bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thermal performance of the photovoltaic module with evaporative cooling ventilated cavity
Authors: Liu Y H , Yan W C , Yang C J , Zhang Y , He C W , Cui X , Jin L W 
Published: July 2024

Abstract
Energy is indispensable in modern life, and solar photovoltaic technology stands out for its substantial advantages. However, the current conversion rate remains suboptimal, ranging from 15% to 20%. Compounding this, a portion of solar energy undergoes conversion into thermal energy, resulting in an elevation of the PV (photovoltaic) module’s temperature and a subsequent reduction in electricity generation efficiency. In response to this challenge, a solution was conceived—a design featuring an evaporative cooling ventilated cavity crafted to alleviate the operating temperature of the photovoltaic module. This innovative system integrates a photovoltaic facade with an evaporative cooling ventilation cavity, encompassing crucial components such as solar photovoltaic panels, an evaporative cooling layer, and a ventilated cavity equipped with thermal regulation. An experimental system was meticulously developed. The results illuminate the system’s efficacy in temperature reduction: approximately 5°C for the PV back sheet, 5°C for the cavity back sheet, and 5.2°C inside the cavity. Furthermore, the system achieves a noteworthy average operating temperature reduction of about 14.1%, 20.2%, and 20.4%, respectively. These findings underscore the substantial impact of the evaporative cooling system on regulating and enhancing the thermal performance of PV modules.
The determination of elements influencing successful collaboration factors in preventing oil spills during bunkering at port
Authors: Ishak I C , Charles I , Ramli M K , Arof A M , Salleh H S , Isha A S N 
Published: July 2024

Abstract
This study is concerned with the factors that could concern the successful collaboration in preventing oil spills during bunkering operations. This study encompasses individual staff at port and bunkering companies in Sabah, Malaysia. The oil spill incidents from bunkering activities are possible to occur while the ships are moving. The primary causes of bunker activities that could lead to the oil spill are overflow, leak incidents, inadequate planning, and human error. This study aims to validate the factors of successful collaboration toward preventing oil spills during bunkering operations. This study utilized a Delphi questionnaire survey distributed to respondents with working experiences between two years and more than 10 years of working experience. The data has been accumulated from the related departments within the individual staff at Jabatan Pelabuhan dan Dermaga Sabah (JPDS) and Kota Kinabalu Port. This study applied an online Delphi questionnaire survey from the required purposive sampling. The Delphi questionnaire survey assembles information about respondents and the importance of and factors influencing successful collaboration by applying Likert scale point of 5 ranging from not important to extremely important. This study has included 59 respondents from JPDS and related bunkering companies and bunkering operators. The data have been analysed using SPSS analysis tools such as Cronbach alpha and Correlation analysis. The result revealed that the Cronbach alpha value shows a high value of 0.960. Meanwhile, the correlation coefficient (r) shows at 0.775. It has shown a positive and strong relationship between the importance of successful collaboration and the factors influencing successful collaboration to prevent oil spills during bunkering. The recommendation of this study could facilitate other port authorities to collaborate or coordinate with other sectors or companies in bunkering operations to gain a successful collaboration in preventing oil spills during bunkering activities. It is also anticipated to contribute to the deficiency of literature on the determination of elements influencing successful collaboration factors in preventing oil spills during bunkering at port.
Extraction of anthocyanin from mangosteen rind using ionic liquids and deep eutectic solvents
Authors: Tan Z L , Cheok C Y 
Published: July 2024

