bluuebunny/crossref_metadata_2025 huggingface dataset:
Biological Carbon Sequestration: From Deep History to the Present Day
Authors: Murphy Denis J.
Published: June 2024

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e., sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago, the ratio between emitted and sequestered carbon has varied considerably, with atmospheric CO2 levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil, and gas. Relatively low atmospheric CO2 levels were the norm for the past 10 million years, and during the past million years, they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO2 levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with the domestication of crops and livestock, leading to urbanisation and the development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO2 emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance, it is important to understand the roles of potential biological carbon sequestration systems and to devise strategies to facilitate net CO2 uptake; for example, via changes in the patterns of land use, such as afforestation, preventing deforestation, and facilitating agriculture–agroforestry transitions.
Environmental Factors Structuring Diatom Diversity of the Protected High Mountain Lakes in the Kaçkar Mountains National Park (Rize, Turkey)
Authors: Şahin Bülent , Barinova Sophia
Published: June 2024

The altitude of the habitat is one of the important regulators of species survival. Kaçkar Mountains National Park is located in the Eastern Black Sea region of Turkey. This is the first study on the benthic diatom flora of the high mountain lakes in Kaçkar Mountains National Park, which is situated between 2782 and 3075 m a.s.l. A total of 84 diatom species were identified from benthic communities of 15 habitats in summer (19 July, 28 August) and autumn (10 September) months of 2020. The genus Pinnularia (thirteen species) formed the basis of the taxonomic list, followed by Eunotia (five species), Navicula (five species), and Frustulia (four species) genera, respectively. The waters in all the studied lakes were fresh, low-saline, with low-alkaline or circumneutral pH and organically uncontaminated, as evidenced by prevailed bioindicator groups. Statistical methods and comparative floristic results confirm the role of the lake altitude for the diatom species distribution. The species richness of the studied lakes was higher in lakes with lower altitudes. The statistical approach also revealed the potential for an increase in the number of species in high mountain lakes if the study of the diatom flora of the Kachkar Mountains National Park is continued and the species composition of the lakes is replenished. Further studies will be needed to continue exploring this pattern. To protect studied high mountain lakes, their ecological conditions must be constantly monitored in the Kaçkar Mountains National Park.
Voices from Graduate School and the Workforce: Identified Student Outcomes from Completing a Multi-Semester Undergraduate Research Experience Capstone
Authors: Colclasure Blake C. , Alai Arian , Quinn Kristina , Granberry Tyler , Doyle Erin L. , Durham Brooks Tessa
Published: June 2024

Recent reforms in undergraduate science education have highlighted the need for student-centered learning that challenges students to take ownership of the scientific process through conducting authentic research. As such, Undergraduate Research Experiences (UREs) have become more prevalent in higher education. However, extensive variations in the structures, durations, and contexts of UREs exist and long-term implications are not well documented. We used the Social Cognitive Career Theory to guide our exploration of student outcomes from completing a required three-semester capstone URE at a predominantly undergraduate institution located in the Midwest, United States. We sought to answer two central research questions: (1) What skills and competencies do alumni perceive to have gained from completing the URE capstone, and (2) What is the impact of the URE capstone on alumni success in the workforce and/or graduate school? We conducted in-depth, one-on-one interviews with 16 alumni who recently completed their undergraduate research capstone and who were currently in a science-based career or attending graduate school. Results indicate long-term benefits from URE capstones and are described through three primary themes: technical skill acquisition and future application, soft skill acquisition and future application, and scientific pursuits.
Multi-Level Leadership Development Using Co-Constructed Spaces with Schools: A Ten-Year Journey
Authors: Youngs Howard , Ogram Maggie
Published: June 2024

Leadership in both theory and practice usually emphasizes a person and a position. There has been a shift from emphasizing the senior level of organizational roles, to include the middle level and other sources of leadership. Nomenclature has emerged over time to reflect this, for example, collective, distributed, shared, and collaborative leadership. Another understanding of leadership needs to be added, one that does not first emphasize a person or position, instead incorporating process and practices, weaving through all levels and sources of leadership. This additional understanding has implications for how leadership development is constructed and facilitated. Over the last ten years, the authors have journeyed with groups of schools, using an emerging co-constructed approach to leadership development. The journey is relayed across three seasons. The first is the grounding of collaborative practices through inquiry, informed by a two-phase research project. The second focuses on adaptation and resilience during the COVID-19 pandemic, whereas the third delves deeper into what sits behind prevalent practices that may enable and hinder student achievement. Our narrative over time shows that leadership development can be shaped through a continual cycle of review, reflection, and co-construction, leading to conditions for transformation across multiple levels and sources of leadership.
Effects of the “High Impact Leadership for School Renewal” Project on Principal Leadership, School Leadership, and Student Achievement
Authors: Ma Xin , Shen Jianping , Reeves Patricia L. , Wu Huang , Roberts LaSonja , Zheng Yunzheng , Chen Qianqian
Published: June 2024

