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This paper aims to investigate the performance and working fluids screening for an ejector refrigeration cycle (ERC) activated by solar energy. Several common and new hydrofluorocarbons, hydrocarbons, hydrofluoroolefins and hydrofluoroethers are proposed as refrigerants for the ERC to determine the most appropriate one.

The ejector performance is characterized by the ejector area ratio (EAR) and entrainment ratio (ω), while the cycle performance is described by the coefficient of performance (COP). The influences of many working parameters like the evaporator, condenser and generator temperatures on the ejector and cycle performances are investigated for all candidates as well.

The results indicate that the best ejector and cycle performances are attained with the highest critical temperature dry refrigerant, i.e. R601 under all studied working conditions. From the perspective of energy efficiency and environmental issues, R601 can be considered the most appropriate working fluid amongst all candidates. However, extra attention should be considered against its flammability. The maximum COP, the corresponding ω and the necessary EAR using R601 are 0.743, 1.02 and 15.5, respectively, with 25 ºC condenser temperature and the typical values for the rest operating conditions.

Many common and new hydrofluorocarbons, hydrocarbons, hydrofluoroolefins and hydrofluoroethers are suggested as working fluids for the ERC to determine the most appropriate one. The mixing process inside the ejector constant-area section is assumed constant-pressure process.

Property management companies in residential properties are increasingly using ICT and specific property management software applications to conduct daily property management tasks. However, the benefits of using specific software applications and how it can add value to property management companies are largely unexplored. The present study examines the impact of property management mobile applications usage features on strata property residents' satisfaction in Kuala Lumpur.

A total of 205 residents from 3 strata residential buildings in Kuala Lumpur using property management applications were surveyed. The study employed structural equation modelling using SPSS Amos software.

The findings suggest that visitor management and security management via software applications positively influence the residents' satisfaction. However, facility management via software application was found to be negatively affecting residents' satisfaction.

The study highlighted the benefit of property managers adopting property management software to achieve increased residents' satisfaction in strata residential properties.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

The purpose of this study is to assess the performance of fuel blends containing ethanol and gasoline in spark ignition engines. The aim is to explore alternative fuels that can enhance performance while minimizing or eliminating adverse environmental impacts, particularly in the context of limited fossil fuel availability and the need for sustainable alternatives.

The authors used the Ricardo Wave software to evaluate the performance of fuel blends with varying ethanol content (represented as E0, E10, E25, E40, E55, E70, E85 and E100) in comparison to gasoline. The assessment involved different composition percentages and was conducted at various engine speeds (1,500, 3,000, 4,500 and 6,000 rpm). This methodology aims to provide a comprehensive understanding of how different ethanol-gasoline blends perform under different conditions.

The study found that, across all fuel blends, the highest brake power (BP) and the highest brake-specific fuel consumption (BSFC) were observed at 6,000 rpm. Additionally, it was noted that the presence of ethanol in gasoline fuel blends has the potential to increase both the BP and BSFC. These findings suggest that ethanol can positively impact the performance of spark-ignition engines, highlighting its potential as an alternative fuel.

This research contributes to the ongoing efforts in the automotive industry to find sustainable alternative fuels. The use of Ricardo Wave software for performance assessment and the comprehensive exploration of various ethanol-gasoline blends at different engine speeds add to the originality of the study. The emphasis on the potential of ethanol to enhance engine performance provides valuable insights for motor vehicle manufacturers and researchers working on alternative fuel solutions.

The purpose of this paper is to find a practical and effective way to test wearing product lifetime with two SCARA robots.

The paper designs a mathematical model to simulate human motion, calculate the coordinate trajectory, then implement with two SCARA robots.

The two-robot testing platform for wrist band is an effective and precise simulation method and is feasible to deploy in mass production.

The paper introduces a way for apply robots in wearing product lifetime testing which is novel, practical and effective.

The demand for energy is increasing massively due to urbanization and industrialization. Due to the massive usage of diesel engines in the transportation sector, global warming is increasing rapidly. The purpose of this paper is to use hydrogen as the potential alternative for diesel engine.

A series of tests conducted in the twin cylinder four stroke diesel engine at various engine speeds. In addition to the hydrogen, the ultrasonication is applied to add the nanoparticles to the neat diesel. The role of nanoparticles on engine performance is effective owing to its physicochemical properties. Here, neat diesel mixed 30% of biodiesel along with the hydrogen at the concentration of 10%, 20% and 30% and 50 ppm of graphite oxide to form the blends DNH10, DNH20 and DNH30.

Inclusion of both hydrogen and nanoparticles increases the brake power and brake thermal efficiency (BTE) of the engine with relatively less fuel consumption. Compared to all blends, the maximum BTE of 33.3% has been reported by 30% hydrogen-based fuel. On the contrary, the production of the pollutants also reduces as the hydrogen concentration increases.

Majority of the pollutants such as carbon monoxide, carbon dioxide and hydrocarbon were dropped massively compared to diesel. On the contrary, there is no reduction in nitrogen of oxides (NOx). Highest production of NOx was witnessed for 30% hydrogen fuel due to the premixed combustion phase and cylinder temperatures.

The study aims to determine the the optimal value of output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The performance parameters like brake thermal efficiency (BTE) and brake specific energy consumption (BSEC), whereas CO emission, HC emission, CO₂ emission, NO_x emission, exhaust gas temperature (EGT) and opacity are the emission parameters measured during the test. Tests are conducted for 2, 6 and 10 kg of load, 16.5 and 17.5 of CR.

In this investigation, the first engine was fueled with 100% diesel and 100% Calophyllum inophyllum oil in single-fuel mode. Then Calophyllum inophyllum oil with producer gas was fed to the engine. Calophyllum inophyllum oil offers lower BTE, CO and HC emissions, opacity and higher EGT, BSEC, CO₂ emission and NO_x emissions compared to diesel fuel in both fuel modes of operation observed. The performance optimization using the Taguchi approach is carried out to determine the optimal input parameters for maximum performance and minimum emissions for the test engine. The optimized value of the input parameters is then fed into the prediction techniques, such as the artificial neural network (ANN).

From multiple response optimization, the minimum emissions of 0.58% of CO, 42% of HC, 191 ppm NO_x and maximum BTE of 21.56% for 16.5 CR, 10 kg load and dual fuel mode of operation are determined. Based on generated errors, the ANN is also ranked for precision. The proposed ANN model provides better prediction with minimum experimental data sets. The values of the R² correlation coefficient are 1, 0.95552, 0.94367 and 0.97789 for training, validation, testing and all, respectively. The said biodiesel may be used as a substitute for conventional diesel fuel.

The blend of Calophyllum inophyllum oil-producer gas is used to run the diesel engine. Performance and emission analysis has been carried out, compared, optimized and validated.