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Records Added in September 2023
Records added in September 2023
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Showing records 181 to 205 of 230. [First] Page: 1 5 6 7 8 9 10 Last
Analysis of Heat Transfer of the Gas Head Cover of Diaphragm Compressors for Hydrogen Refueling Stations
Shengdong Ren, Xiaohan Jia, Jiatong Zhang, Dianbo Xin, Xueyuan Peng
September 20, 2023 (v1)
Keywords: diaphragm compressor, heat transfer enhancement, simulation model, temperature distribution
The inadequate ability to dissipate heat of the gas head cover of the diaphragm compressor will result in its excessive temperature, which will put the operation of the hydrogen filling station at risk for safety issues and raise operating costs. This paper analyzed the structure and the heat transfer characteristics of the gas head cover, along with the relevant heat transfer boundaries, based on which a finite element simulation model of the temperature distribution was established. A test rig for the temperature test of a 22 MPa diaphragm compressor was built to validate this simulation model. The results indicated that the simulated temperatures agree well with the measured values, and the deviation is within 9.1%. Further, this paper proposed two head cover structures for enhancing the heat transfer according to the temperature field distribution characteristics, and the simulation and experimental verification were carried out, respectively. The findings demonstrate that the meth... [more]
Failure Risk Prediction Model for Girth Welds in High-Strength Steel Pipeline Based on Historical Data and Artificial Neural Network
Ke Wang, Min Zhang, Qiang Guo, Weifeng Ma, Yixin Zhang, Wei Wu
September 20, 2023 (v1)
Keywords: failure risk, girth welds, pipeline, sample selection
Pipelines are the most economical and sensible way to transport oil and gas. Long-distance oil and gas pipelines consist of many steel pipes or pipe fittings joined by welded girth welds, so girth welds are an essential part of pipelines. Owing to the limitations of welding conditions and the complexity of controlling weld quality in the field, some defects are inevitably present in girth welds and adjacent weld areas. These defects can lead to pipeline safety problems; therefore, it is necessary to perform failure risk assessment of pipeline girth welds. In this study, an artificial neural network model was proposed to predict the failure risk of pipeline girth welds with defects. Firstly, many pipeline girth weld failure cases, pipeline excavation, and inspection data were collected and analyzed to determine the main factors influencing girth weld failure. Secondly, a spatial orthogonal optimization method was used to select training samples for the artificial neural network model to... [more]
Evaluation of the Capsaicinoid Extraction Conditions from Mexican Capsicum chinense Var. Mayapan with Supercritical Fluid Extraction (SFE)
Kevin Alejandro Avilés-Betanzos, Matteo Scampicchio, Giovanna Ferrentino, Manuel Octavio Ramírez-Sucre, Ingrid Mayanin Rodríguez-Buenfil
September 20, 2023 (v1)
Keywords: antioxidant capacity, capsaicinoids, Capsicum chinense, supercritical fluid extraction
Capsaicin (Cp) is a secondary metabolite produced by the Capsicum plant family. This molecule exhibits various biological properties such as antioxidant capacities, anti-obesogenic effects, and antidiabetic properties, among others. However, conventional extraction methods for Cp present several disadvantages including toxicity, extraction time, and low purity. Therefore, the utilization of supercritical fluid extraction techniques represents a viable option for obtaining highly pure and low-toxicity oleoresins (capsaicin-rich extracts). This approach involves the use of CO2 in the supercritical state and finds applicability in the pharmaceutical, food, and cosmetic industries. The Capsicum chinense variety from the Yucatán Peninsula is a crop with significant economic impact in the region, due to having the highest concentrations of Cp in Mexico. This significant characteristic is attributed to its adaptation to the unique conditions (climate, soil, solar radiation, humidity) of the s... [more]
Special Issue “Process Safety in Coal Mining”
Feng Du, Aitao Zhou, Bo Li
September 20, 2023 (v1)
Subject: Other
As an important natural resource, coal plays a critical role in social and economic development [...]
