Energy efficiency optimization of the waste heat recovery system with embedded phase change materials in greenhouses: A thermo-economic-environmental study

Yan, Shu‐Rong; Fazilati, Mohammad Ali; Samani, Navid; Ghasemi, Hamid; Toghraie, Davood; Nguyen, Quyen; Karimipour, Arash

doi:10.1016/j.est.2020.101445

Cited by 128 publications

(19 citation statements)

References 37 publications

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“…Whereas, y t proves the actual valuation of the inconstant possible at fact t, ε t is random error at time t, ; i and α j are the coefficients of the model. The ARIMA model builds a random temporal structure knowledge set in the following phases: Auto-correlation Function (ACF) plots determined the lag order of the underline model [36,[48][49][50][51].…”

Section: Reseach Methodologymentioning

confidence: 99%

“…Concluding the unemployment rate accurately helps consumers avoid market risk from surprising changes in project conditions and economic care. This study builds on our prior research on the effects of corona virus on global unemployment [ 46 , 49 , 50 , 59 – 61 ]. In this study, we used ARIMA, ANN, SVM, and ARNN hybrid models to predict feasible unemployement.…”

Section: Conclusion and Implementationsmentioning

confidence: 99%

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COVID-19 pandemic and unemployment rate prediction for developing countries of Asia: A hybrid approach

Shi

Khan

Tian³

2022

PLoS ONE

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Unemployment is an essential problem for developing countries, which has a direct and major role in economy of a country. Understanding the pattrens of unemployment rate is critical now a days and has drawn attention of researcher from all fields of study across the globe. As unemployment plays an important role in the planning of a country’s monetary progress for policymakers and researcher. Determining the unemployment rate efficiently required an advance modeling approach. Recently,numerous studies have relied on traditional testing methods to estimate the unemployment rate. Unemployment is usually nonstationary in nature. As a result, demonstrating them using traditional methods will lead to unpredictable results. It needs a hybrid approach to deal with the prediction of unemployment rate in order to deal with the issue associated with traditional techniques. This research primary goal is to examine the effect of the Covid-19 pandemic on the unemployment rate in selected countries of Asia through advanced hybrid modeling approach, using unemployment data of seven developing countries of Asian: Iran, Sri Lanka; Bangladesh; Pakistan; Indonesia; China; and India,and compare the results with conventional modeling approaches. Finding shows that the hybrid ARIMA-ARNN model outperformed over its competitors for Asia developing economies. In addition, the best fitted model was utilised to predict five years ahead unemployment rate. According to the findings, unemployment will rise significantly in developing economies in the next years, and this will have a particularly severe impact on the region’s economies that aren’t yet developed.

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Section: Reseach Methodologymentioning

confidence: 99%

Section: Conclusion and Implementationsmentioning

confidence: 99%

COVID-19 pandemic and unemployment rate prediction for developing countries of Asia: A hybrid approach

Shi

Khan

Tian³

2022

PLoS ONE

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“…The solid–liquid PCMs can be further divided into three categories according to their chemical composition, i.e., organic, inorganic, and eutectic mixtures ( Figure 1 ), which have different ranges of melting temperature (T m ). In the high-temperature range (T m > 200 °C are the molten inorganic salts, including nitrates, carbonates, and chlorides which are mainly applied for industrial waste heat recovery [ 16 ] and concentrated solar power (CSP) [ 17 ]. They have the advantages of relatively high energy storage density (200–1000 J/g) and high thermal conductivity (0.4–0.7 W/m·K) but the main drawback is the corrosive effect on the storage tanks and delivery pipes [ 18 , 19 ].…”

Section: Major Characteristics Of Pcm Emulsionsmentioning

confidence: 99%

Preparation of Stable Phase Change Material Emulsions for Thermal Energy Storage and Thermal Management Applications: A Review

