Energy Production Industry Research Articles

Statistical investigation of heat transfer efficiency on a ternary nanoflow over a stretching surface

Ternary hybrid nanofluids offer significant advantages in heat transfer due to their enhanced thermal conductivity compared to traditional fluids. Investigating their flow behavior over expanding surfaces can contribute to the development of more efficient heat exchangers and cooling systems in the electronics, energy production, and transportation industries. This paper presents a detailed analysis of the flow and thermal transfer characteristics of a ternary hybrid nanofluid (SiO2–Cu–Al2O3/H2O) over a radially stretching surface, utilizing both numerical techniques (Keller Box method) and statistical techniques. Furthermore, the model includes factors like convective heat transport, radiation, internal fluid friction, and suction. Similarity transformations transform the governing equations for fluid flow and heat transfer into a system of nonlinear ordinary differential equations. Then the equations are solved numerically using the Keller Box method with the aid of MATLAB software. Additionally, we have employed statistical techniques such as correlation analysis, probable error estimation, and multivariate regression to validate and ensure the accuracy of the numerical outcomes. Parameter ranges for Biot number, radiation, unsteadiness, Eckert number, and energy generation parameter are 0.1 ≤ Mp ≤ 0.7, 0.1 ≤ Ks ≤ 1.5, 0.2 ≤ Ps ≤ 0.8, 0.1 ≤ EN ≤ 0.4, 0.5 ≤ RN ≤ 2, 1≤ BT ≤ 2.5, 0.1 ≤ Hsc ≤ 0.7 and found to significantly impact heat transfer behavior within these bounds. This study utilizes 3D surface plots to visualize the influence of key parameters on engineering quantities. R squared values show that the data strongly match the regression model. The findings demonstrate excellent concordance between the predicted values and the actual Nusselt number and skin friction measurements. Biot number has a very strong correlation with heat transfer, with minimal chance of error. And the same is evidenced by the correlation matrix and multiple regression analysis. Eckert number also exhibits a negative correlation with the Nusselt number. This translates to a situation where increasing Eckert number directly leads to a decrease in the rate of heat transfer, with no margin for error. Energy generation parameter demonstrates a negative correlation with heat transfer. However, there's a slight possibility of error, with an estimated error percentage of around 0.0017.

Designing China's environmental tax schemes from the perspective of differential tax rates

The Environmental Protection Tax Law of the People's Republic of China was promulgated in 2018. However, it is uncertain whether the tax rates defined under the law are reasonable. Environmental tax reform would help the government improve the law's emission reduction effect. This paper aims to design tax schemes from the perspective of differential tax rates and propose environmental tax reform strategies. To support this goal, we adopted a directional distance function, meta-frontier analysis, and an exponential attenuation model to construct a differential tax rate model. Next, starting with the current differential provincial tax rates (scheme B), we proposed three-level differential tax rates, in which the adjusted provincial tax rates (scheme P), differential sector tax rates (scheme S), and differential province–sector tax rates (scheme P–S). Then, we analyzed three new tax schemes and proposed two step-by-step reform strategies. We selected SO2, NOx, and CO2 for empirical analysis. We found that in the short term, the government should prioritize scheme P and set more effective tax rates for SO2 and NOx. In the long term, the government should implement scheme P–S to consider both regional heterogeneity and industrial heterogeneity within a province. Specific measures should set a high tax rate for the light industry category and a low tax rate for energy production and heavy industry category. In addition, we propose that China should include a carbon tax in the scope of its environmental taxes. Our research provides valuable guidance for China's future environmental tax reform.

Exploring the potential of anti-bacterial and conductive ZnO–Al2O3/SPES proton exchange membrane applied in MFC for sustainable energy generation and sugar beet industry effluent treatment

