J, and 88.04 J/mm3, respectively. The proposed method is effective to assess the sustainability of the CNC milling system, and the established exergy loss models build a good basis for exergy efficiency optimization.

Optimization Study on Salinity Gradient Energy Capture from Brine and Dilute Brine

The power conversion of salinity gradient energy (SGE) between concentrated brine from seawater desalination and seawater by reverse electrodialysis (RED) benefits energy conservation and also dilutes the discharge concentration to relieve the damage to coastal ecosystems. However, two key performance indexes of the maximum net power density and energy conversion efficiency for a RED stack harvesting the energy usually cannot reach the optimal simultaneously. Here, an optimization study on the two indexes was implemented to improve the performance of RED in harvesting the energy. A RED model for capturing the SGE between concentrated brine and seawater was constructed, and the correlation coefficients in the model were experimentally determined. Based on the model, the effects of a single variable (concentration, flow rate, temperature, thickness of the compartment, length of the electrode) on the performance of a RED stack are analyzed. The multi-objective optimization method based on the genetic algorithm was further introduced to obtain the optimal solution set, which could achieve the larger net power density and energy conversion efficiency with coordination. The ranges of optimal feed parameters and stack size were also obtained. The optimal flow velocity of the dilute solution and the concentration of the dilute solution are approximately 7.3 mm/s and 0.4 mol/kg, respectively.

Improved Coreless Axial Flux Permanent-Magnet Machine With Nonuniformly Distributed Winding

The windings of coreless axial flux permanent-magnet machine (CAFPM) are exposed to the rotor magnetic field, where each back electromotive force (EMF) harmonic is induced not only by several different spatial field harmonics but also by the winding distribution. In order to reduce the time harmonics of back EMF for CAFPM with non-overlapping winding, one new winding structure with non-uniform distributed coils is proposed in this paper, in which the coils are arranged in a non-uniform way with annular distribution in the stator. Firstly, the relationship between uniform and non-uniform distributed windings is analyzed based on the phasor diagram of each coil EMF, and the analytical expression of back EMF under non-uniform distributed windings is established. Secondly, key performance indexes under different working states, like no-load, are investigated by three dimensional (3-D) finite element analysis (FEA). Finally, comprehensive experiments are carried out to verify related theoretical analysis, which demonstrate that the non-uniform distributed windings can effectively reduce the time harmonics and increase the working efficiency.

Autonomous Following for Unmanned Ground Vehicles on Unstructured Scenario: Risk and Performance Assessment

Military unmanned ground vehicles are often used in wild natural environment, autonomous following and accompanying security are typical functions. In order to make a quantitative assessment about the autonomous following performance of unmanned ground vehicles on unstructured scenarios, a set of evaluation index system construction method is proposed based on the combination of risk analysis and key performance indexes. First, the kinematics model of autonomous vehicle following in straight and curve based on meta-trajectory is established. Second, the key indexes affecting the following performance are analyzed and obtained from collision risk and lost risk. Third, the evaluation index system of autonomous following performance is constructed from five dimensions: average following speed, collision risk, collision hazard degree, following stability and lost risk. Finally, two unmanned vehicles are tested, the results show that the conclusion based on the constructed evaluation index system can significantly reflect the difference of autonomous following performance, which is basically consistent with the subjective evaluation of the test personnel.

Design and Evaluation Framework for Modular Hybrid Battery Energy Storage Systems in Full-Electric Marine Applications

In the context of the maritime transportation sector electrification, battery hybridization has been identified as a promising manner of meeting the critical requirements on energy and power density, as well as lifetime and safety. Today, multiple promising battery hybridization topologies have been identified, while there is not a level playing field enabling comparison between different topologies. This study bridges this gap directly by proposing a generic hybrid battery energy storage system (HBESS) design and evaluation framework in full-electric marine applications that accounts for the key design requirements in the system topology conceptualization phase. In doing so, generalized key component models, such as battery cell models, aging models, power converter models, and thermal models, are established. Additionally, given the selected key requirements in this study, the case study comparing one baseline monotype design and two HBESS topologies has shown the clear advantage of battery hybridization. Furthermore, we find that, depending on the topology selection and the specific load scenario being considered, power converter devices can also worsen the key performance indexes.

Sustainability reporting, gender diversity, firm value and corporate performance in ASEAN region

This paper aimed to examine the influences of sustainability reporting and gender diversity on corporate outcomes of listed companies in ASEAN region. The listed companies in ASEAN region consisting of Thailand, Malaysia, Indonesia, and the Philippines during 2010 to 2019 were used as population and sample of this study. Seven key performance indexes of the Global Reporting Initiative (GRI) Standards, Carbon Disclosure Project (CDP), Carbon Knights, and Refinitiv were used to measure the extent and level of sustainability reporting, while the proportion of female board committee was used to measure gender diversity, and firm value measured by Tobin’s Q and firm performance measured by return on asset (ROA) were used as the proxies of corporate outcomes. The sequential logit regression models were developed to test the hypotheses used in this study. This study found positive impact of energy used, water management, work safety, and gender diversity on corporate performance, while corporate performance was influenced by carbon emission and waste management negatively. Moreover, gender diversity moderated the negative relationship between energy used, water management, work safety, and corporate performance. On the other hand, there was water management, and work safety influencing firm value positively, while waste management had negative impact on firm value. However, gender diversity did not moderate any relationship between sustainability reporting and firm value. The study findings benefit to top management who may encourage in sustainability reporting especially water management and work safety to enhance the corporate performance and value.