Abstract
Anthocyanins is natural pigments found in many plants that not only impart colours but also have potential health benefits and used as natural colorant in food processing industries. Mangosteen rind, although rich in anthocyanins, is normally disposed of as waste after consuming the delicate pulp. Anthocyanins is stored within the membrane cell wall inside the mangosteen rind, and it is usually recovered from the rind using solvent. Hence, this study investigated potential alternative green solvents, e.g., ionic liquids and deep eutectic solvents in extracting anthocyanins from mangosteen rind. This study is designed in conjunction with Sustainable Development Goals (SDGs) outlined by the United Nations, particularly SDG3 where good health and well-being equalities are emphasized and SDG12 in which efficient management of natural resource is addressed. Anthocyanins yield was determined using pH-differential method and result was expressed in milligram of cyanidin-3-glucoside per gram of mangosteen rind (mg cy-3-glu/g). Results showed that mangosteen rind extracted using both ionic liquids e.g., 1-ethy-3metylimidazolium bromide (EMIM) and 1-butyl-3methylimidazolium bromide (BMIM) solutions gave higher anthocyanins yields of 0.72 mg cy-3-glu/g and 0.69 mg cy-3-glu/g, respectively, in comparison to the 50% ethanol and deep eutectic solvents. This study revealed that high viscosity of deep eutectic solvent was the main factor that hindered the penetration of the solvent into the cell membrane of mangosteen rind, as a result, lower anthocyanins yields were obtained. Hence, in bioactive compounds extraction from plant materials, deep eutectic solvent incorporated with ultrasound or microwave is recommended as it could enhance the penetration of solvent into the plant’s matrix.
Optimization of acetic acid – infused insecticide from avocado (persea americana) seed extract using microwave – assisted extraction method
Authors: Medrano H A , Dungque J , Espulgar H R , Chavez L V , Bautista L S , Sevilla T , Del Mundo C M , Tugade C 
Published: July 2024

Abstract
Insecticides are widely used in households to control and manage pest populations. Biological insecticides are a more sustainable alternative, but they are often less effective. This study evaluated the effectiveness of avocado seed oil extract with added acetic acid as a bio-insecticide against Aedes aegypti mosquitoes. The researchers used microwave-assisted extraction to obtain the avocado seed oil. Avocado oil and acetic acid were formulated in different volume concentrations: 10%, 30%, 50%, 70%, and 90% (v/v) avocado seed oil extract-infused acetic acid. Assessment of its effectiveness is performed by directly spraying it on Aedes aegypti mosquitoes in a 70x70x70 cm glass cylinder setup and conducting knockdown and mortality tests. The avocado seed oil insecticide showed significant knockdown effectiveness (p= 2.07E-7, α= 0.95) against Aedes aegypti mosquitoes compared to both the positive control (Neem Oil) and negative control (acetic acid). At 1 mL application, all the concentrations have significant differences (p= 0.0044, α= 0.95). The 50% and 90% concentration show the highest efficacy, showing no significant difference (p-value= 0.0527, α= 0.95), the % Knockdown is 25.00% and 20.00%, respectively, while 30% is the lowest at 13.33% within 60 minutes. However, none of the test samples reached 50% knockdown in 60 minutes. At a 3 mL rate, all concentrations resulted in 100% mortality, and the 50% concentration was the fastest in 6 minutes but had no significant difference (p= 0.9746, α= 0.95) with 90% concentration at 10 minutes. All concentrations yield higher efficacy compared to the positive control in both 1 mL and 3 mL rates. In the 1 mL and 3 mL tests, there were no recorded instances of mortality in the pure acetic acid sample. Based on the results, the optimum product among all the formulated concentrations is 50% (v/v) avocado seed oil extract-infused acetic acid having a significant difference (p=2.83E-13, α= 0.95).
Analysis of fire protection design strategies for commercial renovation of villagers’ self-built houses
Authors: Fan L , Wei W B , Pang L L 
Published: July 2024