Research and Development of Anti-High-Pressure Sealing Material and Its Bonding Performance
Shigang Hao, Xianzhong Li, Tao Wu, Weilong Zhou, Jinhao Zhang
September 20, 2023 (v1)
Subject: Materials
Keywords: bond performance, fiber materials, fractal dimension, high-pressure sealing materials, hydraulic fracturing
To solve the problem of the field application of downhole hydraulic fracturing technology due to the difficulty in sealing holes, this study analyzes the influence of special cement, expansion agents, stabilizers, and fiber material on basic properties, such as the setting time, fluidity, and compressive strength of high-pressure sealing materials through systematic tests based on a summary of conventional sealing materials. It was determined that with 20−30% special cement and 4% expansion agent added, and a fiber material length of 8 mm and volume of 1%, the high-pressure sealing material had high fluidity and a large expansion rate, demonstrating early strength. The bond performance of the high-pressure sealing material was tested through the variable-angle shear test. The relationship between the fractal dimension of the coal-rock mass around the borehole and the bond performance of the high-pressure sealing material was also explored.
Intelligent Control of Wastewater Treatment Plants Based on Model-Free Deep Reinforcement Learning
Oscar Aponte-Rengifo, Mario Francisco, Ramón Vilanova, Pastora Vega, Silvana Revollar
September 20, 2023 (v1)
Keywords: intelligent control, model-free deep reinforcement learning, reusing policy, waste water treatment plant
In this work, deep reinforcement learning methodology takes advantage of transfer learning methodology to achieve a reasonable trade-off between environmental impact and operating costs in the activated sludge process of Wastewater treatment plants (WWTPs). WWTPs include complex nonlinear biological processes, high uncertainty, and climatic disturbances, among others. The dynamics of complex real processes are difficult to accurately approximate by mathematical models due to the complexity of the process itself. Consequently, model-based control can fail in practical application due to the mismatch between the mathematical model and the real process. Control based on the model-free reinforcement deep learning (RL) methodology emerges as an advantageous method to arrive at suboptimal solutions without the need for mathematical models of the real process. However, convergence of the RL method to a reasonable control for complex processes is data-intensive and time-consuming. For this rea... [more]
Development of a Novel Multi-Modal Contextual Fusion Model for Early Detection of Varicella Zoster Virus Skin Lesions in Human Subjects
McDominic Chimaobi Eze, Lida Ebrahimi Vafaei, Charles Tochukwu Eze, Turgut Tursoy, Dilber Uzun Ozsahin, Mubarak Taiwo Mustapha
September 20, 2023 (v1)
Subject: Biosystems
Keywords: chickenpox, deep-learning, mixed-scale hierarchical attention (MSHA), shingles, skin lesions
Skin lesion detection is crucial in diagnosing and managing dermatological conditions. In this study, we developed and demonstrated the potential applicability of a novel mixed-scale dense convolution, self-attention mechanism, hierarchical feature fusion, and attention-based contextual information technique (MSHA) model for skin lesion detection using digital skin images of chickenpox and shingles lesions. The model adopts a combination of unique architectural designs, such as a mixed-scale dense convolution layer, self-attention mechanism, hierarchical feature fusion, and attention-based contextual information, enabling the MSHA model to capture and extract relevant features more effectively for chickenpox and shingles lesion classification. We also implemented an effective training strategy to enhance a better capacity to learn and represent the relevant features in the skin lesion images. We evaluated the performance of the novel model in comparison to state-of-the-art models, incl... [more]
Performance Analysis of Organic Rankine Cycle with Internal Heat Regeneration: Comparative Study of Binary Mixtures and Pure Constituents in Warm Regions
Muhammad Ehtisham Siddiqui, Eydhah Almatrafi, Usman Saeed
September 20, 2023 (v1)
Keywords: binary mixtures, exergy performance, heat transfer, organic Rankine cycle, specific net power output, warm regions
