Performance Evaluation Of System Research Articles

Performance Evaluation of Novel Advanced Recompression Absorption Refrigeration Systems Equipped with Ejector and Vapor Injection Technology

The absorption refrigeration cycle (ARC) faces challenges considering its decreased working pressure and COP. By integrating Recompression technology (RAC) into ARC, these issues are partly addressed. To address these inefficiencies, in this study, ejector and vapor injection techniques are incorporated into refrigerant side of the RAC cycle, resulting in the development of advanced systems: Refrigerant ejector enhanced recompression absorption cycle (RE-RAC) and Vapor injection enhanced recompression absorption cycle (VI-RAC). Key metrics assessed are 1st and 2nd law efficiency, system exergy destruction rate, compressor load, and generator heat requirements. Conclusively, under analogous operating conditions, RE-RAC and VI-RAC demonstrate a substantial improvement in COP, achieving 76 % and 63 % enhancements, respectively, over the standard RAC system. Compared to the conventional solution ejector-based SE-RAC, these systems show performance increases of 28 % and 19 %, respectively. The findings also highlight the sensitivity of these systems to parameters such as generator temperature and pressure, evaporator temperature, absorber temperature, evaporator recovery and normal pressure ratio. At higher evaporator temperature and lower generator temperature, the performance of these systems as well as enhancement of RE-RAC over VI-RAC is higher observed. The optimal value of generator pressure and recovery pressure ratio for maximum efficiency and minimum total exergy destruction rate is also dependent upon these. At a generator temperature of 67 °C and an evaporator temperature of 8 °C, RE-RAC exhibits a 35 % higher COP compared to VI-RAC. However, at −10 °C evaporator temperature, changes in external generator heat input and compressor work reduce the COP enhancement to 5 %.

Regularity analysis of resilient modulus for hot-mix asphalt with large temperature fluctuations

To evaluate the regularity of resilient modulus for hot-mix asphalt (HMA) under large temperature fluctuations, back propagation (BP) neural network technology was used to analyze the continuous change of HMA resilient modulus. Firstly, based on the abundant data, the training model of HMA resilient modulus was established by using BP neural network technology. Subsequently, BP neural network prediction and regression analysis were performed, and the prediction model of HMA resilient modulus at different temperatures (−50 °C to 60 °C) was obtained, which fully considered multi-factor and nonlinearity. Finally, the fitted theoretical model can be used to evaluate the HMA performance under the condition of large temperature fluctuations, and the rationality of theoretical model was verified by taking Harbin region as an example. It was found that the relationship between HMA resilient modulus and temperatures can be described by inverse tangent function. And the key parameters of theoretical model can be used to evaluate the continuous change characteristics of HMA resilient modulus with large temperature fluctuations. The results can further improve the HMA performance evaluation system and have certain theoretical value.

Optimization and performance evaluation of a novel absorption-based atmospheric water generator system for enhanced energy efficiency

Providing potable water poses a severe and chronic challenge for the human race. Conventional desalination systems are only feasible in large-scale production, requiring significant energy and a source of feeding water. Atmospheric water harvesting is a decentralized water production method that uses air humidity as a renewable water source. This technique holds promise for providing water even in hard-to-reach regions with no source of liquid water. However, the feasibility of this method declines in arid or semi-arid climates. In this paper, a novel absorption-based atmospheric water generator is proposed to improve the feasibility and cost-effectiveness of this technique to make it a viable method for producing fresh water, even in arid regions. The system is modeled using EES software to explore the effects of seven adjustable parameters on its performance. Subsequently, the modeled system is transferred into MATLAB through the utilization of artificial neural networks. A tri-objective optimization is then carried out using the genetic algorithm approach. The optimized system can produce 14016m3/year of fresh water, with a levelized cost of approximately 33.72$/m3, operating under hot and arid weather conditions (27°C and 25% RH). The data acquired from the system’s performance parameters is leveraged to derive correlations that are used to determine the system’s performance based on the input weather data. These correlations allow for the assessment of system feasibility across various regions and serve as a valuable shortcut in modeling similar systems for future research.

