Performance Evaluation Of System Research Articles

Thermodynamic and exergo-economic analyses and multi-objective optimization of an innovative and efficient geothermal-assisted power and hydrogen cogeneration system

This paper presents an efficient integration of a flash-binary geothermal system with a double-pressure Kalina cycle and a proton exchange membrane electrolyzer unit. The main objective is to generate power and hydrogen simultaneously. A comprehensive thermodynamic analysis is conducted, encompassing mass, energy, and exergy assessments, along with an exergo-economic approach, to thoroughly evaluate system performance. The operation of the system is examined under varying conditions, and trends in the assessment indexes are predicted accordingly. The designed system achieves notable results, producing 1018 kW of net power and 0.1119 kg/h of hydrogen. The thermal and exergetic efficiencies are found to be 14.34 % and 45.59 %, respectively, based on the thermodynamic approach. From an economic perspective, the payback period is estimated to be 2.51 years, while the sum unit cost of products is calculated at 8.94 $/GJ. Furthermore, a detailed exergy analysis highlights that the Kalina cycle's condenser contributes the most to exergy destruction, accounting for approximately 129.6 kW. Through a parametric study, it is revealed that the pressure of the production well significantly influences the performance indicators, and the price of electricity sold has a substantial impact on the system's payback period and net present value. Moreover, the application of a multi-objective optimization strategy leads to the identification of the system's optimal state through an exergo-economic assessment. This optimization yields an exergy efficiency of around 49.75 % and a sum unit cost of products of 8.56 $/GJ.

A performance evaluation system for product eco-design in the fashion supply chain

With the increasing environmental awareness of citizens, sustainable fashion has become a hot topic in industry, academia, and society. The importance of product eco-design (ED) in ensuring the sustainability of organizations and supply chains cannot be overstated. This paper aims to establish an eco-design performance evaluation system and identify the most effective management mechanism. To achieve this goal, a linked two-stage network Data Envelopment Analysis (DEA) model is developed. This model has a well-defined internal structure and potential causal relationships between variables; and the two stages are Internal and Supplier Management (ISM) and Openness and Collaboration (OC). We analyze stage and overall efficiencies using proactive, reactive, and simultaneous approaches. Additionally, we explore the convergence characteristics of the industry's ED efficiency from 2015 to 2018. The results show that the overall ED efficiency of fashion enterprises is significant when considering the interrelatedness of subsystems. However, there is disharmony between the two stages. As the proactive approach, ISM is the optimal strategy to maximize ED efficiency. On the other hand, OC is critical to eco-design performance. This paper contributes to the existing literature by developing an innovative DEA analytical framework for evaluating eco-design performance. It also identifies the most eco-efficient way to achieve better environmental performances, which allows decision-makers to better allocate their design efforts and improve both short- and long-term corporate sustainability.

Research on performance test and evaluation of thermal management system of power battery module under harsh conditions

Under harsh conditions, the battery module (BM) used for Ev’s power system has issues of local overheating, continuous high temperature, and spontaneous combustion causing thermal accidents. This problem is directly related to the safety of life and property of drivers and passengers. What’s more, it also seriously restricts the high-quality development and promotion of Evs. To solve the limitations and drawbacks of the BM. this paper designs the thermal management structure with TiO2 nanofluids closed loop pulsating heat pipe (TiO2-CLPHP) as the key component and constructs the thermal management system with TiO2-CLPHP (TiO2-CLPHP TMS). On the basis, the temperature optimal thermal management strategy (TOS) and energy consumption optimal thermal management strategy (ECOS) is proposed. To investigate the performance response of TiO2-CLPHP TMS, the performance test of TiO2-CLPHP TMS is carried out. The results show that in terms of thermal management performance, the TiO2-CLPHP TMS with TOS and ECOS (TOS-TiO2-CLPHP TMS, ECOS-TiO2-CLPHP TMS) can effectively suppress the highest temperature, temperature rise and improve temperature uniformity of the PM. Of these, the minimum improvement rates of TOS-TiO2-CLPHP TMS can reach 29.41%, 78.37%, 65.88%, 58.82%, and 64.95%. The minimum improvement rates of ECOS-TiO2-CLPHP TMS can reach 27.24%, 72.65%, 64.71%, 55.88%, and 68.04%, respectively. In terms of the thermal management economy, compared with TOS-TiO2-CLPHP TMS, ECOS-TiO2-CLPHP TMS has lower energy consumption. The efficiency values of the ECOS-TiO2-CLPHP TMS are not less than 87.72%. It can be concluded that the proposed TiO2-CLPHP TMS has excellent thermal management performance. The ECOS-TiO2-CLPHP TMS can maximize the dual requirements of the thermal management performance and thermal management economy. This study innovatively proposed a thermal management method for nanofluids PHP used in BM. Compared with previous studies, the proposed TiO2-CLPHP TMS reduced the temperature difference from the traditional 5.00 °C to less than 3.40 °C, greatly improving the temperature uniformity of the BM. The completion of this research provides a new idea of battery thermal management based on metal oxide nanofluids PHP, and the constructed performance evaluation method provides a referral scheme for the performance test and evaluation of thermal management technology.