There are various organic compounds that can be utilized in the organic Rankine cycle as working fluids. The selection of a suitable working fluid is complicated due to the large number of options and factors affecting the choice, such as thermodynamic properties, environmental impact, cost, etc. This study evaluates seven different pure organic compounds and twenty-one of their binary zeotropic mixtures as potential working fluids for the organic Rankine cycle powered by a heat source at 200 °C. The pure organic fluids show higher exergy efficiency, higher specific net power output, and lower heat exchange area requirements compared to the binary mixtures. Among the pure fluids, RE347mcc performs the best in terms of exergy efficiency, followed by neopentane, isopentane, and pentane. Cyclopentane exhibits the highest power production capacity per unit mass flow rate of the working fluid. Two mixtures, pentane/Novec 649 and cyclopentane/Novec 649, showed significantly higher exergy eff... [more]
YOLOv7-Based Anomaly Detection Using Intensity and NG Types in Labeling in Cosmetic Manufacturing Processes
Seunghyo Beak, Yo-Han Han, Yeeun Moon, Jieun Lee, Jongpil Jeong
September 20, 2023 (v1)
Keywords: anomaly detection, deep learning, object detection, YOLOv7
The advent of the Fourth Industrial Revolution has revolutionized the manufacturing sector by integrating artificial intelligence into vision inspection systems to improve the efficiency and quality of products. Supervised-learning-based vision inspection systems have emerged as a powerful tool for automated quality control in various industries. During visual inspection or final inspection, a human operator physically inspects a product to determine its condition and categorize it based on their know-how. However, the know-how-based visual inspection process is limited in time and space and is affected by many factors. High accuracy in vision inspection is highly dependent on the quality and precision of the labeling process. Therefore, supervised learning methods of 1-STAGE DETECTION, such as You Only Look Once (YOLO), are utilized in automated inspection to improve accuracy. In this paper, we proposed a labeling method that achieves the highest inspection accuracy among labeling met... [more]
Plant-Derived Essential Oils and Aqueous Extract as Potential Ingredients for a Biopesticide: Phytotoxicity in Soybean and Activity against Soybean Mosaic Virus
María Evangelina Carezzano, Pablo Gastón Reyna, Efrén Accotto, Walter Giordano, María de las Mercedes Oliva, Patricia Rodriguez Pardina, María Carola Sabini
September 20, 2023 (v1)
Keywords: Biocontrol, Glycine max, Potyvirus
Soybean mosaic disease, caused by the soybean mosaic virus (SMV), is responsible for major losses in yield and seed quality worldwide. Although resistant cultivars are used for its prevention and control, an alternative strategy could consist of applying environmentally friendly antimicrobial agents, such as extracts and essential oils (EOs) of aromatic plants. This study assessed an extract of Achyrocline satureioides and EOs of Minthostachys verticillata, Origanum vulgare, and Thymus vulgaris in terms of their phytotoxicity in soybean. Since all the concentrations tested were found to be safe, the activity of each product against SMV was then assayed in vivo, i.e., in experimentally infected soybean plants. The parameters measured were plant height, wet weight, and virus titer. All the treated plants had a greater height and weight than those in the viral control group. The EOs of M. verticillata (0.80 mg/mL) and T. vulgaris (0.71 mg/mL) inhibited the production of viral antigens, as... [more]
Optimized Operation of Fluidized Catalytic Cracking Considering CO2 Fixation and Carbon Pricing
Yusuke Mori, Daisuke Okazaki, Gento Mogi
September 20, 2023 (v1)
Keywords: CO2 emission, decarbonizing, economic value, FCC, fluidized catalytic cracking, liquefied petroleum gas, LPG, operation patterns, plant optimization, process simulation
