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1 – 10 of 49
Article
Publication date: 30 June 2023

Aishwarya Narang, Ravi Kumar, Amit Kumar Dhiman, Ravi Shankar Pandey and Pavan Kumar Sharma

This study describes a series of experiments investigating the upper hot layer temperature profile in a confined space under different ventilation conditions for…

Abstract

Purpose

This study describes a series of experiments investigating the upper hot layer temperature profile in a confined space under different ventilation conditions for porosity-controlled wood crib fires for pre-flashover conditions.

Design/methodology/approach

Full-scale compartment (4 m × 4 m × 4 m) experiments were carried out for four-door openings, i.e. 100%, 75%, 50% and 25% of the total vent area (2 m × 1 m) with the wood crib as a fuel load. The temperature of the upper hot smoke layers of the compartment was recorded with the help of four layers of thermocouples for varying vent areas.

Findings

The effect of ventilation on the properties, i.e. mass loss rate, enclosure temperature, heat release rate and carbon monoxide (CO) gas concentration, has been measured and analyzed. The effect of ventilation on heat flux and flame temperature has also been studied. Compartment gas temperature has been examined by five wood crib burning stages: Ignition, growth, steady burning, recess and collapse.

Originality/value

Findings demonstrate that the influence of vent openings varies for the burning parameters and upper layer temperature of the compartment. The current results are beneficial in analyzing thermal risks concerning compartment fire and fire safety engineering projects.

Details

Journal of Structural Fire Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-2317

Keywords

Article
Publication date: 15 October 2021

Paulthurai Rajesh, Francis H. Shajin and Kumar Cherukupalli

The purpose of this paper is to track the maximal power of wind energy conversion system (WECS) and enhance the search capability for WECS maximum power point tracking (MPPT).

Abstract

Purpose

The purpose of this paper is to track the maximal power of wind energy conversion system (WECS) and enhance the search capability for WECS maximum power point tracking (MPPT).

Design/methodology/approach

The hybrid technique is the combination of tunicate swarm algorithm (TSA) and radial basis function neural network.

Findings

TSA gets input parameters from the rectifier outputs such as rectifier direct current (DC) voltage, DC current and time. From the input parameters, it enhances the reduced fault power of rectifier and generates training data set based on the MPPT conditions. The training data set is used in radial basis function. During the execution time, it produces the rectifier reference DC side voltage that is converted to control pulses of inverter switches.

Originality/value

Finally, the proposed method is executed in MATLAB/Simulink site, and the performance is compared with different existing methods like particle swarm optimization algorithm and hill climb searching technique. Then the output illustrates the performance of the proposed method and confirms its capability to solve issues.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 9 October 2023

Gokulnath R. and Booma Devi

Diesel has traditionally been considered the best-suited and most widely used fuel in various sectors, including manufacturing industries, power production, automobiles and…

Abstract

Purpose

Diesel has traditionally been considered the best-suited and most widely used fuel in various sectors, including manufacturing industries, power production, automobiles and transportation. However, with the ongoing crisis of fossil fuel inadequacy, the search for alternative fuels and their application in these sectors has become increasingly important. One particularly interesting and beneficial alternative fuel is biodiesel derived from bio sources.

Design/methodology/approach

In this research, an attempt was made to use biodiesel in an unconventional micro gas turbine engine. It will remove the concentric use of diesel engines for power production by improving fuel efficiency as well as increasing the power production rate. Before the fuel is used enormously, it has to be checked in many ways such as performance, emission and combustion analysis experimentally.

Findings

In this paper, a detailed experimental study was made for the use of Spirulina microalgae biodiesel in a micro gas turbine. A small-scale setup with the primary micro gas turbine and secondary instruments such as a data acquisition system and AVL gas analyser. The reason for selecting the third-generation microalgae is due to its high lipid and biodiesel production rate. For the conduction of experimental tests, certain conditions were followed in addition that the engine rotating rpm was varied from 4,000, 5,000 and 6,000 rpm. The favourable and predicted results were obtained with the use of microalgae biodiesel.