Abstract
The current situation of self-built houses by villagers is prevalent in rural areas, where many villagers construct their own residential dwellings based on their personal needs and economic circumstances. These self-built houses are typically constructed using basic materials and traditional building techniques, often without adherence to strict building regulations and standards. As a result of the lack of professional knowledge and technical guidance, the structural integrity and safety of these houses are often compromised. In addition, the lack of firefighting facilities and fire prevention measures further increase the risk of fire accidents. This situation contributes to a higher incidence of fires in rural areas, posing a significant threat to the lives and assets of villagers. Therefore, it becomes imperative to improve the current state of self-built houses by villagers. Strengthening fire safety awareness and implementing robust fire prevention measures are vital in this regard. This paper aims to summarize the challenges involved in fire protection design for renovating rural buildings. Additionally, it proposes fire protection design principles specifically for the commercial transformation of self-built houses by villagers. By analyzing real-world engineering cases, this study puts forth specific fire protection measures concerning fire rescue, fire control zones (groups), evacuation design, and fire systems. To ensure the fire safety of these buildings, special fire protection design methods are employed. The effectiveness of the proposed fire protection measures are validated through the use of FDS fire and smoke numerical simulation analysis software and Pathfinder evacuation simulation software, ensuring the fire safety of the buildings. The results show that the available safe evacuation time that can be provided by this scenario is 1200 s as calculated by the FDS simulation, and the necessary safe evacuation time is less than the available safe evacuation time in case of a fire on the first floor of this building, and the safe evacuation of the people can be guaranteed. This study can provide a valuable resource for architects, engineers, and decision makers to implement effective fire protection measures during commercial remodeling of village-owned houses.
Mechanistic indoor air quality model and data-driven calibration for intelligent HVAC AI control system through real-time data in underground buildings
Authors: Jeong C H , Heo S K , Woo T Y , Kim S Y , Park D S , Kim M J , Yoo C K 
Published: July 2024

Abstract
Modeling the dynamics of indoor air quality (IAQ) in subway environments is challenging due to the complex interplay of variables like subway schedules, ventilation, and passenger numbers. This study developed a high-precision mechanistic model for IAQ management and intelligent HVAC control in underground buildings, focusing on Y-station. Global Sensitivity Analysis (GSA) highlighted the significance of the train piston factor during operational hours and the increased sensitivity of penetration and deposition factors when trains are not operational. The model, calibrated in real-time using a Genetic Algorithm (GA), exhibited remarkable accuracy in simulating PM2.5 levels, affirming its effectiveness in forecasting future air quality. The model adeptly captures the complexities of air quality dynamics, providing a comprehensive understanding of temporal IAQ variations. The result demonstrates the model’s efficacy as a tool offering a foundation for strategies to forecast IAQ and control the HVAC system in underground buildings.
Developing a solar PV system for cost-effective electricity reduction in an aluminium extrusion plant
Authors: Yee C Z , Saw L H , Yeo W H , Chua K H , Loo W W , Lim H K , Lim Y P 
Published: July 2024

Abstract
The demand for solar photovoltaic systems has been steadily increasing over the years, driven by the collective goal to reduce both CO2 emissions and electricity bills in order to foster a sustainable world. Industries with high energy consumption, particularly manufacturing, are actively pursuing the establishment of more sustainable plants to align with net-zero objectives. The primary aim of this project is to design a solar photovoltaic system tailored for an aluminium manufacturing plant, with the intent to curtail electricity consumption and minimize CO2 emissions by harnessing and utilizing energy generated from the photovoltaic system. The comprehensive analysis encompasses meteorological data, daily load demand configuration, photovoltaic array assessment, and simulation of grid-connected inverter sizing through the utilization of PVsyst software. According to the simulation results, the collective operational capacity of the solar photovoltaic system reaches 5240 kWp, effectively meeting 85% of the factory’s maximum demand. To fulfil the plant’s requirements, a total of 12780 panels are necessary. The analysis reveals that this solar system can generate a total of 7,609,690 kWh annually, constituting approximately 26.10% of the total electricity bill for the year 2022, amounting to 29,146,841.28 kWh. The estimated savings from implementing this solar solution amount to around RM 2,701,518 per year. Moreover, the solar system significantly reduces CO2 emissions by an annual total of 4,224.467 tons, contributing to a healthier surrounding environment. The anticipated return on investment, as per the PVsyst projections, is expected to occur within approximately 3.4 years.
Optimizing a dew point evaporative cooler in data center applications
Authors: Yan W C , Yang C J , Liu Y L , Jin L W , Cui X , Meng X Z 
Published: July 2024