Recently, Japan and the European Union have been experiencing declining petroleum demand owing to global initiatives aimed at reducing environmental impact by curtailing CO2 emissions. Consequently, alternative products and operational conditions should be developed to utilize the fluid catalytic cracking (FCC) unit. Using simulation software (Aspen Hysys), this study modeled a typical FCC unit and compared the simulation results with operational data to ensure reproducibility. Two new process models were developed to investigate two scenarios: (i) the slurry discharged from the FCC unit is utilized as a feedstock for the FCC process and (ii) the slurry and fraction obtained from the downstream absorber of the FCC unit are introduced into a delayed coker unit to facilitate carbon fixation. Within an optimum riser outlet temperature (ROT) of 520−530 °C, the yields of gasoline and liquefied petroleum gas increased up to 4%. For profit performance, although ROT of 535−545 °C yielded peak... [more]
Optimization of Abrasive Water Jet Machining Process Parameters on Onyx Composite Followed by Additive Manufacturing
Dharmalingam Ganesan, Sachin Salunkhe, Deepak Panghal, Arun Prasad Murali, Sivakumar Mahalingam, Hariprasad Tarigonda, Sharad Ramdas Gawade, Hussein Mohamed Abdel-Moneam Hussein
September 20, 2023 (v1)
Subject: Materials
Keywords: abrasive water jet machining, delamination, onyx composite, surface roughness, Taguchi analysis
Fiber-reinforced additive manufacturing components have been used in various industrial applications in recent years, including in the production of aerospace, automobile, and biomedical components. Compared to conventional methods, additive manufacturing (AM) methods can be used to obtainin lighter parts with superior mechanical properties with lower setup costs and the ability to design more complex parts. Additionally, the fabrication of onyx composites using the conventional method can result in delamination, which is a significant issue during composite machining. To address these shortcomings, the fabrication of onyx composites via additive manufacturing with the Mark forged 3D-composite printer was considered. Machinability tests were conducted using abrasive water jet machining (AWJM) with various drilling diameters, traverse speeds, and abrasive mass flow rates. These parameters were optimized using Taguchi analysis and then validated using the Genetic algorithm (GA) and the M... [more]
Peptide Diversification through Addition Reaction of Free Carboxylic Acids to Ynamides
Zhefan Zhang, Lingchao Cai, Liangliang Song
September 20, 2023 (v1)
Subject: Biosystems
Keywords: addition reaction, peptide, ynamide
Peptide modification has emerged as an important topic in the academic community and pharmaceutical industry. However, they are primarily focused on the diversification of amines, thiols, and alcohols. Direct and chemoselective modification of acid residues in peptides is relatively underdeveloped. In this context, we report a novel and efficient method for the direct functionalization of acid residues in peptides. By using ynamides as reaction partners, the adducts are rapidly obtained in moderate to excellent yields at room temperature in water. This approach shows excellent chemoselectivity and a broad scope including dipeptides bearing unprotected Trp or Tyr residue and free Ser or Gln residue.
Concurrent Biocatalytic Oxidation of 5-Hydroxymethylfurfural into 2,5-Furandicarboxylic Acid by Merging Galactose Oxidase with Whole Cells
Fan-Feng Zhu, Jian-Peng Wang, Min-Hua Zong, Zhao-Juan Zheng, Ning Li
September 20, 2023 (v1)
Subject: Materials
Keywords: aldehyde dehydrogenases, biobased chemicals, biocatalysis, bioplastics, cascade oxidation, oxidases
2,5-Furandicarboxylic acid (FDCA) is an important monomer for manufacturing biobased plastics. Biocatalysis has been recognized as a sustainable tool in organic synthesis. To date, the efficiencies of most biocatalytic processes toward FDCA remain low. So, it is highly desired to develop efficient processes. In this work, a biocatalytic route toward FDCA was developed by integrating a cell-free extract of galactose oxidase variant M3−5 with a whole-cell biocatalyst harboring NAD+-dependent vanillin dehydrogenases and NADH oxidase, starting from 5-hydroxymethylfurfural. FDCA was produced in a concurrent mode with >90% yields within 36 h at 20 mM substrate concentration. In addition, biocatalytic synthesis of FDCA was performed on a preparative scale, with 78% isolated yield. The present work may lay the foundation for sustainable production of FDCA.