In this study, we designed an educational experiment to evaluate the High Impact Leadership for School Renewal project’s impact on principal leadership, school leadership, and student achievement. Principals in the experimental group reported statistically significantly greater improvement in principal leadership than their counterparts in the control group (Hedge’s g of 0.73), but teachers in the experimental and control groups showed no difference in their ratings of principal leadership. Teachers in the experimental group reported statistically significantly more improvement in school leadership than their counterparts in the control group (Hedge’s g of 0.53 on the scale of Orientation to School Renewal and 0.58 on the scale of Learning-Centered School Leadership), but principals in the two groups reported no difference in the growth in school leadership. Schools in the experimental group showed statistically significantly larger annual growth in English language arts proficiency rate (2.05 percentage points more annually). The implications of the findings were discussed in the context of leadership development programs for school improvement.
Relationship between Parenting Educational Styles and Well-Being in Families with Autistic Children: A Systematic Review
Authors: Benseny Delgado Elena , Peñate Castro Wenceslao , Díaz Megolla Alicia
Published: June 2024

The prevalence of diagnosed cases of autism has increased rapidly, which has raised interest in studying the variables related to the well-being of these families. The purpose of this paper is to review the recent literature on other variables related to family well-being, such as parenting styles. We conducted a systematic review using the PRISMA check list and bias assessment with the aim of analyzing if the concepts of autism, well-being and parenting style are related. We screened 755 references from relevant databases like Scopus, Pubmed, PscyInfo EBSCO, Web of Science and Dialnet, updated on May 2024. Sixteen full text articles and abstracts were read. It was identified that the authoritative parenting style, as well as those based on warmth, establishing relationships and emotional bonding, and low expressed emotion were positively related to family well-being. On the other hand, authoritarian, permissive and overprotective styles, as well as critical, punishing and training-based, were negatively associated with well-being and quality of family life.
A Review of Endogenous Security Research
Authors: Liu Xiaoyu , Wang Haizhou , Li Cuixia
Published: June 2024

The development of society has deepened the application of the Internet in production and daily life. At the same time, network security risks are becoming increasingly severe. For the security problems faced in cyberspace, most of the traditional defenses are currently focused on blocking the discovered vulnerabilities. However, these methods not only rely on prior knowledge of vulnerabilities but also fail to address the security issues brought about by the protection program itself. In view of this, endogenous security, which emphasizes the importance of not relying on a priori knowledge and not bringing in new security problems, has received increasing attention. This review provides a detailed introduction to endogenous security and its related issues, which is lacking in the field of network security. Firstly, this paper outlines the detrimental effects of vulnerabilities, identifies issues within moving target defense, and contrasts it with mimic defense. Additionally, the concepts, models, principles, and application scenarios of endogenous security are introduced. Finally, the challenges encountered by this technology are comprehensively summarized, and potential future development trends are further explored.
Enhanced Day-Ahead Electricity Price Forecasting Using a Convolutional Neural Network–Long Short-Term Memory Ensemble Learning Approach with Multimodal Data Integration
Authors: Wang Ziyang , Mae Masahiro , Yamane Takeshi , Ajisaka Masato , Nakata Tatsuya , Matsuhashi Ryuji
Published: June 2024

Day-ahead electricity price forecasting (DAEPF) holds critical significance for stakeholders in energy markets, particularly in areas with large amounts of renewable energy sources (RES) integration. In Japan, the proliferation of RES has led to instances wherein day-ahead electricity prices drop to nearly zero JPY/kWh during peak RES production periods, substantially affecting transactions between electricity retailers and consumers. This paper introduces an innovative DAEPF framework employing a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) model designed to predict day-ahead electricity prices in the Kyushu area of Japan. To mitigate the inherent uncertainties associated with neural networks, a novel ensemble learning approach is implemented to bolster the DAEPF model’s robustness and prediction accuracy. The CNN–LSTM model is verified to outperform a standalone LSTM model in both prediction accuracy and computation time. Additionally, applying a natural logarithm transformation to the target day-ahead electricity price as a pre-processing technique has proven necessary for higher prediction accuracy. A novel “policy-versus-policy” strategy is proposed to address the prediction problem of the zero prices, halving the computation time of the traditional two-stage method. The efficacy of incorporating a suite of multimodal features: areal day-ahead electricity price, day-ahead system electricity price, areal actual power generation, areal meteorological forecasts, calendar forecasts, alongside the rolling features of areal day-ahead electricity price, as explanatory variables to significantly enhance DAEPF accuracy has been validated. With the full integration of the proposed features, the CNN–LSTM ensemble model achieves its highest accuracy, reaching performance metrics of R2, MAE, and RMSE of 0.787, 1.936 JPY/kWh, and 2.630 JPY/kWh, respectively, during the test range from 1 March 2023 to 31 March 2023, underscoring the advantages of a comprehensive, multi-dimensional approach to DAEPF.
Empirical Assessment of the Efficiency of Poland’s Energy Transition Process in the Context of Implementing the European Union’s Energy Policy
Authors: Brodny Jarosław , Tutak Magdalena , Grebski Wes
Published: June 2024

