Operational Performance Parameters Research Articles

Operation optimization of cement clinker production line based on neural network and genetic algorithm

The operation control plays a great role in the running performance of an industrial process. To achieve a successful control, the key point is searching for the target value of the control parameters. The relationship between operation parameters and performance parameters is usually nonlinear and complex, so it is hard to control an industrial process excellently with workers' experience. Based on a large amount of actual operation data, a bridge between control parameters and performance parameters might be built by the neural network. Prediction model is established by using neural network, genetic algorithm was then used to refine these parameters, the optimal condition can be further achieved by combining the relation bridge and genetic algorithm (GA). Paying attention to a cement clinker production process, this article established an optimizing approach based on the neural network and genetic algorithm and one-year operation data (615 sets). The feeding mass rate of raw meal and coal at the precalciner and the feeding coal mass rate at the rotary kiln are selected as the main independent variable and control parameters, and the specific standard coal consumption is determined as the key performance parameter and the optimization objective function. The mean square error and the correlation coefficient of the established neural network model are 12.84 and 0.89, respectively. The relative errors of approximately all prediction data (92.52 %) are within ±5 %. The optimal values for the raw meal feeding rate, the coal feeding rate into precalciner, and the coal feeding rate into rotary kiln are 259.57 t/h, 7.84 t/h, and 7.40 t/h, respectively. In that optimal condition, the specific standard coal consumption reaches 80.00 kgstandard coal/tclinker (This is a relative value, as there is a slight drift in zero point of the factory's instruments). A highly accurate neural network model is developed, which can significantly reduce standard coal consumption and improve industrial energy efficiency.

Estimation and monitoring of grid connected PV system generation

This paper presents a new method to identify the operating performance parameters of a photovoltaic (PV) generator and a grid connected inverter. This method has been applied to the behavior modeling and simulation of the grid connected PV system at the Centre de Developpement des Energies Renouvelables (CDER) in Algeria. The PV module (PVM) parameters has been identified in static with outdoor measurements of I-V curves in order to model the PV array generation. Using the Linear Reoriented Coordinates Method (LRCM), the prediction of maximum power point (MPP) of the PV array has been performed without using complicate approximations or Taylor series. In order to estimate the ac output power, a PV inverter performance model based on empirical relationship was used. However, an accurate identification of the inverter performance parameters is performed using an optimization algorithm, named Levenberg-Marquardt (LM) algorithm, and a moutput current and voltage. The simulation results were achieved through MATLAB/Simulink environment, for the setting and the testing of the models. The results show a good agreement between the measured and estimated results based on the identified parameters. The integration of the proposed method and the presented model present a simple way to estimate the expected system performance with a high degree of accuracy. This solution allows a development of automatic supervision, energy generation prediction and fault detection procedure.

Whale optimized routing path selection and 128 bit secured key management for maritime safety

The critical aspect in advancing global trade lies in ensuring security across marine trading systems. This research significantly contributes to monitoring ships by assessing operational performance parameters. These parameters are sensed through ship-attached sensors, and further transmitted to the cloud via an Internet of Things (IoT) Module. To optimize the efficiency of this data transfer to the cloud, the proposed work employs a Whale Optimization Algorithm-based Radial Basis Function Neural Network (WOA-RBFNN). The utilization of this algorithm enhances the overall effectiveness of the system. Furthermore, to address security concerns, a 128-bit Two Fish Algorithm-based key management is introduced, providing enhanced data protection. This dual-focus approach not only optimizes the efficiency of data transmission but also fortifies the system against potential cyber threats. These enhancements collectively contribute to the successful and secure transmission of information to the cloud advancing the security and efficiency of marine trading systems.