Modeling and thermal economy analysis of the coupled system of compressed steam energy storage and Rankine cycle in thermal power plant

To facilitate the integration of greater amounts of renewable energy into the power grid, it is crucial to enhance the peak shaving capabilities of conventional thermal power units. This paper proposes a novel system that combines compressed steam energy storage with the Rankine cycle of a thermal power plant (referred to as the coupling system), and focuses on modeling a 200 MW thermal power unit. The performance evaluation and parameter selection of the coupling system are conducted through comprehensive energy analysis, exergy analysis, and economic analysis. The results indicate that the energy storage cycle in the coupled system can prevent boilers and turbines in the Rankine cycle from operating at extremely low loads during deep peak shaving. Specifically, when the boiler and steam turbine operate at 66.45 % of their design load, the external power of the coupling system can be reduced to 30 % of the rated power. This results in a reduction of coal consumption by 63.42 g/W * h compared to direct peak shaving of the original thermal power unit, and an improvement in exergy efficiency by 2.99 %. In this study, a 1300 m3 energy storage circulating water storage tank capacity is used as an example, and it is found that the 200 MW unit can achieve continuous deep peak regulation operation for 8.58 h. The study also reveals that a 1 % increase in the isentropic efficiency of energy storage cycle compressors can lead to a reduction in coal consumption by 2.4 g/kW*h. Moreover, economic analysis suggests that maintaining a compressor efficiency of 86 %, utilizing 7 compression stages, and prioritizing the effectiveness of the heat exchanger are optimal for maximizing the system's revenue. These factors collectively result in a shorter payback period for the coupling system and an overall increase in total income.

A computational sustainable approach for energy storage systems performance evaluation based on spherical-fuzzy MCDM with considering uncertainty

Incorporating energy storage systems (ESSs) can mitigate the intermittency of renewable energy sources. There are a variety of ESSs for renewable energy with vastly different characteristics. The problem of diversity of characteristics in selecting the most appropriate ESS can be approached as a multi-criteria decision-making (MCDM) problem. This research evaluates sustainable ESSs through a case study in Egypt. A sustainable computational approach is presented through which experts can use verbal expressions to express their opinions in determining the priorities of the dimensions that affect the selection of ESSs. Determining the appropriate energy storage system requires consideration of several main dimensions such as the technology dimension, environmental dimension, economic dimension, and social-political dimension and, in addition to the sub-indicators. Hence, this research applies a hybrid MCDM approach that deals with different indicators and characteristics. Also, uncertainty in applying the proposed approach was dealt with by a spherical fuzzy (SF) environment and by using the spherical fuzzy numbers (SFNs). At first, the SF analytical hierarchy process (SF-AHP) method was used to assess the priorities of the four main dimensions and their sub-indicators. Then, the SF mixed aggregation by comprehensive normalization technique (SF-MACONT) was applied to evaluate and rank the ESSs selected for analysis through research. An illustrative case study was presented that included seven ESSs out of the eighteen systems listed in the research to confirm the feasibility of the developed approach. Sensitivity analysis was carried out by changing some parameters like λ, μ, δ, and ϑ based on the SF-MACONT method and changing the weights of some main dimensions. A comparative analysis with some MCDM approaches was conducted to show the advantages of the developed approach through its flexibility and built-in parameters. The findings show that the technology dimension is the most influential in choosing a sustainable ESS, while the economic dimension is the least influential. Also, the results of the evaluation and ranking of the seven selected ESSs indicate that the "Pumped Hydro" system is the most suitable system for energy storage in Egypt.