This article addresses one of the contemporary economy’s most challenging endeavors: the energy transition. Specifically, the aim of the study was to assess the effectiveness of Poland’s energy transition process between 2004 and 2021. A comprehensive approach is employed to analyze Poland’s energy transition process, focusing on the effectiveness of implementation through the Energy Transition Effectiveness Index. This methodology incorporates four dimensions, namely energy security, economic considerations, climate impact, and social aspects, each characterized by 22 sub-indices. The research methodology employs a two-tiered approach based on the multi-criteria decision making methodology. The EDAS method is utilized to determine the indices’ values, while the CRITIC, equal weights, and statistical variance methods and Laplace’s criterion are employed to ascertain sub-indices values and dimension weights, particularly useful for decision making under uncertainty. Moreover, the relationship between these indices, the Energy Transition Effectiveness Index, and Poland’s Gross Domestic Product is explored. By evaluating Poland’s energy transition effectiveness from 2004 to 2021 and comparing the results with other European Union countries, it becomes evident that the effectiveness varies over time. Despite encountering economic and social challenges during the energy sector’s transformation, Poland exhibits positive progress in its energy transition efforts, outperforming certain European Union counterparts. However, there is a pressing need to intensify efforts to curtail emissions and enhance renewable energy utilization. The European Union’s support and coordination are deemed crucial in facilitating these endeavors, alongside fostering the wider adoption of best practices among member states. The developed methodology stands as a valuable tool for ongoing evaluation of transformation processes across European Union nations.
Energetic, Exergetic, and Techno-Economic Analysis of A Bioenergy with Carbon Capture and Utilization Process via Integrated Torrefaction–CLC–Methanation
Authors: Cutillo Enrico Alberto , Tregambi Claudio , Bareschino Piero , Mancusi Erasmo , Continillo Gaetano , Pepe Francesco
Published: June 2024

Bioenergy with carbon capture and storage (BECCS) or utilization (BECCU) allows net zero or negative carbon emissions and can be a breakthrough technology for climate change mitigation. This work consists of an energetic, exergetic, and economic analysis of an integrated process based on chemical looping combustion of solar-torrefied agro-industrial residues, followed by methanation of the concentrated CO2 stream with green H2. Four agro-industrial residues and four Italian site locations are considered. Depending on the considered biomass, the integrated plant processes about 18–93 kg h−1 of raw biomass and produces 55–70 t y−1 of synthetic methane. Global exergetic efficiencies ranged within 45–60% and 67–77% when neglecting and considering, respectively, the valorization of torgas. Sugar beet pulp and grape marc required a non-negligible input exergy flow for the torrefaction, due to the high moisture content of the raw biomasses. However, for these biomasses, the water released during drying/torrefaction and CO2 methanation could be recycled to the electrolyzer to eliminate external water consumption, thus allowing for a more sustainable use of water resources. For olive stones and hemp hurd, this water recycling brings, instead, a reduction of approximately 65% in water needs. A round-trip electric efficiency of 28% was estimated assuming an electric conversion efficiency of 40%. According to the economic analysis, the total plant costs ranged within 3–5 M€ depending on the biomass and site location considered. The levelized cost of methane (LCOM) ranged within 4.3–8.9 € kgCH4−1 but, if implementing strategies to avoid the use of a large temporary H2 storage vessel, can be decreased to 2.6–5.3 € kgCH4−1. Lower values are obtained when considering hemp hurd and grape marc as raw biomasses, and when locating the PV field in the south of Italy. Even in the best scenario, values of LCOM are out of the market if compared to current natural gas prices, but they might become competitive with the introduction of a carbon tax or through government incentives for the purchase of the PV field and/or electrolyzer.
Scaling Energy Transfer in Ball Mills: A Scale-Agnostic Approach through a Universal Scaling Constant
Authors: Doroszuk Błażej , Bortnowski Piotr , Ozdoba Maksymilian , Król Robert
Published: June 2024

Ball mills are widely used for size reduction in mineral processing, but effective scaling from laboratory to industrial scale remains challenging. This study introduces a novel scaling constant approach to replicate energy transfer to ore during milling across different scales by adjusting rotational speed and grinding medium size distribution. The scaling constant encapsulates parameters like the number of balls per working area, rotational speed, and an average ball’s maximum potential and kinetic energies. Experiments were conducted using a laboratory ball mill with interchangeable drum sizes (300, 400, and 500 mm) and a Design of Experiments methodology. Statistical analysis revealed that the scaling constant was more effective at maintaining consistent specific energy and energy per rotation across scales than size reduction, especially in dry milling. Wet milling results showed no significant differences in all metrics across scales. The dominant charge motion shifted from centrifuging to cascading as the mill diameter increased, highlighting the complex scaling dynamics. While the scaling constant shows promise for maintaining energy utilization, additional factors like charge motion and particle breakage mechanisms should be considered. The findings provide insights for improving ball mill design and optimization in mineral processing.
On the Development of a Near-Shore Pivoting Wave Energy Converter
Authors: Giannini Gianmaria , Zavvar Esmaeil , Ramos Victor , Calheiros-Cabral Tomás , Iglesias Isabel , Taveira-Pinto Francisco , Rosa-Santos Paulo
Published: June 2024