Comprehensive Performance Analysis of Hybrid Solar Water Heating Systems: Synergizing Photovoltaic and Thermal Technologies

Abstract: Solar water heaters are an efficient and sustainable technology for meeting the growing demand for hot water in residential and commercial applications. This abstract presents a comprehensive overview of the performance evaluation of solar water heater systems through an extensive experimental study. The study aims to assess the effectiveness and efficiency of different solar water heater configurations under varying operating conditions. The experimental investigation involved the measurement and analysis of key performance parameters such as solar collector efficiency, heat transfer efficiency, thermal storage capacity, and overall system efficiency. A range of factors including solar radiation intensity, ambient temperature, water flow rate, and collector tilt angle were systematically varied to examine their impact on system performance. The results of the experimental study demonstrated the significant potential of solar water heaters in providing cost-effective and environmentally friendly hot water solutions. The solar collector efficiency was found to be highly influenced by the solar radiation intensity, with higher levels of solar irradiation leading to increased thermal energy generation. The heat transfer efficiency was optimized by adjusting the water flow rate and collector tilt angle, ensuring efficient transfer of heat from the collector to the water. Furthermore, the thermal storage capacity of the system played a crucial role in maintaining a consistent supply of hot water during periods of low solar radiation or high demand. Overall system efficiency was found to be strongly dependent on the integration of efficient heat exchangers and insulation materials. Based on the experimental findings, recommendations for system design and optimization were formulated, highlighting the importance of proper sizing, selection of suitable materials, and appropriate control strategies. The results also identified areas for future research, such as the integration of advanced heat transfer enhancement techniques and the utilization of hybrid solar water heater systems

Penggunaan Energi Terbarukan PLTS untuk Efisiensi Biaya dan Keberlanjutan Usaha Bubur Bayi Shashi di Bukittinggi

Shashi Baby Porridge business in Bukittinggi faces significant operational cost challenges due to high electricity consumption, particularly from production equipment. To address this issue, a community service team from the Department of Electrical Engineering at Padang State Polytechnic implemented a Solar Power System (SPS) as an alternative solution. The service process included energy needs analysis, SPS system design, installation, and performance monitoring and evaluation. The implementation of the SPS successfully reduced electricity costs and dependence on conventional electricity while supporting environmental conservation efforts. The installed SPS, with a total capacity of 200 Wp, provides energy for lighting, resulting in significant savings in operational costs. Socialization with the owners and workers was also carried out to ensure optimal system maintenance and operation. The outcomes of this project are expected to inspire other small businesses to adopt renewable energy technologies to enhance efficiency and sustainability.

Research on the Performance Evaluation of Listed Liquor Companies based on the Entropy Weight and Closeness Degree Method

In this paper, based on the 2023 annual report data of 18 listed liquor enterprises, adaptation indicators are selected as research samples, performance evaluation system is constructed, entropy weight method and correlation value method are combined, and the performance evaluation of listed liquor enterprises is carried out. 12 indicators are selected and SPSSAU software is used to conduct empirical research on the performance of listed liquor enterprises. The correlation value of 18 liquor enterprises is calculated and the comprehensive performance of the enterprises is sorted to provide relevant help for investors' decision-making.

An analytical approach for an AI-based teacher performance evaluation system in Saudi Arabia’s schools

Teacher performance evaluation is essential to a teacher’s primary responsibilities. This study investigates the process of evaluating teachers’ performance to provide a basis for planning an ongoing professional development program. AI-based systems present an opportunity for objective and reliable evaluations, facilitating the identification of areas requiring improvement and contributing to the overall enhancement of educational quality. Consequently, incorporating AI into evaluating teachers has become a research hotspot. This research proposes an analytical comprehensive AI-based system for teacher evaluation. Moreover, we introduce a novel analytical index system derived from the current adopted Key Performance Indicators (KPI) in the Ministry of Education in Saudi Arabia and an overall algorithm. This study is part of an integrated project to evaluate teachers’ performance using AI. To build our model, we are accurately determining the evaluative weights through 13 workshops held with 283 field experts. The main hypothesis is that the weights were evenly distributed. After studying them, we found they were relatively different by 0.1 to 0.3%. By analyzing T-KPI, we believe that our proposed index system could overcome the limitations of human-based assessments as it assigned appropriate AI techniques for each, thus ensuring accurate, reliable, and objective evaluation. This innovation would also economically impact rationalizing spending and reducing costs.

