Energy Efficiency Evaluation Research Articles

Development of an energy-autonomous eddy current sensor system for in-situ component monitoring

Energy-autonomous non-destructive testing (NDT) systems provide new opportunities for structural health monitoring. An NDT system that is energy-autonomous and transmits the recorded data wirelessly can be used in places that are not easily accessible for inspection. In addition, it can provide for continuous monitoring, which can improve the operational safety of various components and structures. This study presents a concept that enables energy-autonomous and wireless structural health monitoring using a splined shaft as a demonstrator. To monitor mechanical overloads, a material sensor is applied to critical areas of these components by a laser heat treatment. The structural change that occurs as a result of an overload can be monitored by the developed smart sensor system. This system consists of a material sensor, a low-cost eddy current sensor, an energy-efficient evaluation unit with an ultra-low-power microcontroller unit (MCU) and a Long-Range Wide Area Network (LoRaWAN) data transmission unit. Wireless data transmission via LoRaWAN provides access to the Industrial Internet of Things network, enabling the collection of NDT data from multiple smart sensors in a cloud and the processing of these data to assess the condition of the component from any location. It is shown that the MCU-based eddy current testing system is able to generate a similar signal quality for material characterisation compared to an industrial eddy current testing system, despite a much more compact design and a significantly higher energy efficiency. The energy autonomy of the smart sensor system is achieved by an energy harvesting system integrated into the splined shaft. In addition, three different testing scenarios are presented, which differ mainly in the scope of data processing and evaluation on the MCU, and thus also in the energy required.

Are the Adivasi Rice Growers of Sub-Himalayan North Bengal Efficient Enough? Role of Machine Learning in Farm Business After COVID-19

The COVID-19 pandemic and the consequent lockdown have disrupted the farming communities across the planet; however, the indigenous communities such as the Adivasi people of tea garden areas in India have been hit hard. It becomes more crucial when we talk about marginalized communities. In India, the Adivasi tribe found in the sub-Himalayan North Bengal cultivates folk rice that needs immediate energy-efficient measures as the production has been increased after receiving the geographical indication tag. Energy efficiency estimation often applied a two-step data envelopment analysis model in agricultural production. However, in most of the previous articles, the applications discussed the factors affecting energy use efficiency with rare studies on efficiency prediction. In this article, first, data envelopment analysis was used to estimate the energy efficiency of rice growers, and in the second stage, extreme gradient boosting, a state-of-the-art machine learning algorithm, was employed to derive the key leading efficiency determinants. The findings revealed wide variation among efficient and inefficient rice growers in the first stage and derived the most salient factors predicting energy efficiency in the second stage. The optimal use of energy inputs combined with effective education, better credit delivery mechanism, arable land availability and years of farming experience provided improvement for the future energy use efficiency of the Adivasi farmers. Further, the novel application of extreme gradient boosting as a machine learning algorithm in energy efficiency evaluation suggests decision-making solutions with a prediction accuracy of 80.91%. Moreover, this study aims to assist future researchers in examining and predicting the key leading determinants to affect energy utilization.

Analysis of the Methods for Realization of Low-Power Piezoelectric Energy Harvesting Circuits for Wearable Battery-Free Power Supply Devices

This paper presents a comprehensive review of the design and implementation methods of low-power piezoelectric energy harvesting circuits, which in the last few years have gained an extremely large range of applications like the power sources of wearable electronic devices, such as biometrical sensors. Before examining the electronic circuitries of the self-supplied power devices, an overview of the structure, equivalent electrical circuits, and basic parameters of the piezoelectric generators and MEMSs as energy harvesting elements is presented. The structure of energy storage elements (parallel-plate capacitors and thin-film supercapacitors), suitable for this type of application, is also presented. The description of these components from an electrical point of view allows them to be easily workable when connected to the various power conversion electronic circuits. Based on an overview of the structure and the principles of operation, as well as some analytical expressions for energy efficiency evaluation, a comprehensive comparative analysis is presented. Depending on the advantages and disadvantages of the known circuit configurations, the basic electrical and design parameters are systematized in tabular form. Practical realizations of piezoelectric power conversion circuits are also presented in graphic form, ensuring the optimal value of energy efficiency and compactness in the construction of the devices.