Abstract
The escalating energy consumption of data centers has led to a pressing need for energy-efficient cooling solutions. This paper presents a countercurrent dew point evaporative cooler (DPEC) for data center refrigeration. We developed and experimentally validated a numerical model for DPEC, then formulated regression models using the response surface method. These models link eight key design factors, including geometrical and operational factors, to three performance indices: cooling capacity per unit volume, coefficient of performance, and outlet primary air temperature. We assessed the extent of factor influence on these indices. By using these regression models as objective functions, we used the genetic algorithm for design optimization under two climatic conditions, resulting in various optimal parameter combinations. Our findings highlight the strong predictive accuracy of these models. In comparison to the original design, the optimal design achieved an improvement of 104.8%, an increase of 23.9%, and a reduction of 13.8% in the three indices.
Dynamic interaction in sustainable energy: Learning from South Sumatra in transforming conflict into collaboration to accelerate energy mix targets
Authors: Hermawan Pri , Ardianto Rafi Ndari , Suryanto Crista Fialdila , Aryansyah  
Published: July 2024

Abstract
Energy transition is an alternative solution that emerged as an effort to achieve zero net emissions. The countries that signed the Paris Agreement are expected to reach their targets by 2030. Indonesia targets this agreement by performing the energy mix set at 25% nationally. Many provinces have difficulties achieving its implementation due to conflicts between related stakeholders, including industry. However, some provinces have shown promising transition changes with accelerated target achievement. This research aims to identify how the government of South Sumatra can reach beyond the National Target by turning the conflict into a collaboration between government and industry. The collaboration impacts accelerating the achievement of the energy mix target. A multi-layered approach was used to analyze the dynamics of the energy transition by demonstrating the energy transition process in Indonesia using Actor Interaction analysis, Dilemma analysis, and System Analysis. Therefore, the bottom-up approach chosen, systematically uncovering actor interactions within and across systems. Interviews were carried out for data collection. The results of the interviews were identified until a series of methods emerged that were used to identify the collaboration that occurred. The analysis found that local governments encounter dilemmatic situations to balance a smooth energy transition process and ensure stable socioeconomic conditions. The system dynamic simulation has proven to be a vital addition to Drama Theory and Graph Model for Conflict Resolution, offering a temporal perspective that is fundamental for the decision-making process that concerns the ever-changing environmental situation.
Improving building natural ventilation simulation accuracy: calibration of standard k − ε closure coefficients using design of experiment
Authors: Li Q , Tai V C , Moey L K , Go T F , Rahman N F A 
Published: July 2024

Abstract
The objective of this study is to improve the accuracy of the standard k − ε (SKE) turbulence model for natural ventilation simulation, a critical component in the analysis and design of energy-efficient buildings. The methodology involves generating 17 design points for the four closure coefficients (C

ɛ

1,C

ɛ

2,C

µ
,σ

k
) for the SKE model using 2k full-factorial design of experiment (DOE) with a centre point. A sheltered single storey-building with windward and leeward openings is modelled and simulated using computational Fluid Dynamics (CFD) to obtain the Root Mean Square Error (RMSE) and Factor of two observation (FAC2) for each design point. Response models for RMSE and FAC2 are then generated, and optimization is employed to maximize FAC2, minimize RMSE, and the combination of both. The results are validated and compared with experimental and simulation data reported in existing literature. The findings indicate that the indoor velocity profiles with closure coefficients obtained by maximizing FAC2 are better aligned with the actual experimental results. Compared with the existing calibration method, the proposed calibration method can yield superior results with fewer sampling points, highlighting the efficiency of the proposed approach. The calibration framework developed in this study can be extended to other simulation scenarios, contributing to the robust and efficient modelling of natural ventilation systems in various contexts. This research presents a novel calibration method for the SKE model in natural ventilation simulation, providing a more accurate and efficient approach compared to existing methods. The results have important implications for researchers and practitioners working in the field of building energy simulation and sustainability.
Reinforcement learning optimal control method for multi chiller HVAC system in an existing office building
Authors: Wang H Y , Ge Q , Ma C , Cui T 
Published: July 2024