The development of a performance evaluation index system for Chinese Centers for Disease Control and Prevention: a Delphi consensus study

BackgroundThe performance evaluation of the Centers for Disease Control and Prevention (CDC) is crucial for enhancing the quality of public health services. With the ongoing reform of the CDC system in China, the existing performance evaluation system faces challenges. This study used the Delphi method to develop a new performance evaluation system for China’s provincial, city, and county-level CDC.MethodsFollowing the “Structure-Process-Outcome” model, assessment indicators were systematically collected. Indicators were modified and screened through two Delphi rounds based on CDC responsibilities, health development, and national policies. Twenty-four experts provided ratings and recommendations, and the research team evaluated questionnaire reliability, expert positivity, expert authority, and opinion consistency.ResultsThe preliminary index system identified through the literature review and pre-survey included 11 primary, 30 secondary, and 64 tertiary indicators. After the first round of consultation, two secondary indicators and 11 tertiary indicators were removed and 22 tertiary indicators were added. After the second round of consultation, three secondary indicators and 11 tertiary indicators were removed and three tertiary indicators were added, at which point the p-value of the test for Kendall’s coefficient of concordance W was < 0.001 and the coefficient of variation was within acceptable limits (< 0.25), so the consultation was concluded. The final index system included 11 primary, 25 secondary, and 67 tertiary indicators.ConclusionsThis study responded to the CDC system reform by developing a comprehensive performance evaluation index system for provincial, city, and county-level CDC in China. The index system is both scientifically grounded and practical, serving as an effective tool for promoting the high-quality work of CDC organizations.

Performance evaluation of a hybrid treatment system for the treatment of grey water

ABSTRACT The performance of a combined up-flow submerged aerated biological filter (SABF) and photocatalytic process (PC) for the treatment of grey water was studied. The removal of COD, hardness, alkalinity, and turbidity was considered. The removal efficiency of SABF using organic and inorganic packing materials was evaluated. The combined SABF and PC removed 100% of COD, up to an organic loading rate (OLR) of 0.21 ± 0.05 kg/m3/day at 12 h HRT, irrespective of the packing media. The fibrous outer shell of coconut fibres favoured turbidity removal, but both the organic and inorganic packing materials showed equal performance in the removal of physicochemical parameters of the grey water.

Thermal regulation for buildings using evaporative cooling technique: Experimental study

Global warming and increased air-conditioning demand drive up energy use. A passive cooling system for the building's roofs is one solution to this problem. The current study intends to provide a unique evaporative cooling concept for cooling building roofs that use significantly less water than prior approaches. To reduce room temperature, saturated-activated alumina beds with 2, 4, and 6 cm thicknesses were put over the roof. Pure and 35 PPT saline water were utilised to evaluate system performance and sustainability. The device successfully reduced rooftop temperatures by 84 % and 70.9 % after 24 h of testing (6 h during daytime and 18 h at night) under heat loads of 800 and 1000 W/m2. The findings show that salt water is a feasible alternative to freshwater that does not sacrifice cooling efficiency. From an environmental standpoint, compared to a bare roof, a 6-cm layer of saturated activated alumina tables can reduce annual carbon dioxide emissions by 71.3 tCO2/m2 and 92 tCO2/m2 for roof areas subjected to daily solar radiation of 6000 W h/day and 4800 W h/day, respectively.

Comparative performance evaluation of dual-axis solar trackers: Enhancing solar harvesting efficiency

Nowadays, renewable energy is a much discussable topic because of its important specifications such as pollution and un end sources. This paper emphasizes the importance and capabilities of the dual axis solar tracking system (DASTS) of solar cell technologies. The study carried out a practical process of a dual-axis system design, which practically demonstrates the influence of dual-axis solar trackers, including their operational principles, advantages, and associated challenges. Furthermore, it has been shown that dual-axis solar trackers can significantly increase solar energy yield by capturing maximum sunlight, making them an important advancement in improving the efficiency and effectiveness of solar energy generation. The paper also presents a performance evaluation of a solar tracker system that improved energy output by 45 % compared to the fixed solar panel (FSP) while also reducing the numerical calculation (NC) efficiency of DASTS by 3.16 %. Based on these findings, solar tracker systems can provide sustainable and environmentally friendly energy solutions that are both feasible and substantial.