Evaluation of operational performance parameters of rolling stock when driving over bumpy roads

The current situation on the railway network of Russia and the East Siberian Railways in particular, the increase in the number of wagon cuts and unsatisfactory condition of the track and rolling stock, require the search for optimal solutions to these problems. Considering this topical subject it is necessary to touch upon the issues of modern strategies and trends in the development of railway transport with the introduction of modern technologies and technological equipment. As a result of a detailed consideration of the cause-and-effect relationship of the occurrence of factors affecting the dynamics of the car passing the track irregularities, the starting point will be an in-depth analysis of the system of interactions between the wheel and the rail. This analysis will make it possible to objectively assess the causes of existing problems in the field of operation, describe the emerging phenomena with a sufficient degree of justification, offer progressive topical solutions and possible promising developments in this industry. Turning to the statistics on failures over the past 3 years, one can trace the growth of malfunctions associated with defects in the rolling surface of wheel sets. Indeed, an increase in the speed of rolling stock, and in the volume and quantity of transported goods resulted in an increase in the intensity of rolling stock operation. Consequently, there was an increase in loads on the main components of the rolling stock and in the intensity of parts wear.

Research on the Trajectory and Operational Performance of Wheel Loader Automatic Shoveling

In the automatic shoveling operation of wheel loaders, the shovel trajectory has a significant influence on the operation’s performance. In order to obtain a suitable shovel trajectory and optimize the automatic shovel performance of the loader, we developed a test platform for the operational performance of loaders. Nine parallel shoveling trajectories of different depths were designed according to the coordination shoveling method. The formula for calculating the operational performance is established. The automatic shoveling test is performed according to the designed trajectory to obtain the real-time shoveling parameters, which are then combined with the calculation formula to calculate the operating parameters of the loader. Finally, the actual range of operational performance parameters is calculated by the normal distribution. The test results show that the trajectory with a shovel depth of 400 mm is the optimal trajectory. It was also verified by comparing manually controlled shoveling with it. With only a 1% difference in the full bucket rate, the operation time of automatic shoveling was 15.3% less than manually controlled shoveling, fuel consumption was 4.7% less, the energy consumption of practical work performed was 10.7% more, and maximum operation resistance was 20.5% lower. Therefore, the operational performance of the loader following this trajectory for shoveling meets the actual requirements.

Experimental study on design and operational performance of solar-powered venturi aeration system developed for aquaculture – A semi-floating prototype

Venturi-type injectors have been used usually due to the practical use and modular design that allows for quick configuration, ready-to-use, and low-cost solutions in the last years. This study aims to design a solar-powered venturi aeration system (SVAS) and determine its flow characteristics, standard, and real-time operational performance parameters. SVAS has a design providing the maximum vacuum and air velocity at air inlets and allowing for all technical measurements. Moreover, a solar-powered experimental apparatus having a weather station, a pool station, and a data logger station was constructed. Experiments were carried out using a plastic pool with a capacity of 4000 L, a diameter of 3 m and a depth of 0.75 m, four venturi injectors, and a submersible pump of 0.3 kW operated at the constant water flow regime of 4.1 m3 h-1. According to flow tests, the oxygen mass flow rates ranged from 2.77 to 2.84 kg h−1. The specific energy consumption values are 263.2 kJ per cubic meter for water flow and 380 kJ per kg for oxygen transfer.Standard performance experiments were repeated four times. The maximum overall oxygen mass transfer coefficient obtained during the experiments was 5.58 h−1. The maximum values of standard oxygen transfer rate (SOTR), standard aeration efficiency (SAE), and standard oxygen transfer efficiency (SOTE) were 0.206 kgO2 h−1, 0.681 kgO2 kWh−1, and 7.32%, respectively. The pool conditions were simulated using de-oxygenation and mixing systems to determine the operational performance. For simulation experiments, six procedures and two processes were applied. Throughout operational experiments of four days, real-time dissolved oxygen levels fluctuated between 1.05 mg L−1 and 6.65 mg L−1. The maximum performance values were 0.143 kgO2 h−1 for the actual oxygen-transfer rate, 0.474 kgO2 kWh−1 for aeration efficiency, and 5.1% for oxygen transfer efficiency.