Numerous offshore wave energy converter (WEC) designs have been invented; however, none has achieved full commercialization so far. The primary obstacle impeding WEC commercialization is the elevated levelized cost of energy (LCOE). Consequently, there exists a pressing need to innovate and swiftly diminish the LCOE. A critical challenge faced by WECs is their susceptibility to extreme wave loads during storms. Promising concepts must demonstrate robust design features to ensure resilience in adverse conditions, while maintaining efficiency in harnessing power under normal sea states. It is anticipated that the initial commercial endeavors will concentrate on near-shore WEC technologies due to the cost advantages associated with proximity to the coastline, facilitating more affordable power transmission and maintenance. In response, this manuscript proposes a pioneering near-shore WEC concept designed with a survivability mode that is engineered to mitigate wave loads during severe sea conditions. Moreover, prior investigations have highlighted favorable resonance properties of this novel concept, enhancing wave power extraction during recurrent energetic sea states. This study employs numerical and physical modelling techniques to evaluate wave loads on the proposed WEC. The results indicate a remarkable 65% reduction in wave loads on the moving floater of the WEC during a range of sea states under the implemented survivability mode.
Effect of Plasma Gas Type on the Operation Characteristics of a Three-Phase Plasma Reactor with Gliding Arc Discharge
Authors: Stryczewska Henryka Danuta , Komarzyniec Grzegorz , Boiko Oleksandr
Published: June 2024

Three-phase gliding arc discharge reactors are devices in which it is difficult to maintain stable plasma parameters, be it electrically, physically, or chemically. The main cause of plasma instability is the source, which is freely burning arcs in a three-phase system. In addition, these arcs burn at low currents and are intensively cooled, further increasing their instability. These instabilities translate into the electrical characteristics of the plasma reactor. The analysis for the four gases nitrogen, argon, helium, and air shows that the type of plasma-generating gas and its physical parameters have a strong influence on the operational characteristics of the plasma reactor. Current–voltage, power and frequency characteristics of the plasma reactor were plotted experimentally. Characteristics obtained in this way make it possible to determine the areas of effective operation of the plasma reactor, and to estimate the quality of the generated plasma. Based on the characteristics obtained, a method of controlling the plasma parameters can be developed.
Uncalcined Zn/Al Carbonate LDH and Its Calcined Counterpart for Treating the Wastewater Containing Anionic Congo Red Dye
Authors: Rani Kuppusamy Manjula , Palanisamy Pachagoundanpalayam Nachimuthugounder , Kowshalya Vennila Nagamuthu , Tamilvanan Ayyasamy , Prabakaran Rajendran , Kim Sung Chul
Published: June 2024

In this investigation, Zn/Al carbonate layered double hydroxide (ZAC-LDH) and its derived material on calcination were synthesized for removing the anionic azo dye Congo red (CR) from wastewater. Numerous factors were methodically investigated, including temperature, adsorbent dosage, pH, starting Dye Concentration (DC), and contact time. The CR elimination percentage dropped as the initial DC increased from 25 mg/L to 100 mg/L at 30 °C for uncalcined LDH, and from 97.96% to 89.25% for calcined LDH. The pH analysis indicates that the highest level of dye removal was recorded within the acidic pH range through the electrostatic attraction mechanism. The sorption kinetics analysis results demonstrated that the pseudo-second-order kinetic model exhibited a stronger fit to both uncalcined LDH and CZA-LDH, with the maximum correlation coefficient value. The Van’t Hoff plots indicate the spontaneous nature of the physisorption process with a negative ΔG° (<−20 kJ/mol), while the endothermic adsorption process exhibited a positive ΔH°. The X-ray diffraction of calcined LDH reveals a significant intercalation of CR dye molecules, both prior to and following adsorption, showcasing a distinctive memory effect. The Brunauer–Emmett–Teller (BET) gas sorption measurements were performed to support the mesoporous nature of ZAC-LDH and CZA-LDH. The FTIR spectrum confirms the interaction of dye molecules on the surface of uncalcined and calcined LDH. These findings emphasize the efficacy of both the synthesized LDHs in removing CR dye, with CZA-LDH demonstrating superior efficiency compared to uncalcined LDH in the context of CR removal from wastewater.
Microgrid Fault Detection Method Based on Lightweight Gradient Boosting Machine–Neural Network Combined Modeling
Authors: Lu Zhiye , Wang Lishu , Wang Panbao
Published: June 2024