Study on Spectral Response of Saffron (Crocus sativus L.) at Different Leaf Ages and Evaluation of Photosynthetic Energy Efficiency of Narrow-Band LED Spotlights

Leaf photosynthesis largely determines the daughter corm yields in vegetative growth for saffron (Crocus sativus L.). Most of the previous researches focus on the spectral response in various species, but research on saffron leaves at different leaf ages is lacking. In this study, the action spectrum based on photosynthetic photon flux density (PPFD) and irradiance were distinguished and interpreted. The optical properties and photosynthetic performances of leaves were, respectively, investigated at two leaf ages, dependent on customized narrow-band LED spotlights from 380 nm to 780 nm with an interval of 20 nm and a band width of 10 nm. The younger leaves were characterized by higher reflectance and transmittance values at 500−600 nm, resulting in lower absorptance compared to the older leaves. The spectral response curves including the action spectrum and quantum yield for younger leaves were higher than the older, but their relative curves displayed coincidence. The spectral response curves exhibited two peaks at 440 and 640 nm, but no obvious troughs between 500 and 600 nm were observed. Nevertheless, the photosynthetic energy efficiencies of spotlights demonstrated very low values in the green/yellow region. Accordingly, more attention should be paid to green and yellow LED lighting during the vegetative stage for saffron, as well as improving their manufacturing technology.

Evaluating energy efficiency strategies in a tiny house located in a cold dry climate

The ‘Tiny House’ (TH) is a classification of residential construction, which typically have less than 400 ft2 (37 m2) of floor area. The smaller size of components and overall construction pose unique challenges to designers and builders of such houses. Therefore, this study leverages existing literature to identify optimal building practices, materials, and processes for the design, construction and operation of THs that reduce energy consumption while at the same time ensure thermal comfort of occupants. The study then evaluates selected strategies for the envelope, ventilation, as well as for passive heating and cooling, that can potentially contribute to the reduction in energy consumption and maintain appropriate thermal comfort in a TH. The intent of this study is to determine the impact of the unique configuration of the TH on resulting energy performance and thermal comfort. A calibrated whole-building simulation model of a TH in Bozeman, Montana is used to evaluate the measures taken to improve energy efficiency and thermal comfort in the house for the specific climate conditions. Results indicate to overheating as a major concern when implementing energy efficiency strategies in the TH. Recommendations for such strategies include: the use of construction technologies that provide improved insulation and airtightness; implementation of passive ventilation strategies, optimizing the use and position of windows; and implementation of hybrid passive cooling systems, all of which have to address the issue of overheating with adequate ventilation in the TH.

Optimizing solar powered electrokinetic remediation of chromium contaminated groundwater: One step closer to a sustainable solution

Electrokinetic remediation (EKR) presents a promising solution for addressing soil and groundwater contamination challenges. However, practical viability is hindered by significant energy consumption and related expenses, necessitating a comprehensive sustainability approach beyond solely adopting renewable energy and low-carbon sources. This study aims to merge innovative solar-powered systems with a risk-based evaluation strategy for tackling chromium-contaminated groundwater, providing valuable insights into EKR economically viable and applicable approaches. Through the integration of environmental and electrical engineering expertise, this study introduces the Continuous Solar-powered Electrokinetic Remediation (CSER) system and risk-based energy efficiency (REF) evaluation approach, addressing intermittency issues while optimizing energy generation and minimizing costs. Experimental results demonstrate removal efficiencies ranging from 29.85% to 84.26%, highlighting the impact of intermittent current, voltage boosters, and electrolyte selection on risk reduction and energy consumption. While intermittent current intensifies the focusing phenomenon and reduces contaminant migration, it may offer promising results in specific cases, such as observed in the EK2 experiment. Conversely, the EK3 results reveal that the integration of conventional solar power with a voltage booster may enhance removal rates but often leads to unfavorable outcomes in risk reduction considering related higher energy consumption. However, CSER, with its utilization of constant current, proves more efficient in power generation, risk reduction, and energy usage compared to other systems. Integration of such a system with cost-effective and environmentally friendly chemical agents could significantly increase the REF index while minimizing related costs, thereby shifting EKR remediation techniques towards sustainable solutions for contaminated groundwater worldwide.