An empirical investigation of performance assessment of Indian healthcare industry

PurposeThe purpose of the study is to measure the performance of Indian hospitals, both operationally and financially, by using hospital KPI's. The assessment is predominantly done by linking it to the existing Lean practices in Indian hospitals.Design/methodology/approachAn empirical study based on cross-sectional survey of hospital managers and specialists in various private healthcare facilities across India was conducted to validate the proposed Lean framework. From an extensive literature survey, the authors identified quality, delivery, efficiency, accessibility and patient centeredness to be the main operational performance (OP) indicators for hospitals. Business or financial performance was measured based on parameters which are average revenue per occupied bed (ARPOB), earnings before interest, tax, depreciation and amortization (EBITDA) and operating revenue. Confirmatory Factor Analysis (CFA) was carried out using a specialized technique, called Structural Equation Modelling(SEM) and an explicit factor structure was hypothesized.FindingsManagement commitment towards Lean in hospitals is statistically proven to have impacted operational and financial performance. However, leanness in technology and business processes showed no statistical significance on either operational or financial performance parameters. Hospital stakeholders showed statistical significance on though it had no impact on the financial performance. Results obtained from the statistical analysis indicate a positive impact of hospital Lean practices on timely delivery of services and improved service quality. Efficiency, accessibility of services and patient centered behavior in hospital operations could not be statistically proven to have impacted the financial performance.Social implicationsEffectiveness of Lean management (LM) principles in improving hospital operations is largely dependent on patient centered behavior. Empowered employees who are trained to add value from a customer view point, make hospital operations safe and improved. Properly trained and communicated employees who are committed to quality improvements can make a positive impact on patients' quality of life and thus positively impact the society. The study lists ways to attain the required outcomes.Originality/valueThis paper is among the very few that has attempted to suggest ways to link implementation of Lean practices more effectively in Indian hospitals to improve hospital performance at operational and financial levels.

Effect of thermal load on performance parameters of solar concentrating photovoltaic: High-efficiency solar cells

• Effects of thermal load on the cell's performance parameters has been described. • Cell temperature increases from 25 to 125 °C have been evaluated. • Variation of temperature rise of three-layer cells materials has been assessed. • Performance characterisation was performed through J-V and P-V curves. • A sensitivity analysis has been performed on five performance parameters. The triple-junction solar cell is designed to exploit a wide range of the solar spectrum photons. These triple-layers consisting of GaInP/GaInAs/Ge, it is monolithically stacked, leading to high conversion efficiency. To describe and understand it's operating behaviour, this paper presents a performance analysis of a triple-junction solar cell, based on estimation modelling. A model was developed to determine the performance characteristic of the solar cell. Hence, the J-V curve is characterising the performance of solar cells, which used to optimise and improve the design of the cells. It has been discussed the effects of thermal load related to cell temperature increases on the cell's operating performance parameters. Cell temperature increases from 25 to 125 °C have resulted variances, which causes a significant decrease in efficiency to approximately −17%, open circuit voltage by −15% and fill factor by −4.5%. On the other hand, the current density slightly increased by +5.5%. Finally, ought to consider the thermal management while designing and developing solar CPV technology; therefore, it's significant to improve cell efficiency and to maintain cell integrity from thermal damage.

Lab-on-a-Chip Platforms for Airborne Particulate Matter Applications: A Review of Current Perspectives.

Lab-on-a-Chip (LoC) devices are described as versatile, fast, accurate, and low-cost platforms for the handling, detection, characterization, and analysis of a wide range of suspended particles in water-based environments. However, for gas-based applications, particularly in atmospheric aerosols science, LoC platforms are rarely developed. This review summarizes emerging LoC devices for the classification, measurement, and identification of airborne particles, especially those known as Particulate Matter (PM), which are linked to increased morbidity and mortality levels from cardiovascular and respiratory diseases. For these devices, their operating principles and performance parameters are introduced and compared while highlighting their advantages and disadvantages. Discussing the current applications will allow us to identify challenges and determine future directions for developing more robust LoC devices to monitor and analyze airborne PM.