This research introduces a novel approach wherein a sulfonated polyethersulfone (SPES) membrane is modified using bio-synthesized ZnO–Al2O3 nanoparticles (ZANPs). This modified membrane serves as a proton exchange membrane (PEM) within a dual-chamber microbial fuel cell (MFC) for energy production and sugar beet industry effluent treatment. We fabricated ZANPs/SPES membranes through a phase inversion process, varying the ZANPs loadings from 0.5 to 4.0 wt%. The ZANPs underwent analysis using a range of methods, including FTIR, EDS, SEM, and XRD, and the PEMs were thoroughly studied through several analyses, such as FTIR, SEM, EDS, AFM, water contact angle, water uptake, zeta potential, oxygen permeability, ion exchange capacity, proton conductivity, COD removal, coulombic efficiency, and anti-bacterial efficiency. According to the findings, ZANPs exhibited significant benefits for modified PEMs, such as improved proton conductivity, ion exchange capacity, and anti-bacterial capability. The MFC utilizing PEM with 4.0 wt% of ZANPs (ZANPs4.0/SPES) demonstrated a peak power output of 142.75 mW/m2 and a maximum current of 413 mA/m2. The values observed were notably elevated compared to the MFC that used commercial Nafion 117. The ZANPs4.0/SPES also had a maximum ion exchange capacity of 2.75 meq/g and 3.91 mS/cm proton conductivity among the fabricated PEMs compared to Nafion117, which only had 1.07 mS/cm proton conductivity and ion exchange capacity of 0.89 meq/g. Modified membranes improved COD removal from sugar beet industry effluent by up to 98.22 % and had a higher coulombic efficiency of up to 39.26 %. The anti-bacterial efficiency of ZANPs4.0/SPES was over 97 % against two types of bacteria. As per the research findings, it is confirmed that the ZANPs/SPES membranes can function efficiently in dual-chamber MFCs.

Integration of Large Language Models with microcontrollers to optimize industrial automation processes

Integration of Artificial Intelligence (AI) systems into microcontroller-based industrial automation systems can reshape the manufacturing, transportation, and energy production industries. This study explores different Large Language Model (LLM) applications in microcontroller based industrial automation processes; such as real-time control, adaptive decision-making, advanced sensor integration. The study also discusses challenges related to LLM implementation in microcontrollers and proposes potential solutions for overcoming them to drive innovation within modern industries.

Durability analysis of sustainable mortars with biomass fly ash as high-volume replacement of Portland cement

Utilization of various supplementary cementitious materials was in the last decades considered beneficial for the replacement of the energy-intensive Portland cement to meet sustainable targets. However, structural changes in energy production and heavy industry in Europe significantly limit the availability of coal fly ash and blast furnace slag for blended cement production. On the other hand, the increasing production of biomass ash (BA) presents not only challenges for its disposal but also new opportunities for the concrete industry. In this paper, the durability of cement composites containing up to 70 wt% of BA as Portland cement (PC) replacement was analyzed, taking into consideration also microstructure and mechanical properties. The experimental results showed a preservation of good mechanical performance up to the 30 wt% limit. The freeze-thaw resistance was not affected significantly up to the 40 wt% BA dosage during the first 300 cycles. The analyzed composites also exhibited a good overall resistance to alkali silica reaction- and sulfate-induced expansion up to the 50 wt% PC replacement. BA can thus be considered as a prospective future alternative to coal fly ash and blast furnace slag to meet the sustainable development goals in the building industry.

How digital government mediate the influence of fossil fuels on green innovation: Evidence from China's a-share industrial enterprises

China's rapid economic growth has resulted in a heavy reliance on fossil fuels, necessitating effective government intervention to facilitate their green transformation within the industrial sector. Therefore, a comprehensive investigation into the impact of mineral resource and fossil fuel dependence (ED) on the green transformation of Chinese enterprises, alongside the role of digital governance systems, holds paramount importance. This study delves into the influence of ED on firms' green technology innovation (FGI) using data sourced from A-share industrial enterprises listed on China's Shanghai and Shenzhen stock exchanges during the period from 2011 to 2021. Additionally, it examines the internal mechanisms facilitated by digital government, and provides insights into the heterogeneity observed from the perspectives of enterprises' industry classifications and sizes. The following conclusions are drawn: (1) ED significantly impedes the enhancement of green technology innovation levels among listed industrial enterprises, and this finding remains robust across multiple testing methods. (2) ED demonstrates varying inhibitory effects on firms' green technology innovation, with the most pronounced impact observed in the energy production and supply industry and the mining industry, and a relatively weaker effect observed in manufacturing enterprises. Furthermore, the inhibitory effect of fossil energy dependence on green technology innovation is observed to be stronger in small-scale enterprises compared to their larger counterparts. (3) The advancement of the digital economy notably mitigates the inhibitory effect of fossil energy dependence on firms' green technology innovation. (4) ED primarily diminishes the level of green innovation by reducing the stringency of government environmental regulations, hindering regional marketization, and impeding the industrial structure's upgrade.