Balancing preservation and utilization: Window retrofit strategy for energy efficiency in historic modern building

In modern historic buildings, the decline in energy efficiency due to aging necessitates both the preservation of historical value and the need for energy retrofits. However, the windows cannot be altered due to the historical significance of the building's windows in terms of design and materials. Retrofitting windows in modern historic buildings require a more multifaceted improvement than other envelopes. This research examines the energy efficiency of a retrofit strategy that adds double-glazed windows to existing exterior windows. Through the application of retrofit technology, the performance of the windows and their impact on indoor temperature and relative humidity were analyzed. The research conducted an energy performance analysis using building energy simulations to assess energy savings. To ensure accurate energy efficiency evaluation, on-site indoor temperature and relative humidity monitoring, as well as non-destructive thermal performance assessments, were performed. The results revealed a 35 % improvement in airtightness with window retrofit. Based on these results, simulation results showed a 17 % reduction in annual cooling energy consumption and a 24 % reduction in annual heating energy consumption following the implementation of retrofit strategies. Thermal performance improvements proved effective in reducing cooling energy consumption, while airtightness improvements were more effective for heating energy consumption reduction. Consequently, for buildings requiring both heating and cooling, the double-glazed windows retrofit strategy emerged as an energy effective retrofit approach capable of enhancing both airtightness and thermal performance. This retrofit will unlock new possibilities for the preservation and revitalization of modern historic buildings, allowing them to continue their legacy.

Energy, Exergy, Exergoeconomic, and Environmental (4E) Analysis of the Existing Gas Turbine Power Plants in BOB - PT. Bumi Siak Pusako Pertamina

The power plants in Indonesia are mostly used to supply energy for the industrial sector, including the upstream oil and gas as well as mining companies. Several companies operating in Riau contribute to the status of the region as the largest oil producer in Indonesia. These companies rely on self-generated electricity for their operations with subsequent impact on the environment. Therefore, this research was conducted to analyze the flow of energy, exergy, exergoeconomic, and environment at the 6 MW power plant operated by BOB - PT Bumi Siak Pusako - Pertamina Hulu. The second law of thermodynamics was used to evaluate energy efficiency as the maximum achievable effort. This was further integrated with economic principles to appraise the useful and wasted costs associated with thermodynamic systems through the concept of exergoeconomics. The results showed that the thermal efficiency of the gas turbine power plant was 42.85% and the exergy efficiency was 33.22% with the largest loss recorded in the combustion chamber to be 3.091 MW in the form of vibration, friction, or expansion of the components. It was also discovered that the exergy efficiency of each component was above 75%, thereby indicating the components of the gas turbine power plant components were in good condition. Moreover, the largest exergy destruction cost was 2349.16 USD/h and the exergy cost was 3,778.05 USD/kWh. The exhaust emission generated by the gas turbine power plant was 0.21 kg/s or equivalent to 0.1425 kg/kWh requiring a forest area of 11.63 ha. The results showed that the analytical method used could be comprehensively developed and applied to other power plants in Indonesia. It could also be used to understand system performance, identify energy losses, optimize energy efficiency, and link economic aspects with energy use.