Originality/value

The performance and combustion results were not exactly equal or greater for biodiesel blends but close to the values of pure diesel; however, the reduction in the emission of CO was at the appreciable level for the used spirulina microalgae biodiesel. The emission of nitrogen oxides and carbon dioxide was a little higher than the use of pure diesel. This experimental analysis results proved that the use of spirulina microalgae biodiesel is both economical and effective replacement for fossil fuel.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 31 July 2021

Jaruphant Noosomton

The suction pipes are important in agriculture and are used widely in water management and agricultural–mechanical industry in ASEAN. Thus, this paper aims to present design of…

Abstract

Purpose

The suction pipes are important in agriculture and are used widely in water management and agricultural–mechanical industry in ASEAN. Thus, this paper aims to present design of new impeller in suction pipe and include shape blade impeller to optimize for suction head, which has been higher than efficiency local-type by the performance. It mostly depends on the hydrodynamic characteristics, e.g. lift, drag and ratio, which is known as the “Thai Phaya-Nakh pipe”.

Design/methodology/approach

By approach NACA methodology and use applied technique: leading edge of blade, skew-line, cambered-line, developed area and advanced number etc., for analyzing data which the result of CFD simulation.

Findings

The models were tested in field by using motor at rotation speed 1500 rpm and found that the summarized average suction efficiency of the new impeller was estimated to be 72%, which has been greater than that of the local-type impeller with an average suction efficiency of 28% to 2.6 times. In addition, the amount of required electrical energy was reduced by 18%.

Originality/value

Then after analyzing the data from the static pressure distribution flow rate of impeller models, it is found that the new curved impeller has higher flow rate than the local type impeller. Thus, this study suggests the shape new impeller has higher flow rate than the local type impeller.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 26 July 2023

Aarzoo Sharma, Aviral Kumar Tiwari, Emmanuel Joel Aikins Abakah and Freeman Brobbey Owusu

This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be…

Abstract

Purpose

This paper aims to examine the cross-quantile correlation and causality-in-quantiles between green investments and energy commodities during the outbreak of COVID-19. To be specific, the authors aim to address the following questions: Is there any distributional predictability among green bonds and energy commodities during COVID-19? Is there exist any directional predictability between green investments and energy commodities during the global pandemic? Can green bonds hedge the risk of energy commodities during a period of the financial crisis.

Design/methodology/approach

The authors use the nonparametric causality in quantile and cross-quantilogram (CQ) correlation approaches as the estimation techniques to investigate the distributional and directional predictability between green investments and energy commodities respectively using daily spot prices from January 1, 2020, to March 26, 2021. The study uses daily closing price indices S&P Green Bond Index as a representative of the green bond market. In the case of energy commodities, the authors use S&P GSCI Natural Gas Spot, S&P GSCI Biofuel Spot, S&P GSCI Unleaded Gasoline Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI, OPEC Oil Basket Price, Crude Oil Oman, Crude Oil Dubai Cash, S&P GSCI Heating Oil Spot, S&P Global Clean Energy, US Gulf Coast Kerosene and Los Angeles Low Sulfur CARB Diesel Spot.

Findings

From the CQ correlation results, there exists an overall negative directional predictability between green bonds and natural gas. The authors find that the directional predictability between green bonds and S&P GSCI Biofuel Spot, S&P GSCI Gas Oil Spot, S&P GSCI Brent Crude Spot, S&P GSCI WTI Spot, OPEC Oil Basket Spot, Crude Oil Oman Spot, Crude Oil Dubai Cash Spot, S&P GSCI Heating Oil Spot, US Gulf Coast Kerosene-Type Jet Fuel Spot Price and Los Angeles Low Sulfur CARB Diesel Spot Price is negative during normal market conditions and positive during extreme market conditions. Results from the non-parametric causality in the quantile approach show strong evidence of asymmetry in causality across quantiles and strong variations across markets.

Practical implications

The quantile time-varying dependence and predictability results documented in this paper can help market participants with different investment targets and horizons adopt better hedging strategies and portfolio diversification to aid optimal policy measures during volatile market conditions.

Social implications

The outcome of this study will promote awareness regarding the environment and also increase investor’s participation in the green bond market. Further, it allows corporate institutions to fulfill their social commitment through the issuance of green bonds.