The intelligent architecture based on the microgrid (MG) system enhances distributed energy access through an effective line network. However, the increased paths between power sources and loads complicate the system’s topology. This complexity leads to multidirectional line currents, heightening the risk of current loops, imbalances, and potential short-circuit faults. To address these challenges, this study proposes a new approach to accurately locate and identify faults based on MG lines. Initially, characteristic indices such as fault voltage, voltage fundamentals at each MG measurement point, and extracted features like peak voltage values in specific frequency bands, phase-to-phase voltage differences, and the sixth harmonic components are utilized as model inputs. Subsequently, these features are classified using the Lightweight Gradient Boosting Machine (LightGBM), complemented by the bagging (Bootstrap Aggregating) ensemble learning algorithm to consolidate multiple strong LightGBM classifiers in parallel. The output classification results of the integrated model are then fed into a neural network (NN) for further training and learning for fault-type identification and localization. In addition, a Shapley value analysis is introduced to quantify the contribution of each feature and visualize the fault diagnosis decision-making process. A comparative analysis with existing methodologies demonstrates that the LightGBM-NN model not only improves fault detection accuracy but also exhibits greater resilience against noise interference. The introduction of the bagging method, by training multiple base models on the initial classification subset of LightGBM and aggregating their prediction results, can reduce the model variance and prevent overfitting, thus improving the stability and accuracy of fault detection in the combined model and making the interpretation of the Shapley value more stable and reliable. The introduction of the Shapley value analysis helps to quantify the contribution of each feature to improve the transparency and understanding of the combined model’s troubleshooting decision-making process, reduces the model’s subsequent collection of data from different line operations, further optimizes the collection of line feature samples, and ensures the model’s effectiveness and adaptability.
Second-Order Sliding-Mode Control Applied to Microgrids: DC & AC Buck Converters Powering Constant Power Loads
Authors: Monsalve-Rueda Miguel , Candelo-Becerra John E. , Hoyos Fredy E.
Published: June 2024

Microgrids are designed to connect different types of AC and DC loads, which require robust power controllers to achieve an efficient power transfer. However, the effects of both AC and DC disturbances in the same type of controller make achieving stability a design challenge, especially in coupled systems where disturbances affect both the upstream and downstream in the microgrid. This paper presents an analysis of a second-order sliding-mode control (SOSMC) applied to a microgrid with direct-current (DC) and alternating-current (AC) power converters. The aim is to simulate the second-order sliding-mode control with buck converters that feed constant DC–DC and DC–AC power loads. The controller was tested in consideration of a unique sliding surface facing external disturbances, such as variations in the frequency of AC converters, sudden changes in upstream voltages, and constant power loads (CPL). The influence of the gain values (K) on the controller was also analyzed. The results show that the controller is robust regarding its sensitivity to external disturbances and steady-state error. However, the importance of the constant “K” in the model states that there exist K-limit values where if “K” is too low, a slowdown is presented, and the response against disturbances can be critical, and if is too high, an overshoot is presented in the output voltage.
An Intelligent Regression-Based Approach for Predicting a Geothermal Heat Exchanger’s Behavior in a Bioclimatic House Context
Authors: Díaz-Longueira Antonio , Rubiños Manuel , Arcano-Bea Paula , Calvo-Rolle Jose Luis , Quintián Héctor , Zayas-Gato Francisco
Published: June 2024

Growing dependence on fossil fuels is one of the critical factors accelerating climate change, a global concern that can destabilize ecosystems and economies worldwide. In this context, renewable energy is emerging as a sustainable and environmentally responsible alternative. Among the options, geothermal energy stands out for its ability to provide heat and electricity consistently and efficiently, offering a feasible solution to reduce the carbon footprint and promote more sustainable development in a globalized economy. In this work, a machine learning approach is proposed to predict the behavior of a horizontal heat exchanger from a bioclimatic house. First, a correlation analysis was conducted for optimal feature selection. Then, several regression techniques were applied to predict the output temperature of the geothermal exchanger. Satisfactory prediction results were obtained in different scenarios over the whole dataset. Also, a significant correlation between several sensors was concluded.
Comparative Analysis of Deep Learning Methods for Fault Avoidance and Predicting Demand in Electrical Distribution
Authors: Schröder Karla , Farias Gonzalo , Dormido-Canto Sebastián , Fabregas Ernesto
Published: June 2024