Water Transfer Energy Efficiency Index for inter‐basin water transfer projects

AbstractInter‐basin water transfer projects (WTPs) address water scarcity by lifting water uphill, posing energy challenges due to diverse topography. This study therefore analyses historical trends in WTP distance, average annual water volumes delivered, water lift and pumping capacity to develop the Water Transfer Energy Efficiency Index (WTEEI) and apply it for the assessment of WTPs. Results indicate that the WTEEI is a valuable tool for evaluating WTP energy efficiency. While no definitive trend in WTEEI values was observed, the findings suggest the need for monitoring of energy use of WTPs and more research to better understand and improve the energy efficiency of these large‐scale infrastructure projects. By introducing a simple, intuitive and rapid assessment tool for evaluating energy efficiency in WTPs, this study addresses a critical gap in the water–energy field, namely, the evaluation of energy usage in WTPs and the identification of energy‐efficiency improvements for current and future WTPs.

Energy Efficiency Evaluation in Automotive Industry with AHP Method and Best&Worst Method

Energy is one of the most important elements for countries to exist in the competitive market in social, economic, technological and international areas. With the developing technology and increasing energy consumption, the importance of energy efficiency comes to the fore. In this context, the automotive industry, which is an important part of the industrial sector where energy is used intensively, was preferred in the study. Besides the automotive industry's need for energy, its interaction with other industries is the reason for preference. In the study, Energy Efficiency Strategy criterion weights in the Automotive Industry were calculated by using Multi-Criteria Decision Making methods. As a result of the literature research, nine main criteria and thirty-three sub-criteria were determined. The criteria weights of the Energy Efficiency Strategy in the automotive industry are analyzed separately with AHP, which is frequently used in the literature, and BEST & WORST, which is newly introduced to the literature. Comparing the solution results of the two methods is the aim of the study. In the light of the results obtained, it has been determined that the AHP and BEST & WORST methods give close results.

Research on Energy Efficiency and Carbon Emission Evaluation Methods of cogeneration Technology under the Background of Carbon Neutrality

This article delves into the energy efficiency evaluation methods and carbon emission evaluation methods of cogeneration technology. In terms of energy efficiency evaluation, the concept of energy efficiency and commonly used energy efficiency indicators of cogeneration systems were introduced, such as total energy efficiency, power efficiency, thermal energy efficiency, and fuel utilization efficiency. In terms of carbon emission evaluation, the concept of carbon emissions and commonly used carbon emission indicators for cogeneration systems were analyzed, such as carbon emissions per unit of power generation, carbon emissions per unit of thermal energy, and total carbon emissions. For these evaluation methods, different implementation steps and calculation formulas were introduced in detail, and their application scenarios and advantages and disadvantages were illustrated with examples. These evaluation methods help to evaluate the performance and environmental impact of cogeneration systems, providing scientific basis for relevant decision-making.

Multi-Objective set point optimization control of grate cooler considering energy efficiency evaluation

The grate cooler is a key piece of equipment for cooling cement clinker, whose parameter adjustment has a notable influence on energy consumption and equipment operation. This article proposes a multi-objective set-point optimization control method for the grate cooler control system, which takes into account energy efficiency evaluation. Based on the energy efficiency analysis of the grate cooler, the secondary air temperature, tertiary air temperature, and outlet clinker temperature are used as energy efficiency evaluation indicators, and a grate cooler energy efficiency evaluation model is established to construct a multi-objective function. After that, the grate pressure set point and fan current set point are optimized by utilizing the MOEA/D algorithm, and the predictive control method is combined to perform rolling optimization of the control parameters. Eventually, a simulation experiment is conducted based on the actual production data, and the simulation results demonstrate the feasibility and effectiveness of the optimized control method.

Carbon efficiency evaluation method for urban energy system with multiple energy complementary

Urban energy systems (UESs) play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization. In the context of the construction and operation strategy of UESs with multiple complementary energy resources, a comprehensive assessment of the energy efficiency is of paramount importance. First, a multi-dimensional evaluation system with four primary indexes of energy utilization, environmental protection, system operation, and economic efficiency and 21 secondary indexes is constructed to comprehensively portray the UES. Considering that the evaluation system may contain a large number of indexes and that there is overlapping information among them, an energy efficiency evaluation method based on data processing, dimensionality reduction, integration of combined weights, and gray correlation analysis is proposed. This method can effectively reduce the number of calculations and improve the accuracy of energy efficiency assessments. Third, a demonstration project for a UES in China is presented. The energy efficiency of each scenario is assessed using six operational scenarios. The results show that Scenario 5, in which parks operate independently and investors build shared energy-storage equipment, has the best results and is best suited for green and low-carbon development. The results of the comparative assessment methods show that the proposed method provides a good energy efficiency assessment. This study provides a reference for the optimal planning, construction, and operation of UESs with multiple energy sources.