Originality/value

This paper differs from these previous studies in several aspects. First, the authors have included a wide range of energy commodities, comprising three green bond indices and 14 energy commodity indices. Second, the authors have explored the dependency between the two markets, particularly during COVID-19 pandemic. Third, the authors have applied CQ and causality-in-quantile methods on the given data set. Since the market of green and sustainable finance is growing drastically and the world is transmitting toward environment-friendly practices, it is essential and vital to understand the impact of green bonds on other financial markets. In this regard, the study contributes to the literature by documenting an in-depth connectedness between green bonds and crude oil, natural gas, petrol, kerosene, diesel, crude, heating oil, biofuels and other energy commodities.

Details

Studies in Economics and Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1086-7376

Keywords

Article
Publication date: 20 March 2024

Hakan F. Oztop, Burak Kiyak and Ishak Gökhan Aksoy

This study aims to focus on understanding how different jet angles and Reynolds numbers influence the phase change materials’ (PCMs) melting process and their capacity to store…

Abstract

Purpose

This study aims to focus on understanding how different jet angles and Reynolds numbers influence the phase change materials’ (PCMs) melting process and their capacity to store energy. This approach is intended to offer novel insights into enhancing thermal energy storage systems, particularly for applications where heat transfer efficiency and energy storage are critical.

Design/methodology/approach

The research involved an experimental and numerical analysis of PCM with a melting temperature range of 22 °C–26°C under various conditions. Three different jet angles (45°, 90° and 135°) and two container angles (45° and 90°) were tested. Additionally, two different Reynolds numbers (2,235 and 4,470) were used to explore the effects of jet outlet velocities on PCM melting behaviour. The study used a circular container and analysed the melting process using the hot air inclined jet impingement (HAIJI) method.

Findings

The obtained results showed that the average temperature for the last time step at Ф = 90° and Re = 4,470 is 6.26% higher for Ф = 135° and 14.23% higher for Ф = 90° compared with the 45° jet angle. It is also observed that the jet angle, especially for Ф = 90°, is a much more important factor in energy storage than the Reynolds number. In other words, the jet angle can be used as a passive control parameter for energy storage.

Originality/value

This study offers a novel perspective on the effective storage of waste heat transferred with air, such as exhaust gases. It provides valuable insights into the role of jet inclination angles and Reynolds numbers in optimizing the melting and energy storage performance of PCMs, which can be crucial for enhancing the efficiency of thermal energy storage systems.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 21 December 2023

Alireza Arab, Mohammad Ali Sheikholislam and Saeid Abdollahi Lashaki

The purpose of this paper is to review studies on mathematical optimization of the sustainable gasoline supply chain to help decision-makers understand the current situation, the…

Abstract

Purpose

The purpose of this paper is to review studies on mathematical optimization of the sustainable gasoline supply chain to help decision-makers understand the current situation, the exact dimensions of the problem and the models provided in the literature. So, a more realistic mathematical optimization model can be achieved by fully covering all dimensions of the supply chain of this product.

Design/methodology/approach

To evaluate and comprehend the mathematical optimization of the sustainable gasoline supply chain research area, a systematic literature review is undertaken that covers material collection, descriptive analysis, content analysis and material evaluation steps. Finally, based on this process, 69 related articles were carefully investigated.

Findings

The results of the systematic literature review show the main areas of the published papers on mathematical optimization of sustainable gasoline supply chain problems and the gaps for future research in this field presented based on them.

Research limitations/implications

This approach is subject to limitations because the protocol of the systematic review of the research literature only included searching for the considered combination of keywords in the Scopus and ProQuest databases. Furthermore, the protocol used in this paper restricts documents to English.

Practical implications

The results have significant implications for both academicians and practitioners in this field. It can be useful for academics to comprehend the gaps and future trends in this field. Also, for practitioners, it can be useful to identify and understand the parts of the mathematical optimization model, which can help them model this problem effectively and efficiently.

Originality/value

No systematic literature review has been done in this field by considering gasoline to the best of the authors’ knowledge and delivers new facts for the future development of this field.