Assessment of annual performance of quonset GiPVT system combined with an earth-air heat exchanger (EAHE) for hot and dry climatic conditions

Annual performance of a Quonset-shaped GiPVT system combined with an earth air heat exchanger (EAHE) has been evaluated for hot and dry climatic conditions. A periodic thermal model for the GiPVT system has been developed in terms of input climatic and design parameters by employing the energy balance equations of the greenhouse system. The present model is used to calculate the effective cooling and heating capacity of the EAHE, which is further utilized to determine the optimum operating hours of EAHE for different months of the year. Furthermore, the electrical energy of the GiPVT system and the thermal energy of EAHE are calculated, enabling a comprehensive performance evaluation of the greenhouse system. Results show that the EAHE increases the greenhouse air temperature by 8 °C on the coldest day and decreases the greenhouse air temperature by 21 °C on the hottest day of the year. EAHE has a lower potential for heating than cooling because of the hot and dry climatic conditions. Moreover, the system generates 17.6 kWh and 29.22 kWh of electrical energy on an extremely cold and hot day, respectively making the system self-sustainable. The EAHE significantly reduced TLL and DF values, which gives thermal comfort to the greenhouse.

Performance Evaluation of Lecturers in Applied Universities in Shaanxi Province: Systematic Literature Review

This study addresses the development of lecturers’ performance evaluation system specifically designed for applied universities. It analyzes the existing lecturer’s performance evaluation system in applied universities in Shaanxi Province and highlights several problems based on facts. The current lecturer performance evaluation system in applied universities is very similar to the system used in research universities, and it is found not suitable for the special requirements of applied universities. The indicators used in the performance evaluation system suffer from problems such as excessive quantification, imperfection, rigidity, and dogmas that lack scientific rigor in practical application. Through the literature, the study found that there are not many researches on applied universities. However, the existing research lacks the following three parts. First, there is a lack of performance evaluation policies for applied university lecturers. Second, the performance evaluation indicators are not in line with the talent training goal of applied university. Third, as a feature of application-oriented undergraduate social service research is also very few. Based on this, the main objective of this study is to develop a performance evaluation system for applied university lecturers, taking into account the educational objectives and characteristics of applied university. In this study, semi-structured interviews are used to collect data from research participants to understand the existing performance evaluation system of applied university lecturers from different perspectives and how they think it can be improved. Then form an applied university lecturer performance evaluation system.

Enhancing well-being in modern education: A comprehensive eHealth proposal for managing stress and anxiety based on machine learning

In the evolving education landscape, institutions are transitioning to a hybrid model encompassing physical and virtual classes. In this scenario, as working hours and exhausting routines increase, individuals accumulate psychological and physical challenges over time. This change requires students and educators to adjust to changes in teaching and learning routines, leading to moments of stress and anxiety. Cultivating self-awareness about unhealthy habits emerges as a pragmatic strategy to address this issue. In this work, a comprehensive eHealth proposal is developed to provide individuals with pertinent health information, assisting educational agents (students and teachers) in identifying and managing these stressful instances during their daily activities. This proposal acquires, processes, and disseminates vital sign data using IoT devices, supported by a Fog Computing architecture for scalability and adaptability. IoT plays a pivotal role in this eHealth proposal, facilitating the seamless collection and transmission of real-time data from various devices. Connected wearables and sensors enable the continuous monitoring of vital signs, enhancing the accuracy and responsiveness of the system. Heart rate data from educational agents were collected for implementation, allowing the evaluation of system performance. Machine learning models were leveraged to discern behavioral profiles and predict possible irregularities in vital signs. The results confirm the system’s ability to perform its intended functions, giving users quick and accurate insights into their evolving behavioral patterns. Integrating these research perspectives underscores the importance of adaptive systems in navigating the challenges of modern education environments. The incorporation of IoT technology not only enhances data collection but also opens avenues for real-time interventions and personalized feedback, ultimately contributing to a more proactive approach in addressing health-related concerns within the educational context.

An evolutionary game study on the collaborative governance of environmental pollution: from the perspective of regulatory capture.