In recent years, the distribution network in Chile has undergone various modifications to meet new demands and integrate new technologies. However, these improvements often do not last as long as expected due to inaccurate forecasting, resulting in frequent equipment changes and service interruptions. These issues affect project investment, unsold energy, and penalties for poor quality of supply. Understanding the electricity market, especially in distribution, is crucial and requires linking technical quality standards with service quality factors, such as the frequency and duration of interruptions, to understand their impact on regulated distribution to customers. In this context, a comparative study will be carried out between Long Short-Term Memory (LSTM) and transformer architectures, with the aim of improving the sizing of distribution transformers and preventing failures when determining the nominal power of the transformer to be installed. Variables such as voltages and operating currents of transformers installed between 2020 and 2021 in the Valparaíso region, Chile, along with the type and number of connected customers, maximum and minimum temperatures of the sectors of interest, and seasonality considerations will be used. The compilation of previous studies and the identification of key variables will help to propose solutions based on error percentages to optimise the accuracy of transformer sizing.
Well Logging Reconstruction Based on a Temporal Convolutional Network and Bidirectional Gated Recurrent Unit Network with Attention Mechanism Optimized by Improved Sand Cat Swarm Optimization
Authors: Wang Guanqun , Teng Haibo , Qiao Lei , Yu Hongtao , Cui You , Xiao Kun
Published: June 2024

Geophysical logging plays a very important role in reservoir evaluation. In the actual production process, some logging data are often missing due to well wall collapse and instrument failure. Therefore, this paper proposes a logging reconstruction method based on improved sand cat swarm optimization (ISCSO) and a temporal convolutional network (TCN) and bidirectional gated recurrent unit network with attention mechanism (BiGRU-AM). The ISCSO-TCN-BiGRU-AM can process both past and future states efficiently, thereby extracting valuable deterioration information from logging data. Firstly, the sand cat swarm optimization (SCSO) improved by the variable spiral strategy and sparrow warning mechanism is introduced. Secondly, the ISCSO’s performance is evaluated using the CEC–2022 functions and the Wilcoxon test, and the findings demonstrate that the ISCSO outperforms the rival algorithms. Finally, the logging reconstruction method based on the ISCSO-TCN-BiGRU-AM is obtained. The results are compared with the competing models, including the back propagation neural network (BPNN), GRU, and BiGRU-AM. The results show that the ISCSO-TCN-BiGRU-AM has the best performance, which verifies its high accuracy and feasibility for the missing logging reconstruction.
Site Selection for Offshore Wind Power Farms with Natural Disaster Risk Assessment: A Case Study of the Waters off Taiwan’s West Coast
Authors: Ning Fang-Shii , Pien Kuang-Chang , Liou Wei-Jie , Cheng Tsung-Chi
Published: June 2024

This research examines the risk of natural disasters for offshore wind turbines together with their potential wind energy capacity to help the site selection of offshore wind power farms. Through evaluations of expert questionnaires, we use the fuzzy analytic hierarchy process to weight how natural disasters damage the sub-assemblies of an offshore wind turbine, then obtain the natural disaster risk assessment model, and finally utilize ArcGIS Pro 3.2 to map the potential wind farm sites for the waters off Taiwan’s west coast. We identify that typhoons are the most threatening type of disaster to generators, rotor blades, and rotor hubs; earthquakes are the most threatening to towers; and lightning is the most threatening to transformers. For the whole wind turbine, wind is ironically the most threatening natural disaster, followed by lightning, sea waves, and then earthquakes. Lastly, we examine the results by overlapping the offshore wind farms developed and planned in Taiwan, which coincide with locations in relatively low risk and high wind speed areas.
Fluid Chemical and Isotopic Signatures Insighting the Hydrothermal Control of the Wahongshan-Wenquan Fracture Zone (WWFZ), NE Tibetan Plateau
Authors: Li Tingxin , Lu Rui , Xie Wenping , Zhu Jinshou , Liu Lingxia , Lin Wenjing
Published: June 2024

Compared to the southern Tibetan Plateau, the northern part has been regarded as relatively lacking geothermal resources. However, there is no lack of natural hot springs exposed in beads along large-scale fracture systems, and research on them is currently limited to individual hot springs or geothermal systems. This paper focuses on the Wahongshan-Wenquan Fracture Zone (WWFZ), analyzes the formation of five hydrothermal activity zones along the fracture zone in terms of differences in hot water hydrochemical and isotopic composition, and then explores the hot springs’ hydrothermal control in the fracture zone. The results show that the main fractures of the WWFZ are the regional heat control structures, and its near-north–south- and near-east–west-oriented fractures form a fracture system that provides favorable channels for deep hydrothermal convection. Ice and snow meltwater from the Elashan Mountains, with an average elevation of more than 4,500 m above sea level, infiltrates along the fractures, and is heated by deep circulation to form deep geothermal reservoirs. There is no detectable mantle contribution source heat to the hot spring gases, and the heat source is mainly natural heat conduction warming, but the “low-velocity body (LVB)” in the middle and lower crust may be the primary heat source of the high geothermal background in the area. The hot springs’ hydrochemical components show a certain regularity, and the main ionic components, TDS, and water temperature tend to increase away from the main rupture, reflecting the WWFZ controlling effect on hydrothermal transport. In the future, the geothermal research in this area should focus on the hydrothermal control properties of different levels, the nature of fractures, and the thermal contribution of the LVB in the middle and lower crust.
Techno-Economic Assessment of Molten Salt-Based Concentrated Solar Power: Case Study of Linear Fresnel Reflector with a Fossil Fuel Backup under Saudi Arabia’s Climate Conditions
Authors: Aljudaya Ahmed , Michailos Stavros , Ingham Derek B. , Hughes Kevin J. , Ma Lin , Pourkashanian Mohamed
Published: June 2024