Details

Journal of Science and Technology Policy Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 15 February 2023

Mehmet Necati Cizrelioğullari, Tapdig Veyran Imanov, Tugrul Gunay and Aliyev Shaiq Amir

Temperature anomalies in the upper troposphere have become a reality as a result of global warming, which has a noticeable impact on aircraft performance. The purpose of this…

Abstract

Purpose

Temperature anomalies in the upper troposphere have become a reality as a result of global warming, which has a noticeable impact on aircraft performance. The purpose of this study is to investigate the total air temperature (TAT) anomaly observed during the cruise level and its impact on engine parameter variations.

Design/methodology/approach

Empirical methodology is used in this study, and it is based on measurements and observations of anomalous phenomena on the tropopause. The primary data were taken from the Boeing 747-8F's enhanced flight data recorder, which refers to the quantitative method, while the qualitative method is based on a literature review and interviews. The GEnx Integrated Vehicle Health Management system was used for the study's evaluation of engine performance to support the complete range of operational priorities throughout the entire engine lifecycle.

Findings

The study's findings indicate that TAT and SAT anomalies, which occur between 270- and 320-feet flight level, have a substantial impact on aircraft performance at cruise altitude and, as a result, on engine parameters, specifically an increase in fuel consumption and engine exhaust gas temperature values. The TAT and Ram Rise anomalies were the focus of the atmospheric deviations, which were assessed as major departures from the International Civil Aviation Organizations–defined International Standard Atmosphere, which is obvious on a positive tendency and so goes against the norms.

Research limitations/implications

Necessary fixed flight parameters gathered from the aircraft's enhanced airborne flight recorder (EAFR) via Aeronautical Radio Incorporated (ARINC) 664 Part 7 at a certain velocity and altitude interfacing with the diagnostic program direct parameter display (DPD), allow for analysis of aircraft performance in a real-time frame. Thus, processed data transmits to the ground maintenance infrastructure for future evaluation and for proper maintenance solutions.

Originality/value

A real-time analysis of aircraft performance is possible using the diagnostic program DPD in conjunction with necessary fixed flight parameters obtained from the aircraft's EAFR via ARINC 664 Part 7 at a specific speed and altitude. Thus, processed data is transmitted to the ground infrastructure for maintenance to be evaluated in the future and to find the best maintenance fixes.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 9 January 2024

John Mendy and Nawaf AlGhanem

This paper's purpose centres on advancing the current financialisation strategies within digital transformation (DT) through a rebalanced synthesis of both financialisation and…

Abstract

Purpose

This paper's purpose centres on advancing the current financialisation strategies within digital transformation (DT) through a rebalanced synthesis of both financialisation and people/centric, non-financialisation strategies of the DT field. Based on empirical data from Bahrain's energy sector, a new framework on People-centric, Sustaining Network Leadership is developed, capturing DT's human values deficit and proposing a new model on financialisation and non-financialisation strategies showing ‘how’ and ‘why’ DT is implemented in contemporary organisations.

Design/methodology/approach

This study conducted a mixed methodology of narrative interviews, case studies and reviewed significant contributions from the DT, leadership and change management debates. A total of 26 operational and high-level leaders from Bahrain, 8 top energy companies and Braun and Clarke's 6-phase analysis were combined to form four empirical thematic bundles on ‘how’ and ‘why’ leaders adopted financialisation and non-financialisation strategies to resolve organisational sustainability issues in an Arabic context.

Findings

Four sets of findings (bundles 1–4) highlight participants' financial and structural understanding when implementing DT initiatives, the different leadership styles ranging from authoritarian to network leadership, the socio-economic, political and cultural ramifications of their practices and the urgency of staff reskilling for organisational resilience and strategic sustainability. Based on the eight energy cases and interviews, a new values-driven, People-centric Sustaining Network Leadership Model is developed to show a more effective and efficient use of financial and non-financial resources when organisations implement DT initiatives in efforts to resolve global energy sustainability problems.

Research limitations/implications

Leadership, change management, DT, energy and environmental sustainability is a huge area of scholarship. While new studies emerge and contribute to this growing body of knowledge, this investigation has focused on those that significantly highlight how to make effective use of financialisation and non-financialisation resources. Therefore, all the literature on the topic has not been included. Although this study has filled the non-financialisation gap in current DT studies, a further rebalancing of the financialisation versus non-financialisation debates will be needed for theoreticians, practitioners and policy makers to continue addressing emerging and more complex socio-economic, political and cultural issues within and beyond organisations. Limitations are the study's focus on the Bahrain energy sector and the limited sample of 26 leaders.