Machine Learning on Prediction of Relative Physical Activity Intensity Using Medical Radar Sensor and 3D Accelerometer.

One of the most critical topics in sports safety today is the reduction in injury risks through controlled fatigue using non-invasive athlete monitoring. Due to the risk of injuries, it is prohibited to use accelerometer-based smart trackers, activity measurement bracelets, and smart watches for recording health parameters during performance sports activities. This study analyzes the synergy feasibility of medical radar sensors and tri-axial acceleration sensor data to predict physical activity key performance indexes in performance sports by using machine learning (ML). The novelty of this method is that it uses a 24 GHz Doppler radar sensor to detect vital signs such as the heartbeat and breathing without touching the person and to predict the intensity of physical activity, combined with the acceleration data from 3D accelerometers. This study is based on the data collected from professional athletes and freely available datasets created for research purposes. A combination of sensor data management was used: a medical radar sensor with no-contact remote sensing to measure the heart rate (HR) and 3D acceleration to measure the velocity of the activity. Various advanced ML methods and models were employed on the top of sensors to analyze the vital parameters and predict the health activity key performance indexes. three-axial acceleration, heart rate data, age, as well as activity level variances. The ML models recognized the physical activity intensity and estimated the energy expenditure on a realistic level. Leave-one-out (LOO) cross-validation (CV), as well as out-of-sample testing (OST) methods, have been used to evaluate the level of accuracy in activity intensity prediction. The energy expenditure prediction with three-axial accelerometer sensors by using linear regression provided 97-99% accuracy on selected sports (cycling, running, and soccer). The ML-based RPE results using medical radar sensors on a time-series heart rate (HR) dataset varied between 90 and 96% accuracy. The expected level of accuracy was examined with different models. The average accuracy for all the models (RPE and METs) and setups was higher than 90%. The ML models that classify the rating of the perceived exertion and the metabolic equivalent of tasks perform consistently.

The Model of Socio-Economic Stratification of Society Based on An Agent Approach, Taking Into Account Rank Exchange

The purpose of the study is to demonstrate the possibility of adequate mathematical modeling of property inequality in a stratified society based on an agent approach, taking into account the unequal (rank) exchange between agents with different socio-economic status. To achieve this goal, it was necessary to solve the following tasks:1. To develop minimum criteria for the adequacy of mathematical models of socio-economic inequality.2. To substantiate the advantages of mathematical models based on an agent approach using rank exchange.3. To present the author’s version of the mathematical model of the goods’ movement in society based on an agent approach, taking into account rank exchange.4. To check the author’s mathematical model for compliance with the minimum qualitative criteria of adequacy and to create a quantitatively coinciding with the real distribution of the country’s population of the Russian Federation by income.5. Determine the limitations of the developed mathematical model by the authors.Materials and methods. The paper used statistical data from Rosstat, the Federal Tax Service of the Russian Federation, the World Bank, the US Bureau of the Census, the Edelman Trust Barometer, as well as data published by domestic and foreign researchers of inequality. These data were compared with the results of inequality calculations obtained using the mathematical model of the goods’ movement in society based on an agent approach, taking into account rank (nonequivalent) exchange.Results. The minimum criteria that any adequate model of stratification of society must meet are defined: 1. reveals a lognormal distribution of the population by income with a heavy tail; 2. reflects in long-term historical retrospect the trend of inequality growth; 3. demonstrates a short-term reduction of inequality during periods of socio-economic crises.The proposed model meets these requirements, it demonstrates not only qualitative, but also quantitative adequacy – reproduces by calculation the curve of the actual distribution of Russian society by income.Common concepts of inequality, in particular, the theory of superstars or skill-based technological change do not allow achieving such a result. The limitations of the created mathematical model are shown:– the impossibility of creating an adequate Lorentz curve with insufficient computing power;– inability to describe changes in cross-country inequality, since countries are not subjects of rank exchange, although interstate agreements certainly have an impact on the exchange between economic subjects of social interaction;– inability to describe situations of absolute poverty, i.e. long-term decline in income, although in the real economy such situations are sometimes observed;– the endless growth of inequality over time, whereas in reality economic processes of inequality growth are always opposed by social processes of counteraction to this growth.Conclusion. The mechanism of spontaneous emergence and growth of income (property) inequality as an inevitable consequence of market relations is demonstrated.The agent-based approach, taking into account the rank exchange, can allow identifying critical moments in time, after which extraordinary economic and socio-political consequences will have an irreversible character, and can also help in studying the influence of individual behavior of economic agents of different levels on the evolution of the entire economic, and as a consequence, socio-political system.The results obtained will be useful for strategic planning, when developing target indexes for the socio-economic development of regions and the country as a whole, and improving the methodology for calculating key performance indexes for civil servants

Modeling and High-performance Trajectory Optimization of the Industrial Robot

Rapidity, accuracy and energy cost are the key performance indexes for of the work of industrial robot. In this paper, the shortest time and the minimum energy consumption are taken as the goal for the comprehensive optimization. The control vector parameterization method is used to reasonably refine the time grid of the optimization problem. Then, an efficient control strategy for non-uniform adaptive mesh refinement is proposed. According to different changing trends, time nodes are merged or inserted into the time grid. While reducing the number of discrete grids, it also ensures the accuracy of the solution. Taking the Manutec R3 industrial robot as the object, the trajectory optimization simulation calculation is carried out. According to the verification of the simulation computing, the proposed method can significantly improve the time grid refinement. Compared with the traditional CVP method, not only the calculation time is shortened, but also more accurate results can be obtained.