Local governments have been captured by enterprises and, thus, have relaxed environmental regulations. This phenomenon has occurred repeatedly and has resulted in serious environmental pollution, posing an enormous threat to public health. To solve this problem, this study introduces central environmental protection inspection and media supervision and considers the economic preferences and environmental preferences of local governments. A four-party evolutionary game model composed of enterprises, local governments, the central government and the media is constructed, and the equilibrium solution of four-party replicator dynamics equations is obtained. The influence of relevant parameters on the choice of strategies of the four main bodies is simulated by using MATLAB software to explore the paths and measures for overcoming regulatory capture and to further improve the modern environmental governance system. The results show the following: First, local governments are easily captured by large enterprises. Second, the central government can improve the environmental behavior of local governments by reducing their economic preferences and strengthening punishment. Third, compared to the penalties imposed by the central government, those imposed by local governments have a more significant impact on the environmental behaviors of enterprises. Fourth, compared to the use of an environmental protection tax policy or a tax relief policy alone, the combination of the two has a more significant impact on the environmental behaviors of enterprises. Fifth, central environmental protection inspection and media supervision can improve the environmental behaviors of both local governments and enterprises, and the effect of media supervision is better than that of central environmental protection inspection. This study recommends improving the performance evaluation system for local governments to coordinate economic development and environmental protection, ensuring that local governments assume the main responsibility, using a combination of incentive and constraint policies for enterprises, and increasing the environmental protection inspection and media supervision of local governments and enterprises to resolve the dilemma of regulatory capture in environmental pollution through the simultaneous enhancement of the environmental behavior of local governments and enterprises.

Performance evaluation of a zoom iris recognition system using Q-type aspherical design.

Based on a Q-type aspheric surface, a wide working distance zoom iris recognition lens is designed. The lens has an aperture of 2.0 and a working distance of 200-1200mm. The design results show that the modulation transfer function values of each field at the cutoff frequency are greater than 0.3 and the optical distortion is less than 1.1%. With the same structure and parameters, the performance of two optical systems using Q-type aspherical and even power series aspherical are analyzed. The Q-type non-spherical aberration correction is better.

Performance investigation and evaluation of a low-temperature solar thermal energy storage system under dynamic weather conditions

Designed and operational parameters matter greatly in how successful an energy storage system performs. However, a current challenge in matching suitable these parameters lies in the poor understanding of such systems’ performance under dynamic weather conditions. In this paper, we investigated a phase change material (PCM) storage unit that is particularly aimed for poor-solar areas, and connected the unit to a flat plate solar collector to establish a complete solar thermal energy storage system (STESS). To optimize the system performance, different grades of solar radiation and outdoor ambient temperatures are introduced, and the effects of heat transfer fluid (HTF) flow rates and solar collecting areas are investigated numerically through multiple performance evaluation parameters. The results indicate that the solar collecting area has a significant effect on the performance of the STESS compared to that of the water flow rate. And different collecting areas of 1 m2, 1.5 m2, and 3 m2 with an optimal water flow rate of 0.06 m3/h are matched to different average daily solar radiation of 203.4 W/m2, 155.2 W/m2, 92.7 W/m2, respectively. Further for the heat release process, different heat release efficiencies from 88.32 % to 97.12 % with different energy consumption of the fan from 0.003 kWh to 0.063 kWh are obtained when the air flow rate is increased from 30 m3/h to 90 m3/h. One of the air flow rates of 60 m3/h is superior for the STESS considering higher heat release efficiency and lower energy consumption of the fan. The findings of this paper will contribute to optimizing the performance of a STESS in practical applications.

Design and performance evaluation of vehicular visible light communication system under different weather conditions and system parameters

Design and performance evaluation of vehicular visible light communication system under different weather conditions and system parameters

Performance evaluation of UFMC-based VLC systems using a modified SLM technique

Performance evaluation of UFMC-based VLC systems using a modified SLM technique

Evaluation of a Blockchain-Based Prescription System and Data Source for National Research and Development

In the Philippines, healthcare providers, government agencies, and research institutions use data from patient prescriptions to generate reports for health planning and decision-making. However, current e-prescription systems have vulnerabilities, including erroneous information, hacking attempts, a single point of failure, and medical fraud. In addition to affecting the quality of data reporting, these issues violate a patient’s rights to data privacy. One promising solution is a blockchain-based prescription system. Blockchain’s immutable ledger accurately traces medical fraud and erroneous information, while its decentralized nature reduces the impact of failures. Performance is an important consideration, as healthcare systems need to be scalable and time-sensitive. This study aims to understand the performance and security of blockchain-based prescription systems. It focuses on evaluating system performance and scalability when using different encryption algorithms. The study found that using the most secure technology had only a small performance impact for all prototype features except key generation and report viewing. In addition, the results suggest that the proposed system’s scalability is sufficient to service the entire Philippines. This knowledge will help improve prescription systems to protect patients’ rights and improve report reliability.