Abstract
Given that buildings consume approximately 33% of global energy, and HVAC systems contribute nearly half of a building’s total energy demand, optimizing their efficiency is imperative for sustainable energy use. Many existing buildings operate HVAC systems inefficiently, displaying non-stationary behavior. Current reinforcement learning (RL) training methods rely on historical data, which is often obtained through costly modeling or trial-and-error methods in real buildings. This paper introduces a novel reinforcement learning construction framework designed to improve the robustness and learning speed of RL control while reducing learning costs. The framework is specifically tailored for existing office buildings. Applying this framework to control HVAC systems in real office buildings in Beijing, engineering practice results demonstrate: during the data collection phase, energy efficiency surpasses traditional rule-based control methods from the previous year, achieving significantly improved energy performance (a 17.27% reduction) with minimal comfort sacrifices. The system achieves acceptable robustness, learning speed, and control stability. Reduced ongoing manual supervision leads to savings in optimization labor. Systematic exploration of actions required for RL training lays the foundation for RL algorithm development. Furthermore, by leveraging collected data, a reinforcement learning control algorithm is established, validating the reliability of this approach. This construction framework reduces the prerequisites for historical data and models, providing an acceptable alternative for systems with insufficient data or equipment conditions.
Ion- and surface-sensitive interactions during oxygen evolution reaction in alkaline media
Authors: Angeles P D , Bustamante A R I , Sasil H A S , Loresca D E D , Paraggua J A D R 
Published: July 2024

Abstract
Clean and sustainable energy has turned towards electrochemical water splitting as a viable solution in minimizing carbon emissions. Electrolysis of water converts electrical energy to chemical energy, through the production of hydrogen and oxygen gases, which can be harnessed for potential applications without contributing to greenhouse emissions. While this energy storage process shows great potential, its efficiency is hindered by the sluggish kinetics of the oxygen evolution reaction (OER). As a result, its widespread application in green electrolytic technologies is limited hence investigations on improving OER kinetics are of utmost importance. Recent research breakthroughs indicate that alkali metal cations are more than passive observers. They play complex roles in the electric double layer (EDL), which positively influences the OER kinetics. The presence of numerous ions and their combinations presents a challenge of complexity. This study aims to delve into the impact of alkali metal cations on OER activity due to the variance in their hydration energies. Specific investigations focusing on different alkali metal cations in solution, such as Li+, Na+, and K+, was conducted on RuO2 to gain a deeper understanding of how these ions interact with both reactants and intermediate species in the reaction kinetics. Traditional electrochemical tests, including cyclic voltammetry (CV), linear sweep voltammetry (LSV), electrochemical impedance spectroscopy (EIS), and accelerated degradation test (ADT) measurements were employed to elucidate critical aspects such as surface activation, electric double layer interactions, catalytic activity and stability, ohmic resistance, and mass and charge transport.
Thermoeconomic analysis of novel hydrogen liquefaction assisted by absorption refrigeration utilizing heat from Brayton cycle
Authors: Rahadiyan L , Aziz M , Nasruddin N 
Published: July 2024

Abstract
Current research presents a novel method for reducing the energy consumption of hydrogen liquefaction through heat recovery of hydrogen liquefier. An ammonia absorption refrigeration cycle on the hydrogen precooling utilizes the heat generated by the compressor intercooler and aftercooler of the reverse Brayton cycle of hydrogen liquefier to precool hydrogen feedstock. The system is analyzed from exergy, energy, and economic perspective. The results are compared with the reference case without a heat recovery system. The proposed system can reduce SEC (specific energy consumption) from 7.37 kWh/kgLH2 to 6.23 kWh/kgLH2 and exergy efficiency improvement from 55.2% to 60.90%. The economic analysis shows that the levelized cost of energy to produce 5.07 tons/day of liquid hydrogen for the reference and novel case is 5.88 USD/kgLH2 and 5.03 USD/kgLH2, respectively. The results imply that the proposed method can be a reference for designing an integrated hydrogen liquefaction system to minimize energy consumption.