ENERGY EFFICIENCY OF AGRICULTURAL TRACTORS EQUIPPED WITH CONTINUOUSLY VARIABLE AND FULL POWERSHIFT TRANSMISSION SYSTEMS

The efficiency of agricultural tractor transmission has been improved over the years, with new concepts such as Continuously Variable Transmission (CVT) and Full Powershift (FPS) evolving in advanced technologies. Both options seek to offer the farmer greater operational results with lower energy expenditure, necessitating studies to assess the effectiveness of these technologies and define the best choice for each purpose. The objective of this work was to evaluate the energy efficiency of two tractors equipped with CVT and FPS transmissions. For this, a strip experiment was conducted in a randomized block design, that analyzed, in addition to CVT and FPS transmissions, target velocities of 4, 6, 8 and 10 km h-1. Operational energy performance parameters were evaluated, such as slippage index, engine rotation, operational velocity, fuel consumption, power available and efficiency on the drawbar, turbo pressure and temperatures of air intake and exhaust gas. Based on the results obtained, the tractor with FPS transmission was more energy efficient in most of the analyzed parameters, requiring 16.31% less in hourly fuel consumption, and providing 16.29% more in the traction bar yield, however, with lower operational velocity compared to the tractor with CVT transmission.

Performance Analysis and Test Research of PEMFC Oil-Free Positive Displacement Compressor for Vehicle

In order to study the matching characteristics of the positive displacement air compressor and the PEMFC (proton exchange membrane fuel cells), air supply subsystem, the basic operating performance parameters of the scroll and single-screw air compressors were analyzed with the focus on the oil-free double-wrap scroll compressor. According to the thermodynamic model and three-dimensional unsteady-state numerical simulation, the variation of the temperature, pressure, and velocity was obtained. Besides, under the rated operating condition of the compressor, the inlet and outlet mass flow rate of the fluid in the working chamber with the orbiting angle of the crank was achieved. Based on the built test platform, the actual working process of scroll and screw compressors was analyzed. This study indicates that the volume flow can be significantly increased by improving the speed of the positive displacement compressor. Based on the experimental measurement, when the height of the scroll tooth of the scroll compressor increases by 5 mm, the volume flow of the prototype SC2 increases by 0.17 m3/min and the exhaust temperature is reduced by 13 °C at the rated speed.

Regenerative flow pumps, blowers and compressors – A review

This paper presents a detailed and objective review of regenerative flow turbomachines, namely pumps, blowers and compressors. Several aspects of turbomachines like design and operating parameters, working principle, flow behaviour, performance parameters and analytical and Computational Fluid Dynamics (CFD) related details have been reviewed and summarized. Experimental work has been put in perspective and the most useful results for optimized performance have been presented. Consolidated plots of specific speed-specific diameter have been plotted which can be helpful in the early stages of design. Industrial outlook involving details of suppliers from various parts of the world, their product description and applications too are included. Finally, future research work to be carried out to make these machines widespread is suggested. This review is targeted at designer engineers who would need quantitative data to work with.

Rezistif Süperiletken Arıza Akım Sınırlayıcılarının MATLAB/SIMULINK’te Modellenmesi

High current levels caused by failures in power systems, comprise danger to the system and its elements. Limiting these fault currents protects the system and the system components from challenging thermal and dynamic effects. Many studies have been carried out to limit the fault currents. The common purpose of these studies are to ensure the safety and reliability of the system. The increasing usage of electrical energy leads to the continuous expansion and complexity of power systems. Therefore, fault current limiters are becoming increasingly important in continuously developing power systems. Operation continuity can be ensured by means of fault current limiters without making any changes in the existing system. Like many power system components, fault current limiters are modeled in virtual environments before they are used in the real system, and their operating performance and necessary parameters are determined. For this purpose, different effects on system parameters have been investigated in a 14-bus IEEE system using different SIMULINK superconductor fault current limiter (SFCL) models.