Manajemen Koperasi Gema Nusa Gerakan Pemuda Ansor Kecamatan Cilongok Kabupaten Banyumas Tahun 2023

The aim of this research is to analyze the management of the Gema Nusa Cooperative in an effort to improve the welfare of its members and support local socio-religious organizations. The research method used is a qualitative approach with a case study design. Data collection was conducted through interviews, observations, and documentation studies. Data analysis includes three data processing flows, namely data reduction, data presentation, and conclusion drawing. Data validation uses data triangulation, which is a data collection technique that combines various existing data and sources. The results show that Gema Nusa Cooperative has implemented management functions quite well, but still has some weaknesses in terms of strategic planning and supervision. Therefore, Gema Nusa Cooperative needs to develop a comprehensive organizational strategic planning, develop an effective and efficient organizational structure, and apply the principles of good cooperative governance that includes a performance monitoring and evaluation system, performance feedback, and responsive and collaborative problem solving. Collectively, with the increase in management capacity, it is expected that Gema Nusa Cooperative can be more optimal in improving the welfare of its members.

Turning Data Center Waste Heat into Energy: A Guide to Organic Rankine Cycle System Design and Performance Evaluation

This study delves into the adoption of the organic Rankine cycle (ORC) for recovering waste heat from data centers (DCs). Through a literature review, it examines energy reuse with a focus on electric power generation, the selection of working fluids, and system design principles. The objective is to develop a thorough framework for system design and analysis, beginning with a quantity and quality investigation of waste heat available. Air cooling systems, chosen often for their simplicity, account for about 70% of used cooling methods. Water cooling demonstrates greater effectiveness, albeit less commonly adopted. This study pays close attention to the selection of potential working fluids, meticulously considering the limitations presented by the available sources of heat and cold for vaporization and condensation, respectively. It reviews an ORC-based system setup, incorporating fluid streams for internal processes. The research includes a conceptual case study where the system is designed and simulations are conducted in the DWSIM environment. The simulation model considers hot air or hot liquid water returning from the data center cooling system for ORC working fluid evaporation. Ambient water serves for condensing, with pentane and isopentane identified as suitable organic fluids. Pentane assures ORC net electric efficiencies ranging between 3.1 and 7.1% when operating pressure ratios increase from 2.8 to 6.4. Isopentane systems, meanwhile, achieve efficiencies of 3.6–7.0% across pressure ratios of 2.7–6.0. Furthermore, the investigation provides key performance indicators for a reference data center in terms of power usage effectiveness (PUE), energy reuse factor (ERF), energy reuse effectiveness (ERE), and greenhouse gas (GHG) savings. This study concludes with guidelines for system analysis, including exergy considerations, and details the sizing process for evaporators and condensers.

Modelling and performance evaluation of a parabolic trough solar water heating system in various weather conditions in South Africa

In recent years, various energy sources and methods have been used to heat water in domestic and commercial buildings. Water heating methods for large households or commercial buildings include electrical heating elements, gas heaters, and solar energy (solar concentrators, flat plate collectors, evacuated tube collectors, etc.). In recent decades, the focus of water heating has shifted to solar energy, which is abundantly available in most African countries. The weather condition of a region has a huge impact on the system's performance. South Africa is characterised by four different weather seasons (winter, spring, summer, and autumn), unlike most African countries. Therefore, this study focuses on the impact of weather seasons on the system's performance for water heating through the combined use of solar energy and solar concentrator techniques. The system performance was modelled by using Matlab Simulink®, where historical weather data for Pretoria, South Africa, was fed into the model. Based on the weather data input, the system behaviour varied per season due to the change in solar intensity. The average outlet temperatures of the absorber, in the order of magnitude, were 333, 332, 328, and 325 K during the autumn, summer, spring, and winter seasons, respectively. Similarly, the average storage tank temperatures, in the order of magnitude, were 366, 364, 363, and 360 K in spring, summer, autumn, and winter, respectively. From this study, it is concluded that the different weather seasons in South Africa, have a direct impact on the performance of the system. Irrespective of the season, the system produced the required volume of hot water required throughout the year.