Hybrid Technology Incorporated Into Colombian Heavy Oil Field Development Plan

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 213199, “Incorporating Hybrid Technology of CSS and Foam in Heavy Oil Field Development Plans: Practical Experiences and Lessons Learned,” by Romel A. Perez, SPE, Hector A. Rodriguez, and Jorge E. Romero, Ecopetrol, et al. The paper has not been peer reviewed. _ A research and development project was conducted to study the use of preformed foams to improve cyclic steam stimulation (CSS). The field results showed benefits in incremental oil production, improvements in energy efficiency, and reduction in carbon intensity. Based on those outcomes, and with the goal of extending the production life of mature assets, the hybrid technology of CSS plus foam improvements was incorporated into the heavy oil field development plans of the Middle Magdalena Valley (MMV) basin in Colombia. Pilot Results: 2019–2022 CSS maturity is one of the major challenges in the MMV. Many wells report more than 10 steam cycles, decreasing oil productivity, and a trend of shorter steam cycles (less than 10 months). Most injected steam drained the higher-flow-capacity intervals based on the permeability contrast within the pay zone and openhole completions. Therefore, the bullhead injection of preformed foam improvements implemented before the steam cycle was proposed as part of a conformance strategy. The main goal of the pilot test was to demonstrate the efficiency of the hybrid technology, extend the production life of steam cycles, increase oil recovery, and improve energy efficiency and carbon footprint. The CSS pilot was implemented in six wells of the Teca-Cocorna field (Fig. 1). Performance was evaluated in terms of incremental oil, carbon intensity, and energy efficiency. A similar approach was proposed to evaluate energy efficiency and greenhouse emissions of CSS and hybrid CSS based on numerical simulations and the performance of two wells in Block D-80 in China. By the end of this stage, an incremental oil of approximately 32,000 STB was confirmed. Only one well recorded almost 50% of the total incremental oil of the pilot, and one well was only evaluated for 6 months because of a mechanical failure. Incremental oil recoveries and geochemical analysis confirmed the potential of this hybrid steam method to target unswept zones in idle or marginal wells operating since the 1980s. Additionally, the Teca-Cocorna pilot reduced carbon intensity and improved energy efficiency by 56% and 54%, respectively. The reduction of the carbon intensity from 83 (baseline) to 46 kg CO2/STB represents an important achievement in terms of environmental benefits and highlights the fact that the volume of natural gas used to generate steam was optimized by using less gas by extending steam cycles to a minimum of 9 months. In other words, the CCS/foam cycle can produce as much oil as two CCS cycles in the pilot wells.

Evaluation of Energy Efficiency and Analysis of Influencing Factors of Company CW’s Manufacturing Workshops

In this work, the Slacks-Based Measure (SBM) model within Data Envelopment Analysis was employed toestablish a set of indicators for evaluating the energy efficiency of manufacturing workshops. The energy efficiency of 12 Company CW’s manufacturing workshops from 2016 to 2022 was assessed. The findings indicated that aside from a few workshops operating at the production frontier, the rest exhibit significant fluctuations in energy efficiency and generally low energy efficiency. Subsequently, a combined GRA-Tobit analysis model was introduced to identify factors influencing the energy efficiency of Company CW’s manufacturing workshops. Regression analysis revealed that technological investments, employee quality, workshop production scale, investment in clean energy, and the level of pollution control all significantly impact the energy efficiency of Company CW’s manufacturing workshops. By evaluating the energy efficiency of Company CW’s manufacturing workshops and studying their influencing factors, this research aids companymanagers in understanding the energy efficiency of the manufacturing process. It optimizes the combination of various production elements, thereby offering effective guidance for improving the energy efficiency issues of the company’s manufacturing workshops, which can contribute to enhancing the corporation’s overall energy efficiency.