Investigation of the mechanical work during ultrasonic fatigue loading using pulsed time-resolved X-ray diffraction.

In the energy production and transportation industries, numerous metallic structures may be subjected to at least several billions of cycles, i.e. loaded in the very high cycle fatigue domain (VHCF). Therefore, to design structures in the VHCF domain, a reliable methodology is necessary. One useful quantity to characterize plastic activity at the microscopic scale and fatigue damage evolution is the mechanical work supplied to a material. However, the estimation of this mechanical work in a metal during ultrasonic fatigue tests remains challenging. This paper aims to present an innovative methodology to quantify this. An experimental procedure was developed to estimate the mechanical work from stress and total strain evolution measurements during one loading cycle with a time accuracy of about 50 ns. This was achieved by conducting time-resolved X-ray diffraction coupled to strain gauge measurements at a synchrotron facility working in pulsed mode (single-bunch mode).

International Functional Economic Accounting and Calculation of Energy by Equivalent on the BRICS+ Platform

According to the forecast of the International Energy Agency (International Energy Agency), global demand for electricity by 2040 will increase by 70%. The global energy production and distribution industry must be restructured. The solution to the problem will be the transition to energy efficient technologies and international functional accounting and calculation of all types of energy in terms of energy equivalent on the BRICS + platform using digital platforms.

Can industrial intelligence promote green transformation? New insights from heavily polluting listed enterprises in China

The main challenge for sustainable development in China lies in promoting the green transformation of enterprises. Industrial intelligence provides a novel avenue for this shift towards sustainability. This study uses a database of Chinese A-share listed companies from 2012 to 2019, focusing on 813 high-polluting firms, to examine the impact of industrial intelligence on green transformation through a two-way fixed effects model. The findings reveal that industrial intelligence significantly facilitates the green transition of businesses; however, these effects substantially vary across various businesses. Honestly, state-owned enterprises, manufacturing sectors, and energy production and supply industries documented more pronounced impacts. Government interference hinders the positive effects of industrial intelligence on green transformation, while marketization enhancement has a positive moderating effect. In contrast, the financial market's moderating effect is negligible. It suggests that governments would increase the use of industrial intelligence, reduce government involvement, optimize financial markets, and enhance marketization to encourage green development in firms.

A novel FFA‐GWO‐based optimization paradigm for solving a dynamic economic emission dispatch in power plants

AbstractThermal power plants are the primary components of the electrical energy production industry. These plants come with certain challenges such as the production of harmful gases causing environmental pollution. This adds to global warming issues that are dangerous for the earth's ecosystem. Another crucial aim is the least cost operation of these power plants. Combining both of these results in the formulation of the Dynamic Economic Emission Dispatch (DEED). This is a multi‐objective, constrained, dynamic, complex, and non‐linear optimization problem. Traditional methods are insufficient to undertake the complexities of DEED due to challenges such as high computational requirements and local optimal solutions. Hence, for obtaining an optimal or near‐optimal solution to such a complex problem, a metaheuristic technique is greatly needed. Metaheuristic techniques offer several benefits to solving complex problems such as being robust, efficient, and overall, less affected by an increase in problem size. In this work, a novel hybrid Firefly Optimization Algorithm (FFA)—Grey Wolf Optimization Algorithm (GWO) has been proposed to solve the DEED problem. The complexity of the DEED problem is undertaken by involving constraints like power limits, power balance, and transmission losses. FFA‐GWO was applied on 5, 10, and 15‐unit standard test systems to meet 24‐h load demands. The optimal costs obtained in 5, 10, and 15‐unit standard test systems are 32264$, 1394212.615$, and 465373.448$ respectively. The comparison of results shows that the proposed framework surpasses the other methodologies in terms of reduced fuel cost and emissions.