Concentrated solar power (CSP) has gained traction for generating electricity at high capacity and meeting base-load energy demands in the energy mix market in a cost-effective manner. The linear Fresnel reflector (LFR) is valued for its cost-effectiveness, reduced capital and operational expenses, and limited land impact compared to alternatives such as the parabolic trough collector (PTC). To this end, the aim of this study is to optimize the operational parameters, such as the solar multiple (SM), thermal energy storage (TES), and fossil fuel (FF) backup system, in LFR power plants using molten salt as a heat transfer fluid (HTF). A 50 MW LFR power plant in Duba, Saudi Arabia, serves as a case study, with a Direct Normal Irradiance (DNI) above 2500 kWh/m2. About 600 SM-TES configurations are analyzed with the aim of minimizing the levelized cost of electricity (LCOE). The analysis shows that a solar-only plant can achieve a low LCOE of 11.92 ¢/kWh with a capacity factor (CF) up to 36%, generating around 131 GWh/y. By utilizing a TES system, the SM of 3.5 and a 15 h duration TES provides the optimum integration by increasing the annual energy generation (AEG) to 337 GWh, lowering the LCOE to 9.24 ¢/kWh, and boosting the CF to 86%. The techno-economic optimization reveals the superiority of the LFR with substantial TES over solar-only systems, exhibiting a 300% increase in annual energy output and a 20% reduction in LCOE. Additionally, employing the FF backup system at 64% of the turbine’s rated capacity boosts AEG by 17%, accompanied by a 5% LCOE reduction. However, this enhancement comes with a trade-off, involving burning a substantial amount of natural gas (503,429 MMBtu), leading to greenhouse gas emissions totaling 14,185 tonnes CO₂ eq. This comprehensive analysis is a first-of-a-kind study and provides insights into the optimal designs of LFR power plants and addresses thermal, economic, and environmental considerations of utilizing molten salt with a large TES system as well as employing natural gas backup. The outcomes of the research address a wide audience including academics, operators, and policy makers.
The Relationship between Transparency Obligations and Foreign Investment in Renewable Energies: Realising the Potential Role of IIAs
Authors: Qian Xuming , Ghaziani Mohammad Akefi
Published: June 2024

The global deployment of renewable energies has taken off and calls for a continuous increase in foreign investments and cooperation, particularly because many states cannot cover the costs and technological requirements of the energy transition on their own. Therefore, there should be policies and legal frameworks in place to protect and thereby promote foreign investments. International Investment Agreements (IIAs) can, ceteris paribus, contribute to this goal. These agreements contain a set of obligations that protect foreign investments against possible discriminatory or arbitrary conduct of the host states. This includes transparency obligations that can help to create a level playing field for national and foreign renewable energy investors. Unfortunately, the concept of transparency, and its inherent implications, has not been clearly defined to date, and its relationship with renewable energy investments is still under investigation. Therefore, it is important to realise the prevailing transparency obligations under IIAs, and the best practices that can better meet the particular requirements of renewable energy investments. Using a qualitative approach, this article intends to pursue this goal by providing an overview of the concept of transparency, exploring its status in the context of fair and equitable treatment (FET), and analysing favourable transparency clauses in the light of renewable energy investment considerations.
Multi-Physical Field Analysis and Optimization Design of the High-Speed Motor of an Air Compressor for Hydrogen Oxygen Fuel Cells
Authors: Ren Xiaojun , Feng Ming , Liu Jinliang , Du Rui
Published: June 2024

The hydrogen oxygen fuel cell is a power source with significant potential for development. The air compressor provides ample oxygen for the fuel cell, and as a key component of the air compressor, the performance of the motor greatly impacts the efficiency of the fuel cell. In order to enhance the system performance of high-speed permanent magnet motors, optimization was conducted on the motor’s geometric dimensions to minimize rotor loss and maximize power density, taking into account the comprehensive constraints of electromagnetic and mechanical properties. The finite-element method was employed to analyze the motor’s performance, conducting a multi-physical field analysis that included electromagnetic field, rotor loss, and mechanical strength analysis, as well as temperature field analysis. Aiming at the problem of high temperature rise in high-speed motor winding, the influence of the cooling water flow rate on the winding temperature rise was analyzed and simulated. Based on the analysis results, the minimum cooling water flow rate was obtained. According to the optimized design results, a prototype of an 18 kW, 100,000 rpm motor was manufactured, and the efficiency and temperature rise were tested. The experimental results verify the correctness and effectiveness of the optimal design.
Evaluation of Biogas Production from Swine Manure Using a UASB Reactor (Upflow Anaerobic Sludge Blanket) with Long-Term Operation
Authors: Mosquera Ana Marcela , Delgado Juan Martín , Ramón Aura Alexandra , Vásquez Juan Esteban , Peñuela Mariana
Published: June 2024