Applying simulation in lean service to enhance the operational system in Indian postal service industry

This paper aims to present an innovative approach to design a Lean Service System in the India Post service industry using the Simulation method to reduce the system’s complexity. Using logic and systematic building blocks, simulation models have been developed from lean service elements using the arena software and verified in Siemens Tecnomatix plant simulation suite. Simulation is used to replicate the real model, guide the future production system, and determine the optimal parameter values. Simulation studies have been divided into two perspectives, “before LS” and “after LS” through Value Stream Mapping (VSM). It has been found that there is a 9.62 percent enhancement in delivering articles per person. A real case of postal service internal operational performance has been taken for the study. This study is the first to combine Value Stream Mapping - Simulation (VSM-Sim) to simulate and optimize the mailing service operations’ operational performance parameters.

Characterizing the growing microorganisms at species level in 46 anaerobic digesters at Danish wastewater treatment plants: A six-year survey on microbial community structure and key drivers

Anaerobic digestion (AD) is a key technology at many wastewater treatment plants (WWTPs) for converting primary and surplus activated sludge to methane-rich biogas. However, the limited number of surveys and the lack of comprehensive datasets have hindered a deeper understanding of the characteristics and associations between key variables and the microbial community composition. Here, we present a six-year survey of 46 anaerobic digesters, located at 22 WWTPs in Denmark, which is the first and largest known study of the microbial ecology of AD at WWTPs at a regional scale. For three types of AD (mesophilic, mesophilic with thermal hydrolysis pretreatment, and thermophilic), we present the typical value range of 12 key parameters including operational variables and performance parameters. High-resolution bacterial and archaeal community analyses were carried out at species level using amplicon sequencing of >1,000 samples and the new ecosystem-specific MiDAS 3 reference database. We detected 42 phyla, 1,600 genera, and 3,584 species in the bacterial community, where 70% of the genera and 93% of the species represented environmental taxa that were only classified based on MiDAS 3 de novo placeholder taxonomy. More than 40% of the bacterial species were found not to grow in the mesophilic and thermophilic digesters and were only present due to immigration with the feed sludge. Ammonium concentration was the main driver shaping the bacterial community while temperature and pH were main drivers for the archaea in the three types of ADs. Sub-setting for the growing microbes improved significantly the correlation analyses and revealed the main drivers for the presence of specific species. Within mesophilic digesters, feed sludge composition and other key parameters (organic loading rate, biogas yield, and ammonium concentration) correlated with specific growing species. This survey provides a comprehensive insight into community structure at species level, providing a foundation for future studies of the ecological significance/characteristics and function of the many novel or poorly described taxa.

Estimation of state of charge of lithium battery based on parameter identification of fractional order model

Accurate estimation of state of charge of lithium battery is one of the important performance parameters for safe and reliable operation of lithium battery. A fractional order second-order Thevenin equivalent circuit model was proposed by based on the improvement of the traditional Thevenin equivalent circuit model for accurately estimating the state of charge of lithium-ion battery. In order to overcome the shortcomings of the least square method easily enter into local convergence or even unable to converge, an adaptive genetic algorithm is proposed to identify the parameters of lithium battery model, and global parameter identification is carried out to improve the convergence of the algorithm. Matlab simulation shows that the parameters of fractional order model of the second-order Thevenin equivalent circuit identified by adaptive genetic algorithm are better than those of integer order model identified by least square method. Combined with extended Kalman filter, the estimation of state of charge accuracy control is realized, with the accuracy error being within 1.61%.

Comparative Study of E- and U-core Modular Dual-Stator Axial-Field Flux-Switching Permanent Magnet Motors With Different Stator/Rotor-Pole Combinations Based on Flux Modulation Principle