Phase transformations in the alumina-forming austenitic stainless-steel Fe-20Cr-30Ni-2Nb-5Al during creep at 750ºC 45 MPa

Heat resistant steels are widely used in the energy production industry. However, pushing their operating temperatures higher means reducing component lifetimes due to the acceleration of the time-dependent processes of deformation and oxidation. The goal of next-generation alloy design is therefore to increase the temperature capability of these materials, while simultaneously maintaining low component costs. The creep lifetime of the newly developed alumina-forming-austenitic stainless steels can be improved by controlling the precipitation and microstructural evolution during creep. The current research aims to further the knowledge on the transformation pathways of Fe-20Cr-30Ni-2Nb-5Al (at.%) during aging and creep at 750ºC / 45 MPa. It was found that the initial γ-γ’-Laves (aged) microstructure transformed to a γ-γ’-Laves-β-α'-σ (crept) microstructure as various phases rejected or attracted different elements. Atom probe tomography (APT) and transmission electron microscopy (TEM) were employed to evaluate the composition and structure of the matrix and various inter- and intra-granular precipitates and to understand their formation mechanisms. The formation of σ-CrFe was related to dislocation slip on {111}, with Laves-σ co-precipitation growing along the <111> directions. Meanwhile grain boundary α'-Cr precipitation was related to the rejection of Cr, mainly by β-NiAl. Interestingly a few nm thin but up to mm long Laves phase plates formed along annealing twin boundaries, however, a significant effect on the creep properties associated to their formation was not observed.

Analysis of embodied carbon emissions and carbon sequestration in Tibetan Plateau-Case study of Tibet and Qinghai

The Tibetan Plateau is one of the most important carbon sinks, while it is facing with huge pressure of carbon emission in the process of urbanization, and the inter-regional trade activities lead to the carbon emission structure to be more complex. To facilitate the realization of carbon neutrality, it is required to figure out the carbon sequestration capacity and the carbon emissions caused by socio-economic activities of the Tibetan Plateau. This study adopted the net primary productivity (NPP) remote estimation model to evaluate carbon sequestration capacity and utilized a multi-regional input–output analysis framework combined with a structural decomposition analysis model for embodied carbon emission evaluation of Tibet and Qinghai to identify the carbon emission characteristics in 2012 and 2017. The results reflect that Tibet had great potential for carbon neutrality, but Qinghai had a slight carbon deficit from both the production and consumption perspectives. The carbon emission flow patterns shown that Tibet was basically a net emission importer, and Qinghai mainly imported net emissions from northern China like Inner Mongolia, Henan, and Hebei, and exported emissions to southern China like Shanghai, Zhejiang, and Guangdong. The energy production and supply industries were the largest carbon emission sources and the major contributors of emission growth for Tibet and Qinghai. The gross capital formation have induced about 75% of the consumption-based emissions in plateau in both 2012 and 2017. The increased emissions were mainly driven by changes in average consumption structure, which promoted the emissions increased by 34.70% and 23.21% for Tibet and Qinghai, respectively. It can be concluded that the main task to achieve the target of carbon reduction is to change the energy structure of the Tibetan Plateau into a cleaner structure to reduce dependence on high-carbon products from other provinces and promote green development all over the country.

Rethinking the equity and efficiency of carbon tax: A novel perspective

Previous research has generally concluded that carbon tax is regressive, despite its efficacy in reducing emissions. This paper takes a deeper dive to explore the validity of this assertion and proposes alternative approaches to enhance the efficiency of carbon tax without revenue recycling. Our argument asserts that the efficiency of a carbon tax can be determined by adjusting tax coverage. Furthermore, we find that taxing solely on energy production industries rather than the entire industry can significantly improve mitigation efficiency. Our findings also indicate that the carbon footprint and the emissions per unit cost for a given energy source account for the observed regressivity. Specifically, the wealthy consume commodities with higher carbon footprints, an indirect and invisible factor. However, it is important to note that the poor allocate a significantly greater proportion of their budget toward energy consumption, which is a visible and direct concern. Based on these findings, we provide several policy implications.