To meet Colombia’s energy needs by 2050, a total installed capacity of 42 MW across its power generation infrastructure is required. To achieve this, transitioning to cleaner energy sources, such as biomass—a non-conventional renewable energy—is necessary. Biomass is a promising renewable source for thermal and electrical energy production. This study researched the production of biogas from swine manure using a UASB reactor to valorize this waste. Swine manure was collected every 20 days from a pig farm with a capacity of 200 sows, located in Santa Rosa de Osos, Antioquia. The flow rate was increased three times (1.30 L d−1, 1.62 L d−1, and 2.08 L d−1) to reduce the hydraulic retention time (HRT) and enhance biogas production. The volatile and total solids, chemical oxygen demand (COD), alkalinity, and biogas composition were measured over one year. The proposed system achieved 87.40% COD remotion from the feed stream and generated a yield of 507 mLCH4 gVS−1, with an HRT of 19 days and an OLR of 4.27 gCOD L−1 d−1. The reactor produced biogas with a CH4 content of 67.7%, CO2 content of 18.1%, and H2S content of 1413 ppm. This study highlights the effectiveness of the UASB reactor for biogas production using swine manure as a substrate.
Investments in Electricity Distribution Grids: Strategic versus Incremental Planning
Authors: Giannelos Spyros , Zhang Tai , Pudjianto Danny , Konstantelos Ioannis , Strbac Goran
Published: June 2024

The ongoing electrification of the transport sector is expected to cause an increase in electricity demand and, therefore, trigger significant network investments to accommodate it. This paper focuses on investment decision-making for electricity distribution grids and specifically on the strategic and incremental investment network planning approaches. In particular, the former involves network planning with the consideration of a long-term multi-stage study horizon, as opposed to a shorter–term view of the future that applies to the latter case. An investment analysis that is carried out underlines the economic savings generated from adopting a strategic investment perspective over an incremental one. These economic savings are achieved from the fact that the associated fixed investment costs are incurred only once in the horizon under strategic planning. On the other hand, incremental planning involves a series of network reinforcement decisions, thereby incurring the fixed cost multiple times. In addition, sensitivity analyses that are carried out capture the effect of key parameters, such as investment cost, discount rate and investment delay, on the generated economic savings.
Influence of Coherent Vortex Rolls on Particle Dynamics in Unstably Stratified Turbulent Channel Flows
Authors: Zaza Domenico , Iovieno Michele
Published: June 2024

This work investigates the dynamics of heavy particles dispersed in turbulent channel flows under unstable thermal stratification conditions using point-particle direct numerical simulations (PP-DNS), to quantify the influence of large-scale coherent vortex rolls, arising from the combined effects of shear and buoyancy, on the spatial distribution and preferential sampling behavior of inertial particles. We examined three particle Stokes numbers (St+=0.6,60,120) and two friction Richardson numbers, Riτ=0.272 and Riτ=27.2, which exemplify the regimes below and above the critical condition for vortex roll formation, respectively. The results indicate that the flow reorganization into large-scale longitudinal vortices significantly alters the topological features of small scales in the near-wall region impinged by the thermal plumes, resulting in a prevalence of vorticity-dominated topologies. The interplay between this phenomenon and the tendency of particles to preferentially sample strain-dominated topologies leads to a distinctive asymmetric particle distribution in the near-wall planes. Inertial particles markedly accumulate in the strain-dominated regions where the coherent thermal plumes emerge from the walls, while avoiding the vorticity-dominated impingement zones. This peculiar particle response to the vortex rolls is most pronounced when the particle response time matches the characteristic timescale of the large-scale coherent motions in the cross-stream planes.
Enhancing Injectivity in Lithuanian Hydrocarbon Reservoirs through Wettability-Altering Surfactant Injection
Authors: Dangi Shankar Lal , Pal Mayur
Published: June 2024

Improved and efficient recovery methods are investigated as possible candidates to arrest the production decline and to improve the injection capacity in hydrocarbon fields in Lithuania. The data show that the Cambrian reservoirs in Lithuania are mixed to oil-wet in nature, which results in poor water-flooding efficiency. Wettability alteration could help in improved water injection and, at the same time, it could help recover additional oil from the residual oil saturation zone of the reservoir. In this paper, a screening exercise is conducted to help alter reservoir wettability, improve water injection efficiency, and to improve oil recovery. Analytical and machine-learning supported methods are used for screening. Based on the screening results, dilute surfactant-based injection techniques are suggested as a potential method to improve injectivity and, thereby, recovery from the field. An initial experimental analysis targets the wettability of the rock from the field, followed by testing for wettability-altering surfactants. Based on the findings of the screening study and experimental analysis, it is recommended that we initiate a core flooding experimental program to investigate wettability changes and enhance injection and recovery from the field.