Thermodynamic performance evaluation and optimization of a hybrid system integrating vacuum graphene-anode thermionic converters with direct carbon fuel cells

An efficient hybrid system integrating a direct carbon fuel cell (DCFC) with a vacuum graphene-anode thermionic converter (VGTC) is proposed for cogeneration. The VGTC efficiently recycles waste heat released from the DCFC and generate additional electricity, significantly improving energy utilization efficiency and economic performance. A comprehensive mathematical model is developed to quantitatively assess the thermodynamic performance of the hybrid system, taking into account the overpotential losses of the DCFC and the irreversible energy losses occurring within the system. The results show that at an operating temperature of 923 K, the hybrid system can achieve a maximum power density of 466 W/m2, which is approximately 1.34 times that of a single DCFC, indicating a significant improvement in output performance. Besides, the optimal operating region and parameter selection criteria for the hybrid system are determined using finite-time thermodynamic optimization theory. Furthermore, the effects of essential parameters on the output performance of the hybrid system, such as the operating temperature of the DCFC, the heat transfer coefficient, the Fermi level of graphene, the work function of the cathode, the thermal emissivity, and the reflectivity of the back mirror, are investigated. Finally, the comparative study shows that the proposed hybrid system outperforms other previously reported hybrid systems regarding output electric power and conversion efficiency due to the efficient high-grade waste heat recovery and energy conversion by the VGTC.

Power Generation Systems Assessment: A New Approach

Power generation systems have become useful for grid base and off grid electric power generation. Hence, its performance has become critical for sustainable growth and development. Performance evaluation of power generation systems has always been carried out using the independent assessment approach (IAA) whose models are: the reliability, availability, emission characteristics, energy and exergy efficiency. The IAA approach only assesses the system performance in part without recur to other indexes, hence, limiting a holistic view of the true plant state. In this paper, the development of a new performance index using the combined assessment approach (CAA) is explored. This approach (CAA) seeks to combine two relatable traditional measures for the assessment of power generation system. The model combines exergy efficiency and reliability measures for analysis. First Independent Power Limited (FIPL) gas turbine power plant was used to test the model. The plant reliability and availability were evaluated along with its thermal efficiency using the exergy model. The analysis of plant thermal efficiency was carried out using the steady state model. Results of the traditional indexes of the plant were compared with the proposed (Bassy-II index) index. It was seen that the new index provided a new assessment criteria. The exergy efficiency, reliability and availability measures indicated a fairly rated plant state. However, the new index defined a new plant state which is unique and represents the true status of the system in whole. Hence, the proposed index (Bassy-II index) is recommended for use in the holistic assessment of power generation systems.

Comprehensive Review: Machine and Deep Learning in Brain Stroke Diagnosis.

Brain stroke, or a cerebrovascular accident, is a devastating medical condition that disrupts the blood supply to the brain, depriving it of oxygen and nutrients. Each year, according to the World Health Organization, 15 million people worldwide experience a stroke. This results in approximately 5 million deaths and another 5 million individuals suffering permanent disabilities. The complex interplay of various risk factors highlights the urgent need for sophisticated analytical methods to more accurately predict stroke risks and manage their outcomes. Machine learning and deep learning technologies offer promising solutions by analyzing extensive datasets including patient demographics, health records, and lifestyle choices to uncover patterns and predictors not easily discernible by humans. These technologies enable advanced data processing, analysis, and fusion techniques for a comprehensive health assessment. We conducted a comprehensive review of 25 review papers published between 2020 and 2024 on machine learning and deep learning applications in brain stroke diagnosis, focusing on classification, segmentation, and object detection. Furthermore, all these reviews explore the performance evaluation and validation of advanced sensor systems in these areas, enhancing predictive health monitoring and personalized care recommendations. Moreover, we also provide a collection of the most relevant datasets used in brain stroke analysis. The selection of the papers was conducted according to PRISMA guidelines. Furthermore, this review critically examines each domain, identifies current challenges, and proposes future research directions, emphasizing the potential of AI methods in transforming health monitoring and patient care.