Bibliometric and visualization analysis of the application of inorganic nanomaterials to autoimmune diseases.

Objective: To conduct bibliometric analysis of the application of inorganic nanomaterials to autoimmune diseases to characterize current research trends and to visualize past and emerging trends in this field in the past 15 years. Methods: The evolution and thematic trends of the application of inorganic nanomaterials to autoimmune diseases from January 1, 1985, to March 15, 2024, were analyzed by bibliometric analysis of data retrieved and extracted from the Web of Science Core Collection (WoSCC) database. A total of 734 relevant reports in the literature were evaluated according to specific characteristics such as year of publication, journal, institution, country/region, references, and keywords. VOSviewer was used to build co-authorship analysis, co-occurrence analysis, co-citation analysis, and network visualization. Some important subtopics identified by bibliometric characterization are further discussed and reviewed. Result: From 2009 to 2024, annual publications worldwide increased from 11 to 95, an increase of 764%. ACS Nano published the most papers (14) with the most citations (1372). China (230 papers, 4922 citations) and the Chinese Academy of Sciences (36 papers, 718 citations) are the most productive and influential country and institution, respectively. The first 100 keywords were co-clustered to form four clusters: (1) the application of inorganic nanomaterials in drug delivery, (2) the application of inorganic nano-biosensing to autoimmune diseases, (3) the use of inorganic nanomaterials for imaging applied to autoimmune diseases, and (4) the application of inorganic nanomaterials in the treatment of autoimmune diseases. Combination therapy, microvesicles, photothermal therapy (PTT), targeting, diagnostics, transdermal, microneedling, silver nanoparticles, psoriasis, and inflammatory cytokines are the latest high-frequency keywords, marking the emerging frontier of inorganic nanomaterials in the field of autoimmune diseases. Sub-topics were further discussed to help researchers determine the scope of research topics and plan research directions. Conclusion: Over the past 39 years, the application of inorganic nanotechnology to the field of autoimmune diseases shows extensive cooperation between countries and institutions, showing a continuous increase in the number of reports in the literature, and has clinical translation prospects. Future research should further improve the safety of inorganic nanomaterials, clarify the mechanism of action of nanomaterials, establish a standardized nanomaterial preparation and performance evaluation system, and ultimately achieve the goal of early detection and precise treatment of autoimmune diseases.

Research on Piano Curriculum Education and Its Performance Ecosystem Based on Network Flow Optimization

Abstract This paper investigates music education, where an efficient and accurate performance evaluation system in the piano teaching and performance ecosystem is increasingly becoming an essential tool for improving teaching quality and performance level. The objective evaluation of students’ performance skills can be achieved by carefully analyzing piano performances using the network flow optimization technique. This technique optimizes the performance evaluation system’s audio recognition ability by analyzing the piano audio signal and solving the multi-constraint nonlinear optimization problem in a limited time domain. This paper establishes a network flow optimization model, applies the multi-constraint nonlinear optimization technique, and combines the non-negative matrix decomposition and dynamic time regularization algorithm to analyze the piano performance for experiments. After optimization processing, hundreds of piano audio samples were collected, and the audio recognition accuracy was improved by 20%. By optimizing and processing the audio signals from the network stream, the evaluation system could detect polyphony more accurately and track the musical score effectively, improving accuracy and efficiency. Using the non-negative matrix decomposition algorithm, the accuracy of detecting polyphony can reach 85%, while the dynamic temporal regularization algorithm can match the position of the musical score with 95% accuracy. The accuracy of piano performance evaluation is optimized by this network flow optimization method, providing new technical means for music education, and promoting the quality of teaching and performance.