A synthesis of approaches to support integrated assessments of hazards for the emerging Blue Economy

Growth in offshore blue economies is predicted to accelerate as emerging food and energy production industries look to expand into these environments. Operating in novel environments for these industries inherently fosters uncertainty in outcomes generated by a complex suite of hazards, some of which are unknown prior to deployment. Faced with such uncertainty, a precautionary, flexible, and cross-disciplinary (integrated) approach is recommended to optimize the potential for hazards to be identified in a timely, comprehensive, and robust manner, and mitigated. However, relevant disciplines – such as aquaculture production, marine engineering, and marine renewable energy design, and associated interactions with society and the environment – often evolve with their siloed techniques and lexicons. Here we first provide an overview of selected discipline-specific approaches to hazard analysis as a first step in a pathway that can generate a holistic synthesis of hazards to and from multiple emerging sectors in novel environments. Despite challenges of applying these individual methods to cross-disciplinary projects for emerging industries, we then identify where disciplines share methodological approaches and where opportunities exist to develop integrated methods. With a growing focus on sustainable economic growth and optimizing the use of ocean space through multi-use, our review highlighted that the emerging offshore Blue Economy could benefit from the development of a flexible, integrated approach to identify and assess hazards in a comprehensive, robust and useful manner for successful planning, development, and operations.

Analysing the waste management, industrial and agriculture greenhouse gas emissions of biomass, fossil fuel, and metallic ores utilization in Iceland

With Iceland's CAP 2020, the country aims significant improvement in the state of its environment through reduction in greenhouse gas (GHG) emission especially in energy production and small industry, waste management, ships and ports, land transport, and agriculture by 2030. Considering this ambition, this study queries whether the consumptions of domestic materials i.e., DMC (especially metallic ores, biomass, and fossil fuels) exhibit differential impact on (i) aggregated greenhouse gas emissions i.e., GHG, (ii) waste management greenhouse gas emission i.e., WGHG, (ii) industrial greenhouse gas emission i.e., IGHG, and (iv) agriculture greenhouse gas emission i.e., AGHG during the period 1990 to 2019. By using Fourier function approaches, the investigation establishes that metallic ores DMC spur GHG, but biomass and fossil fuel DMC mitigate GHG in the long run. Additionally, biomass DMC mitigates AGHG and WGHG by respective elasticities of 0.04 and 0.025 in the long run. While IGHG is significantly reduced by fossil fuel DMC with elasticity of 0.18 in the long run, the AGHG and WGHG are unaffected by the consumption of fossil fuel domestic materials. Moreover, metallic ores DMC spurs only IGHG by elasticity of ∼0.24. The overall evidence shows the need for more stringent material use and resource circularity (especially for metallic ores and fossil fuels) for the country to stay on course of the CAP 2020 and maintain environmental sustainability.

Does nuclear energy reduce carbon emissions despite using fuels and chemicals? Transition to clean energy and finance for green solutions

Green power conversion is the shift away from traditional fuels towards clean energy sources such as nuclear power plants, hydroelectric dams, wind farms, and solar panels. This research examines the impact of clean energy demand and green financing on reducing carbon emissions in 29 economies in Europe and Asia from 2007 to 2020. The study used a two-step differenced GMM estimator for the available data set spanning 2007 to 2020. The study found that rising demand for nuclear power helps to achieve a carbon-neutral agenda, but insufficient funding for renewable energy leads to higher carbon emissions. The research suggests increasing investment in nuclear energy and green financing can improve regional environmental quality. The study found a causal link between fuel imports, nuclear power and regional growth. It also determined that fuel imports, chemical use, green financing and the need for nuclear energy will likely impact regional environmental quality. The research recommends allocating more resources toward innovation to boost energy efficiency and expanding investment in renewable and nuclear energy production industries via green finance. The study also highlights the need to encourage the development of renewable energy sources to cut carbon emissions and establish a sustainable society.

An Overview of the State of the Art and Challenges in the Use of Gelling and Thickening Agents to Create Stable Thermal Energy Storage Materials

Building cooling and heating, solar-powered energy production, energy recovery, and other energy-consuming industries have all seen an increase in the use of cold/hot latent thermal energy storage (LH-TES). Through energy recovery, LH-TES that uses phase-change materials (PCMs) as a storage medium helps to close the energy supply and demand gap and raises the possibility of energy savings. However, the stability, thermal, physical, and chemical properties of the PCM play a major role in how effectively it can be used. In recent years, adding gelling and thickening agents (GTAs) has gained popularity apart from the nanoparticles (NPs) and nucleating triggers (NTs), particularly for the creation of stable PCMs. Therefore, the current work’s goal is to provide an overview of how GTAs are used in the process of developing reliable PCMs for TES applications. It has been found that using GTAs not only increased stability but also decreased sedimentation, leakage, and the supercooling degree (SCD). It was noted that the addition of a GTA with a weight percentage of 2–15% resulted in excellent stability with a negligible leakage rate and latent heat reduced by 3.6–35% after only 200 cycles. Furthermore, PCMs for solar-thermal and building heating systems in the medium-temperature range (21–61 °C) were mostly studied for their performance with GTAs, but no study for a cool TES application was reported. Most works have studied inorganic PCM components with GTAs, and a few reports are available for paraffin. However, the GTA blending resulted in reduced thermal performance due to a decrease in thermal conductivity, latent heat, and a rise in viscosity. Further, NTs and NPs with small amounts were seeded into the PCM-GTA for eradicating the SCD with enhanced TC and accelerated energy transfer.