Practical implications

The study provides practitioners and policy makers with an approach for the successful implementation of DT initiatives in the oil and gas sector. For academics, this study provides empirically unique and interesting thematic bundles, insightful analyses into leadership, organisational change, digital transformation and network leadership theories to develop an innovative and creative People-centric, Sustaining Network Leadership Approach/Model on the practical barriers, implications/impacts of various leadership styles and potential solutions via a socio-cultural values-based alternative to the current financialisation discourse of DT.

Originality/value

While there is a growing body of literature on DT, Leadership and Organisational Transformation and Change, there is a dearth of scholarship on the human-orientated strategies of DT implementation outside of western contexts. A contemporary and comprehensive, empirically evidenced analysis of the field has led to the development of this study's People-centric, Sustaining Network Leadership model which frames, captures, synthesises and extends the dominant cost-minimisation rhetoric of DT discourse to include a shared set of leadership practices, behaviours, intentions, perceptions and values. This helped to reveal the previously missing ‘how’ and ‘why’ of DT’s operational and strategic implementation.

Details

Journal of Strategy and Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1755-425X

Keywords

Article
Publication date: 28 December 2023

Weixin Zhang, Zhao Liu, Yu Song, Yixuan Lu and Zhenping Feng

To improve the speed and accuracy of turbine blade film cooling design process, the most advanced deep learning models were introduced into this study to investigate the most…

Abstract

Purpose

To improve the speed and accuracy of turbine blade film cooling design process, the most advanced deep learning models were introduced into this study to investigate the most suitable define for prediction work. This paper aims to create a generative surrogate model that can be applied on multi-objective optimization problems.

Design/methodology/approach

The latest backbone in the field of computer vision (Swin-Transformer, 2021) was introduced and improved as the surrogate function for prediction of the multi-physics field distribution (film cooling effectiveness, pressure, density and velocity). The basic samples were generated by Latin hypercube sampling method and the numerical method adopt for the calculation was validated experimentally at first. The training and testing samples were calculated at experimental conditions. At last, the surrogate model predicted results were verified by experiment in a linear cascade.

Findings

The results indicated that comparing with the Multi-Scale Pix2Pix Model, the Swin-Transformer U-Net model presented higher accuracy and computing speed on the prediction of contour results. The computation time for each step of the Swin-Transformer U-Net model is one-third of the original model, especially in the case of multi-physics field prediction. The correlation index reached more than 99.2% and the first-order error was lower than 0.3% for multi-physics field. The predictions of the data-driven surrogate model are consistent with the predictions of the computational fluid dynamics results, and both are very close to the experimental results. The application of the Swin-Transformer model on enlarging the different structure samples will reduce the cost of numerical calculations as well as experiments.

Research limitations/implications

The number of U-Net layers and sample scales has a proper relationship according to equation (8). Too many layers of U-Net will lead to unnecessary nonlinear variation, whereas too few layers will lead to insufficient feature extraction. In the case of Swin-Transformer U-Net model, incorrect number of U-Net layer will reduce the prediction accuracy. The multi-scale Pix2Pix model owns higher accuracy in predicting a single physical field, but the calculation speed is too slow. The Swin-Transformer model is fast in prediction and training (nearly three times faster than multi Pix2Pix model), but the predicted contours have more noise. The neural network predicted results and numerical calculations are consistent with the experimental distribution.

Originality/value

This paper creates a generative surrogate model that can be applied on multi-objective optimization problems. The generative adversarial networks using new backbone is chosen to adjust the output from single contour to multi-physics fields, which will generate more results simultaneously than traditional surrogate models and reduce the time-cost. And it is more applicable to multi-objective spatial optimization algorithms. The Swin-Transformer surrogate model is three times faster to computation speed than the Multi Pix2Pix model. In the prediction results of multi-physics fields, the prediction results of the Swin-Transformer model are more accurate.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0961-5539

Keywords

1 – 10 of 49