Building energy efficiency assessment base on predict-center criterion under diversified conditions

With the rapid expanding of urban economy and population, how to reduce the energy consumption and improve energy efficiency of public buildings has become a key issue for energy conservation and urban development. However, due to the diversity of building usage condition, energy consumption data often has problems with nonlinearity, outliers, and diversity, which greatly reduce the accuracy of energy consumption prediction and energy conservation assessment. To overcome the above drawbacks, a regression prediction model of building energy consumption is designed, which cluster the same type of data characteristics to form a subset of equipment through Gaussian mixture clustering, and design the specific normalized adaptive loss function to determine the optimal control parameters of regression model. Furthermore, a novel predict-center energy efficiency evaluation criterion is proposed, and the cumulative distribution pattern is further statistically analyzed. Finally, the energy benchmark evaluation framework is proposed to determine the energy efficiency evaluation grade. Through comparative experimental analysis, it can be seen that the proposed prediction model can adapt to different types of building data, and have better prediction accuracy and convergence speed. The consistency and robustness of the benchmark evaluation framework and method are optimal.

The effect of living wall systems’ variables on the energy consumption of buildings

PurposeLiving walls (LWs), vegetated walls with an integrated growth layer behind, are being increasingly incorporated in buildings. Examining plant characteristics’ comparative impacts on LWs’ energy efficiency-related thermal behavior was aimed, considering that studies on their relative effects are limited. LWs of varying leaf albedo, leaf transmittance and leaf area index (LAI) were studied for Antalya, Turkey for typical days of four seasons.Design/methodology/approachDynamic simulations run by Envi-met were used to assess the plant characteristics’ influence on seasonal and orientation-based heat fluxes. After model calibration, a sensitivity analysis was conducted through 112 simulations. The minimum, mean and maximum values were investigated for each plant characteristic. Energy need (regardless of orientation), temperature and heat flux results were compared among different scenarios, including a building without LW, to evaluate energy efficiency and variables’ impacts.FindingsLWs reduced annual energy consumption in Antalya, despite increasing energy needs in winter. South and west facades were particularly advantageous for energy efficiency. The impacts of leaf albedo and transmittance were more significant (44–46%) than LAI (10%) in determining LWs’ effectiveness. The changes in plant characteristics changed the energy needs up to ca 1%.Research limitations/implicationsThis study can potentially contribute to generating guiding principles for architects considering LW use in their designs in hot-humid climates.Originality/valueThe plant characteristics’ relative impacts on energy efficiency, which cannot be easily determined by experimental studies, were examined using parametric simulation results regarding three plant characteristics.

Sustainable energy efficiency in China from the perspective of environmental development: A comprehensive analysis of regional disparities and policy implications

Global agreements have emerged in order to achieve carbon neutrality as the needs for renewable energy sources and carbon reduction continue to grow. To achieve the global carbon neutrality goals, China, one of the largest carbon emitters, must improve urban energy efficiency. Using a three-stage slacks-based measure (SBM) technique, this study analyses the total factor energy efficiency of 270 prefecture-level cities from 2011 through 2020. It tries to monitor and evaluate energy efficiency without taking into account variations in the outside environment. China's total factor energy efficiency shows an overall rising trend, despite significant regional variations. Improved energy efficiency levels can be attributed to technical advancements, while limitations in technology contribute to lower energy efficiency in certain areas. The study highlights the importance of considering external environmental factors in evaluating energy efficiency, able to avoid an overestimation of China's overall energy efficiency. It is noteworthy that the eastern region consistently outperforms the national average in terms of energy use efficiency. Even after taking environmental factors out of the equation, the central, west, and northeast regions still have worse energy efficiency and slower rates of growth. On this basis, from strengthening energy management and planning; facilitating cross-regional sharing of expertise; take targeted policy measures to adapt to the characteristics of the western and northeastern regions and put forward policy suggestions. These guidelines contribute to international energy cooperation and carbon reduction initiatives, while promoting sustainable energy development in China.