In this paper, the dual-stator axial-field flux-switching permanent magnet (DSAFFSPM) motors with E- and U-core stator modular segments, as well as different stator/rotor-pole combinations are compared. The operation performance of the DSAFFSPM machines are explored by using the MMF-permeance model method. A more comprehensive theoretical analysis, no more limited to numerical calculation, is presented. This reveals directly the relations between the operation performance and design parameters of the machine. The performance comparisons between the E-shaped and U-shaped teeth DSAFFSPM machines are given, including the effects of the structural parameters on the electromagnetic torque, different stator/rotor-pole combinations on the winding factor and gear ratio, the differences of the average torque and the torque density and the efficiency in the 12/10 U-core and 6/10 E-core topology. These are the basis of the DSAFFSPM machine design and optimization. Finally, the experiments on the two prototype, 6/10 E-core and 12/10 U-core DSAFFSPM machines are carried out. The results show that the average torque of the 12/10 U-core prototype is higher than that of the 6/10 E-core prototype, while the torque density and the efficiency of 6/10 E-core DSAFFSPM machines are much higher.

Selection and design of tools for finishing machining of seal grooves of hydraulic cylinders

The most important operating performance parameters of machine components such as tightness, wear resistance, durability, and corrosion resistance largely depend on the state of their surface layer, determined by the parameters of machine processing during manufacturing. Selection of the technique for final machining of machine components is a rather difficult task, since, despite the large amount of information on technological support of the surface layer parameters, there are practically no recommendations on the quantitative estimates of the parameters of performance properties achieved in this case. Reliable functioning of hydraulic systems, their durability, and, consequently, reliable functioning and durability of the drilling rig, depend on the quality of the surface of the seal grooves. At present, turning is used for grooves machining, which in some cases does not provide the required quality indicators of the machined surface according to the surface roughness parameter. In this regard, an analysis of the possibilities of obtaining the required surface roughness using edge cutting machining techniques was conducted as well as other machining techniques ensuring uniformity of the surface roughness of seal grooves were analyzed. One of the promising processing techniques that can provide the required quality of the machined surface is a surface plastic deformation method. However, in order to use this method effectively, it is necessary to carry out an experimental study of the rolling process and determine processing conditions.

Techno-economic assessment of Fischer-Tropsch synthesis and direct methane-to-methanol processes in modular GTL reactors

The aim of this study is to perform a techno-economic assessment of the Fischer-Tropsch synthesis (FTS) process in a microchannel reactor (MCR) to produce clean syncrude, and the Direct Methane to Methanol (DMTM) process in a compact plant footprint. The operational and economic performances of the two processes were modeled using the Aspen HYSYS v7.2. The operational performance parameters include products yield and the economic performance parameters include net present value (NPV), payback period (PBP) and internal rate of return (IRR). In addition, the effects of tailgas recycle ratios and water integration on the performances of the FTS process and the effect of methane recycle ratios on the performances of the DMTM were investigated. The simulation results showed that the unit cost of the DMTM process was sensitive to the methane recycle ratio, however, that of the FTS in MCR was less sensitive to the tailgas recycle ratios. In order to maintain an IRR > 10 %, the tail gas recycle ratio of the FTS in MCR had to be greater than 8 % and 30 %, at CO conversions of 80 % and 72 %, respectively, whereas in the DMTM process, a minimum methane recycle ratio of 60 % was required to achieve any profitability. In addition, the DMTM process appeared to have significantly higher net energy requirements per product yield when compared with those of the FTS in MCR process; however, both processes had higher energy requirements than those of conventional GTL technologies.

A Heuristic Methodology for Optimal Deployment of Radar Systems in a Constrained Area of Operation

In emerging network-centric warfare scenarios, the location of sensors in the sensor-grid plays a dominant role in determining the effectiveness of air defence against enemy air threats. Maximising the coverage area of sensors in the sensor-grid, considering operational performance parameters, terrain features and deployability is a challenging task for military operational planners and commanders. Such optimisation problems may not be amenable to classical operations research techniques, or may require enormous computational time to arrive at the results as the decision space grows non-linearly for large areas of operation. In this paper, a novel methodology that uses a heuristic technique (genetic algorithms) to compute the optimal or near-optimal deployment locations for a given set of sensors in a constrained area of operation is proposed. The proposed methodology is illustrated with a number of case studies and a decision support tool is developed as an aid to the military commanders.