A Review of Treatment Technologies for Perfluorooctane Sulfonate (PFOS) and Perfluorooctanoic Acid (PFOA) in Water
Juntao Cheng, Liming Huang, Yunfeng Li, Zhen Zhang, Runzhi Mu, Changqing Liu, Shuncheng Hu, Yihua Xiao, Mengchen Xu
September 20, 2023 (v1)
Subject: Biosystems
Keywords: Adsorption, advanced oxidation processes, membrane separation, microbial treatment, PFOA, PFOS
Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are a category of persistent, non-degradable pollutants that are widespread in the environment and in humans. They have attracted considerable attention due to their high bioaccumulation, multiple toxicities, long-term stability, and, in particular, their effects on human health. Therefore, there is an urgent need for highly efficient technologies and systematic mechanisms for the degradation of PFOS and PFOA. Therefore, we summarize four mainstream technologies for the degradation of PFOS and PFOA in water and their research progress in this review, namely adsorption, advanced oxidation processes, microbial treatment, and membrane separation. Among them, adsorption technology is the earliest and relatively mature, the advanced oxidation process has relatively high treatment efficiency, there are deep and broad development prospects for microbial treatment in the future, and membrane separation technology can recycle ra... [more]
In Situ Indoor Air Volatile Organic Compounds Assessment in a Car Factory Painting Line
Pedro Catalão Moura, Fausto Santos, Carlos Fujão, Valentina Vassilenko
September 20, 2023 (v1)
Subject: Other
Keywords: air quality, car factory, coatings, gas chromatography, indoor air, ion mobility spectrometry, painting line, volatile organic compounds
Proper working conditions must be one of the employers’ main concerns in any type of company but particularly in work locations where the employees are chronically exposed to hazardous compounds, like factories and production lines. Regarding this challenge, the present research addresses the mapping of a car factory painting line to possibly toxic volatile organic compounds emitted by all the coatings and chemicals used during the work shifts for the future evaluation of employees’ exposure. For the first time, a Gas Chromatography−Ion Mobility Spectrometry device was employed for the in situ detection of volatile organic compounds in an automotive factory. A total of 26 analytes were detected at nine different locations, of which 15 VOCs were accurately identified. Pure chemical-grade substances were used for the development of the VOC database. Although quantitative analysis was not the goal of this study, a calibration model was presented to one analyte for exemplificative purposes... [more]
A Two-Stage Optimal Preventive Control Model Incorporating Transient Stability Constraints in the Presence of Multi-Resource Uncertainties
Qiulong Ni, Jingliao Sun, Xianyu Zha, Taibin Zhou, Zelun Sun, Ming Zhao
September 20, 2023 (v1)
Subject: Optimization
Keywords: multi-resource uncertainties, particle swarm algorithm, preventive control, transient stability constraints, two-stage model
The volatility and uncertainty introduced by increasingly integrated renewable energy pose challenges to the reliable and stable operation of the power system. To mitigate the operation risks, a two-stage optimal preventive control model that incorporates transient stability constraints and considers uncertainties from multiple resources is proposed. First, the uncertainties of different re-sources are modeled, with which the non-sequential Monte Carlo sampling method is used to correspondingly generate the scenarios. Thereafter, a two-stage control model that balances operational safety and economy and realizes preventive control and emergency control is built. The operation schedule from the preventive control stage aims to minimize the transient stability probability and operation costs. If any faults destabilize the system, the emergency control stage will be activated immediately to help the system recover stability with minimal control costs. To expedite the solving of the two-st... [more]
Electric Vehicle Charging Load Prediction Model Considering Traffic Conditions and Temperature
Jiangpeng Feng, Xiqiang Chang, Yanfang Fan, Weixiang Luo
September 20, 2023 (v1)
Keywords: electric vehicles, load forecasting, Monte Carlo method, spatio-temporal distribution, traffic conditions
The paper presents a novel charging load prediction model for electric vehicles that takes into account traffic conditions and ambient temperature, which are often overlooked in conventional EV load prediction models. Additionally, the paper investigates the impact of disordered charging on distribution networks. Firstly, the paper creates a traffic road network topology and speed-flow model to accurately simulate the driving status of EVs on real road networks. Next, we calculate the electric vehicle power consumption per unit kilometer by considering the effects of temperature and vehicle speed on electricity consumption. Then, we combine the vehicle’s main parameters to create a single electric vehicle charging model, use the Monte Carlo method to simulate electric vehicle travel behavior and charging, and obtain the spatial and temporal distribution of total charging load. Finally, the actual traffic road network and typical distribution network in northern China are used to analyz... [more]