Liu

Niu

2021

Materials

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Thermal energy storage (TES) is an important means for the conservation and efficient utilization of excessive and renewable energy. With a much higher thermal storage capacity, latent heat storage (LHS) may be more efficient than sensible heat storage. Phase change materials (PCMs) are the essential storage media for LHS. PCM emulsions have been developed for LHS in flow systems, which act as both heat transfer and thermal storage media with enhanced heat transfer, low pumping power, and high thermal storage capacity. However, two major barriers to the application of PCM emulsions are their instability and high degree of supercooling. To overcome these, various strategies have been attempted, such as the reduction of emulsion droplet size, addition of nucleating agents, and optimization of the formulation. To the best of our knowledge, however, there is still a lack of review articles on fabrication methods for PCM emulsions or their latest applications. This review was to provide an up-to-date and comprehensive summary on the effective strategies and the underlying mechanisms for the preparation of stable PCM emulsions and reduction of supercooling, especially with the organic PCMs of paraffin. It was also to share our insightful perspectives on further development and potential applications of PCM emulsions for efficient energy storage.

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“…Many different theoretical, experimental and computational studies have been performed by using PCMs in various systems for thermal management and improving the energy efficiencies. Applications with PCM can be found in solar power (Shalaby et al , 2014; Javadi et al , 2020; Khan et al , 2018), building energy (Konuklu et al , 2015; Pomianowski et al , 2013; Rathore et al , 2020), waste heat recovery (Yan et al , 2020; Shon et al , 2014) and convective heat transfer (HTR) (Batina et al , 2014; Bondareva and Sheremet, 2018; Abu-Hamdeh et al , 2020; Alquaity et al , 2013; Castell et al , 2008; Raizah and Aly, 2021; Sadeghi et al , 2020). As in the applications, thermal conductivity of PCM is a challenge; many different techniques have been offered to improve the effectiveness of installed PCMs.…”

Section: Introductionmentioning

confidence: 99%

Investigation of phase change dynamics in a T-shaped multiple vented cylindrical cavity during nanofluid convection for PCM-embedded system

Kolsi

Selimefendigil

Omri

2022

HFF

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Purpose The purpose of this study is to explore the phase change (PC) dynamics in a T-shaped ventilated cavity having multiple inlet and outlet ports during nanofluid convection with phase change material (PCM) packed bed-installed system. Design/Methodology/Approach Finite element method was used to analyze the PC dynamics and phase completion time for encapsulated PCM within a vented cavity during the convection of nanoparticle loaded fluid. The study is performed for different Reynolds number of flow streams (Re1 and Re2 between 300 and 900), temperature difference (ΔT1 and ΔT2 between −5 and 10), aspect ratio of the cavity (between 0.5 and 1.5) and nanoparticle loading (between 0.02% and 0.1%). Findings It is observed that phase transition can be controlled by assigning different velocities and temperatures at the inlet ports of the T-shaped cavity. The PC becomes fast especially when the Re number and temperature of fluid in the port vary closer to the wall (second port). When the configurations with the lowest and highest Re number of the second port are considered up to 54.7% in reduction of complete phase transition time is obtained, while this amount is 78% when considering the lowest and highest inlet temperatures. The geometric factor which is the aspect ratio has also affected the flow field and PC dynamics. Up to 78% reduction in the phase transition time is obtained at the highest aspect ratio. Further improvements in the performance are achieved by using nanoparticles in the base fluid. The amounts in the phase transition time reduction are 8% and 10.5% at aspect ratio of 0.5 and 1.5 at the highest nanoparticle concentration. Originality/Value The thermofluid system and offered control mechanism for PC dynamics control can be considered for the design, optimization, further modeling and performance improvements of applications with PCM installed systems.

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Energy efficiency optimization of the waste heat recovery system with embedded phase change materials in greenhouses: A thermo-economic-environmental study

Cited by 128 publications

References 37 publications

COVID-19 pandemic and unemployment rate prediction for developing countries of Asia: A hybrid approach

COVID-19 pandemic and unemployment rate prediction for developing countries of Asia: A hybrid approach

Preparation of Stable Phase Change Material Emulsions for Thermal Energy Storage and Thermal Management Applications: A Review

Investigation of phase change dynamics in a T-shaped multiple vented cylindrical cavity during nanofluid convection for PCM-embedded system

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