Green SCM Performance Evaluation of Petroleum Exploration Companies using Green SCOR Model

This research aims to create a green SCM performance evaluation system using the Green SCOR model approach. The Green SCOR performance evaluation system begins by determining three process hierarchies, namely levels 1, 2, and 3. Level 1 includes the general process of plan, source, make, deliver and return. Level 2 includes the dimensions of reliability, responsiveness, flexibility, cost, and asset. Level 3 is related to the level of the company’s process elements. The results of expert validation obtained 18 Green SCM key performance indicators (KPIs) that correspond to the company’s supply chain operations. In the next step, the experts conducted a weighting process for levels 1, 2, and 3 using the Analytical Hierarchy Process (AHP). Based on the results of the performance measurement on each indicator, the total score obtained is 85, which means good. There are 4 KPIs that fall into the poor category, namely MA2 (total water usage) with a performance value of 13, SA1 (percentage of turnover ratio) with a performance value of 18, MR2 (level of hazardous materials produced) with a performance value of 18, and DA1 (Percentage of vehicle fuel for transportation and material handling) with a performance value of 35.

Motivation and Job Performance among Nurses at Public Hospital in Bangladesh

Background: The performance of nurses plays a crucial role in achieving positive outcomes for healthcare organizations. Performance is directly related to motivation; as higher motivation leads to better performance. Motivated nurses tend to have a strong sense of organizational belonging, resulting in improved work quality, increased productivity, and enhanced job performance. Objective: The study aims to examine the relationship between motivation and job performance among nurses at public hospital in Bangladesh. Methods: A descriptive correlational study was conducted at Shaheed Suhrawardy Medical College Hospital. A total of 112 nurses were selected using a convenience sampling technique. Data were collected from February 2023 to March 2023 using a structured questionnaire. The instrument consisted of three parts: Part I, the Socio-Demographic Questionnaire (SCQ-10); Part II, the Nurses' Motivation Measurement Questionnaire (NMMQ-32); and Part III, the Nursing Job Performance Related Questionnaire (NJPQ-52). Descriptive and inferential statistics were used to analyze the data. Results: The average age of the participants was 37.3 years (SD = 57.102). Among them, 94.6% were female, 97.3% were married, and 75% identified themselves as Muslims. The mean score of motivation was 3.43 (SD = 0.660), indicating that nurses were motivated. The mean score of job performance was 2.78 (SD = 0.640), indicating that nurses had good job performance. The results also showed that more than half of the nurses expressed dissatisfaction with their remuneration. There was a significant positive correlation between motivation and job performance (r = 0.725, p = 0.000). Conclusion: The present study found that motivation and job performance strongly correlate with each other. Although the participants were motivated and had a good performance, there is still a lack of a fair performance evaluation system and proper resources for better job performance. Based on these findings, the researchers recommended that further study be conducted with a larger sample size and in multiple healthcare settings to allow the generalizability of the findings and provide a more diverse and comprehensive understanding of the relationship between motivation and job performance.

Modeling, Performance Evaluation and Optimization of (s, Q) Retrial Inventory System with partial backlogging demands: A GSPN Approach

Modeling, Performance Evaluation and Optimization of (s, Q) Retrial Inventory System with partial backlogging demands: A GSPN Approach

Performance Evaluation of Cryogenic Liquefaction System Precooled by Combined Vapour Compression-Absorption Refrigeration System

Liquefaction is a high-energy-consuming process. One of the most efficient methods of lowering energy consumption use is to run a precooled cycle with a cascade refrigeration system. When compared with the vapour compression system, the merit of adopting a cascade system is that it consumes very less energy. Another advantage is that non-traditional energy sources such as geothermal and solar might be used to power these cycles. This paper examines a precooled Linde Hampson-liquefaction system using a double-stage cascade vapour compression-absorption refrigeration cycle that consists of an absorption system at the high-temperature stage and a compression system at the low-temperature stage to generate cooling at a small temperatures by using various refrigerants in the absorption and compression sections. The system's performance was evaluated by employing various combinations of natural refrigerants in the absorption section. Liquefaction of Nitrogen is carried out using a precooled Linde Hampson system and precooled liquefaction using a cascade refrigeration cycle. Nitrogen was liquefied using two methods in the current study. A thorough examination of the precooled system was conducted, and it was discovered that by employing a cascade refrigeration cycle, the input required per unit mass of gas liquefied is decreased. The performance metrics of the liquefaction system, such as Figure of Merit (FOM) and Liquid Yield, were discovered for both scenarios, and it is concluded that the usage of a cascade refrigeration system has more efficiency and consumes less energy than a system without an absorption chiller. The use of a precooled Linde Hampson system with cascade cycles improved liquefaction characteristics by 5-7%.