Evaluation of energy efficiency of thermoelectric energy generator system with heat pipes, solar tracker, Fresnel lens and nano-particle fluids

This study investigated the limits of electrical energy production from a thermoelectric generator in a high thermal efficiency system using pure water and nanofluids called aluminum oxide and titanium dioxide. It was aim to provide efficient thermal performance by using a Fresnel lens, solar glass tube, heat pipe and tracking system. Experimental measurements were made between 10:00 and 14:00 on July 26 and 27 in 2023. On each measurement day, the system containing pure water and a nanofluid was compared. The values of parameters such as temperature, solar radiation, wind speed and Thermoelectric Generator (TEG) open circuit voltage were measured instantaneously during the measurements. These data were used to calculate thermal resistance, electrical efficiency and output power. The results showed that the open circuit voltage increased with increasing solar radiation and, therefore, hot side temperature. The calculations showed that the highest open circuit voltage of 2.76 V was obtained with the mechanism using pure water as the working fluid. However, the obtained electrical efficiency ηe and output power Pmax values remained at 1.06 % and 1.058 W, respectively. Numerical and Artificial Neural Network (ANN) models are widely used to save time and cost in determining the optimal operating conditions of the TEG. Therefore, in addition to the experimental study, a numerical model consisting of TEG and a cooling system, and an Artificial Neural Network (ANN) model were also developed in this study. The average absolute errors for Computational Fluid Dynamics (CFD) and electrical results were obtained in the numerical model as 3.47 % and 2.97 %, respectively. In addition, the average absolute errors in the ANN model were obtained as 0.6 %, 0.5 % and 0.27 % for water, Al2O3 and TiO2 nanofluids, respectively.

Charting sustainable logistics on the 21st-Century Maritime Silk Road: a DEA-based approach enhanced by risk considerations through prospect theory

This study investigates the sustainable logistics potential of countries along the Maritime Silk Road (MSR), an essential element of the Belt and Road Initiative (BRI), against a backdrop of increasing global emphasis on sustainability and efficient trade practices. Addressing the gap in existing literature, it explores how strategic positioning influences countries’ logistics capabilities, integrating risk considerations and behavioral decision-making aspects into the assessment. Through a specialized Data Envelopment Analysis (DEA) model that incorporates Prospect Theory, this research provides a nuanced evaluation of economic performance, energy efficiency, infrastructure robustness, governance quality, and innovation capabilities. The analysis reveals significant findings, such as Vietnam’s outstanding economic efficiency, Indonesia’s notable achievements in sustainability and governance, and Malaysia’s balanced efficiency, which collectively enhance the MSR’s logistics framework. Additionally, India, Greece, Djibouti, and Kenya emerge as vital partners due to their diverse strengths. The introduction of a risk-aware DEA model, enriched with behavioral factors, marks a significant advancement in logistics assessment methodologies, offering a more comprehensive understanding of sustainable logistics practices along the MSR. The implications of this study are profound, providing valuable insights for policymakers, investors, and business leaders. It guides strategic decision-making, promoting sustainability in MSR trade activities while aligning with global eco-conscious practices and economic growth within the context of environmental stewardship and sustainable development. However, the research acknowledges limitations related to the indirect measurement of decision-makers’ psychological behavioral coefficients and the focus on efficiency metrics without extensive exploration of cultural, political, or legal factors. This work sets a new precedent in sustainable logistics research, encouraging future studies to incorporate direct behavioral data and qualitative factors for a more enriched evaluation. Its innovative approach not only contributes to the academic discourse on sustainable logistics but also offers practical tools for enhancing the MSR’s trade efficiency and sustainability.