Evaluation of a permanent SHM system performance in detecting damage scenarios considering runnability thresholds

Due to an increasing number of bridges approaching the end of their design lives, there is a growing interest by the infrastructure managers on monitoring systems able to provide information on the service capability of structures. Focusing, in particular, on railway bridges, serviceability is related to both structural serviceability and runnability, where the first is related to the structural capability of the bridge, while the second is related to the constraints on rail geometry. In this work the authors present an investigation of the capability of a permanent monitoring system to detect the presence of damages that would lead to an exceedance of the structural threshold values imposed by runnability norms. The target structure is a double-span Warren truss railway bridge, located in Italy, designed in 1946 and currently instrumented with a permanent monitoring system. The latter performs dynamic, quasi-static and static measurements, with sensors ranging from velocimeters to end displacement transducers and clinometers. Thanks to a FE model of the actual structure, a set of damage scenarios can be simulated, defining the damage entities that lead to the exceedance of thresholds imposed by norms in terms of runability assessment. As a result, the installed sensors mesh was found to distinguish such critical structural conditions as well as lower entity damage scenarios. The paper discusses the capability of different sensor configurations and monitoring strategies (“dynamic”, “static”, etc) to detect such damage scenarios, in terms both of “early warning” capability and of minimum time required to detect the anomaly. The same approach can be extended to the analysis with respect to structural serviceability limits.

Construction and performance evaluation of polyguluronic acid polysaccharides-based drug delivery systems

Polysaccharides have garnered significant attention as potential nanoparticle carriers for targeted tumor therapy due to their excellent biodegradability and biocompatibility. Polyguluronic acid (PG) is a homogeneous acidic polysaccharide fragment derived from alginate, which is found in brown algae, possesses excellent bioactivities, unique properties. This study explored the immunomodulatory activity of PG and developed PG-based nanogels through modified disulfide bonds and Ca2+ dual crosslinking. We characterized their structure, assessed their drug-loading and release properties, and ultimately validated both the safety of the nanocarrier and the in vitro anti-tumor efficacy of the encapsulated drug. Results indicated that PG significantly enhanced the proliferative activity and phagocytosis of RAW264.7 cells while promoting reactive oxygen species (ROS) production and cytokine secretion. The study identified TLR4 as the primary receptor for PG recognition in RAW264.7 cells. Furthermore, PG-based drug-carrying nanogels were prepared, exhibiting uniform sizes of about 184 nm and demonstrating exceptional encapsulation efficiency (82.15 ± 0.82 %) and drug loading capacity (8.12 ± 0.08 %). In vitro release experiments showed that these nanogels could responsively release drugs under conditions of high glutathione (GSH) reduction, facilitating drug accumulation at tumor sites and enhancing therapeutic efficacy. This research not only expands the application of PG in drug delivery systems but also provides valuable insights into leveraging natural immunomodulatory polysaccharides as carriers for targeted drug delivery.

Performance evaluation of the SMART passive safety injection system against the SBLOCA scenario with the SMART-ITL facility

A set of system performance tests has been performed and the thermal-hydraulic behaviors were investigated for the passive safety injection system (PSIS) of the SMART design. Major thermal-hydraulic characteristics of core cooling in reactor coolant system and safety injection (SI) in PSIS were investigated using the SMART-ITL. The parametric effects of break size, break location and train number on the PSIS performance were discussed with the relevant SMART-ITL data. Compared with the 2.0 inch SI line break test, the 0.4 inch SI line break test has a milder change of system parameters. The pressure is reduced more quickly, the decrease of water level is slower and the break mass flow rate is higher during the pressurizer safety valve line break than during the SI line break. Major thermal-hydraulic parameters were compared among single, two and full train operation of the PSIS focusing on the effect of train number. It was shown that multiple trains of CMT and SIT were operated independently and the reactor vessel (RV) inventory increased proportionally with the addition of each train. Sufficient SI water was injected into the RV in a passive manner to cool down the reactor core efficiently during the full train test.