The Tie that Binds: The Trials of US–Canada Energy Infrastructure

The subject of International Energy does not get any bigger than the bilateral energy trade between the United States and Canada. Our two countries share a singular geopolitical endowment: the world's longest and highest value trading border—bounded by two oceans—where not a shot has been fired in anger since the War of 1812. We share unusual natural resources and common institutions: (1) a continent with multiple productive hydrocarbon basins and renewable energy resources, including hydroelectric, solar, and wind; (2) English common law with strong Constitutional and judicial protections for private property; (3) federal governmental systems; and (4) highly competitive energy production and transport infrastructure industries. With such institutional foundations, our two nations exhibit by far the world's oldest and most extensive pipeline infrastructure systems and dozens of international power transmission links. The long‐time lack of military conflict, stability of institutions of governance, and highly competitive business infrastructure generally has always been the source of great industrial productivity in providing low‐cost energy for consumers and businesses in North America.

Self-Driven UVC–NIR Broadband Photodetector with High-Temperature Reliability Based on a Coco Palm-Like MoS2/GaN Heterostructure

One of the dominant sources of energy production is burning fossil fuels (coal, natural gas, and petroleum), which emit different optical traces (ultraviolet to infrared). A self-driven broadband optical detector is essential for monitoring these optical signals in harsh environments because it is challenging to apply additional bias under high-temperature conditions. However, the existing optical detectors are constrained to operate at room temperature or require additional bias and present practical limitations in high-temperature operating environments. This study introduces a unique coco palm-like MoS2/GaN heterojunction-based self-powered photodetector that operates in the broadband spectral range from ultraviolet-C to near-infrared. The fabricated detector displays the highest responsivity of 379 mA W–1 under no applied bias at room temperature. The photodetector also exhibits consistent performance at high operating temperatures (up to 250 °C). Under self-driven conditions, the device possesses the highest responsivity of 360 mA W–1 at 250 °C. The heterostructure-based device also achieves the best responsivity of 2.8 × 106 mA W–1 at 8 V applied bias and has remarkable low-light detection abilities down to 9 femto-Watts. The high-temperature-operated self-driven broadband photodetector opens up possibilities for in situ monitoring of optical radiations from diverse industrial processes in challenging conditions and for optical signature-generating systems in the automobile, aerospace, and energy production industries.

Janus ceramic membranes with asymmetric wettability for high-efficient microbubble aeration

Microbubbles have drawn increasing attention due to their wide applications in many fileds such as energy production, environmental remediation, and chemical and petrochemical industries. How to facilely and efficiently produce microbubbles is still keeps a great challenge. Herein, we report a Janus ceramic membrane with asymmetric wettability for high-efficient microbubble aeration. The pristine hydrophilic ceramic membrane was firstly modified by 1H,1H,2H,2H-perfluorooctyltrimethoxysilane (PFTMS), and then functionalized through single-surface deposition of polydopamine (PDA) to achieve a Janus ceramic membrane with asymmetric surface wettability. Results highlight that the introduction of DA with suitable concentration and modification time is highly efficient for the control of surface wettability. Compared to the pristine and hydrophobic modified ceramic membranes, the use of the Janus ceramic membrane allows a uniform microbubble-in-liquid dispersion system at relatively low transmembrane pressure, and as a result, the dissolved oxygen concentration is effectively increased by 1.3 times. The bubble size is stable at about 160 μm in a 24 h continuous run, and the Janus ceramic membrane shows excellent stability. Our study demonstrates the effectiveness of fabricating Janus ceramic membranes and the advantages of Janus ceramic membranes in microbubble aeration.