A Study on Environmental Trends and Sustainability in the Ocean Economy Using Topic Modeling: South Korean News Articles
Hee Jay Kang, Changhee Kim, Sungki Kim, Chanho Kim
September 20, 2023 (v1)
Subject: Environment
Keywords: environmental trends, ocean economy, Renewable and Sustainable Energy, text mining, topic modeling
The ocean economy plays a critical role in global economic growth, yet it confronts substantial environmental risks. This study employs topic modeling of South Korean news articles to analyze the evolving trends of environmental risks and sustainability in ocean economy. A dataset comprising 50,213 articles from 2008 to 2022 is examined, revealing prevalent environmental concerns that have persisted over the years. The findings demonstrate an increasing emphasis on sustainability and marine environmental issues, as evidenced by prominent keywords related to construction, safety, plastic pollution, and ecosystem conservation. Through Latent Dirichlet Allocation (LDA) in topic modeling, 10 distinct themes are identified, encompassing sustainable fisheries management, accident and disaster response, polar environment, carbon neutrality, microplastic pollution, habitat ecosystems, cruise tourism development, nuclear power plant pollution, and infectious diseases. The outcomes highlight the... [more]
A Novel Cellular Network Traffic Prediction Algorithm Based on Graph Convolution Neural Networks and Long Short-Term Memory through Extraction of Spatial-Temporal Characteristics
Geng Chen, Yishan Guo, Qingtian Zeng, Yudong Zhang
September 20, 2023 (v1)
Keywords: cellular network, graph convolutional neural networks, RMSE, short and long-term memory networks, traffic prediction
In recent years, cellular communication systems have continued to develop in the direction of intelligence. The demand for cellular networks is increasing as they meet the public’s pursuit of a better life. Accurate prediction of cellular network traffic can help operators avoid wasting resources and improve management efficiency. Traditional prediction methods can no longer perfectly cope with the highly complex spatiotemporal relationships of the current cellular networks, and prediction methods based on deep learning are constantly growing. In this paper, a spatial-temporal parallel prediction model based on graph convolution combined with long and short-term memory networks (STP-GLN) is proposed to effectively capture spatial-temporal characteristics and to obtain accurate prediction results. STP-GLN is mainly composed of a spatial module and temporal module. Among them, the spatial module designs dynamic graph data based on the principle of spatial distance and spatial correlation... [more]
Material Transport and Flow Pattern Characteristics of Gas−Liquid−Solid Mixed Flows
Juntong Chen, Man Ge, Lin Li, Gaoan Zheng
September 20, 2023 (v1)
Subject: Materials
Keywords: battery homogenate mixing, dynamic regulation, gas–liquid–solid mixed flow, inflation control, material transport, porous model
Flow pattern monitoring of gas−liquid−solid mixed flow has great significance to enhance the quality and efficiency of material mixing, and the material transport mechanism and dynamic control strategy are faced with significant challenges. To solve these problems, a computational fluid mechanics and discrete element method (CFD-DEM) coupling modeling and solving approach based on soft sphere and porous models is presented to explore material transport mechanisms. The user-defined function (UDF) is adopted to perform data communication, and the porosity of the porous model is calculated to achieve the bidirectional calculation of Eulerian fluid and Lagrange particle phases. Material transport processes of gas−liquid−solid mixed flows are discussed to explore material transport mechanisms of particle flow and the flow pattern evolution laws under the inflation control are obtained. The results show that the particles are not evenly distributed under the synergistic action of impeller ro... [more]
Green Extraction Techniques of Bioactive Compounds: A State-of-the-Art Review
Rodrigo Martins, Ana Barbosa, Bárbara Advinha, Hélia Sales, Rita Pontes, João Nunes
September 20, 2023 (v1)
Keywords: antioxidant, bioactive pigments, bioeconomy, green chemistry, phenolic compounds
Green extraction techniques are more and more relevant due to major sustainable goals set by the United Nations. Greener extraction processes are being designed through the use of unconventional extraction techniques and green solvents, resulting in less hazardous processes which, consequently, reduces environmental impacts. This is also in line with the main principles of green chemistry. Additionally, greener extraction techniques intend to solve different drawbacks that are often related to conventional extraction techniques such as the high environmental impact. Biorefineries are a major player in developing greener extraction processes. These facilities take full advantage of several biomass sources, such as food waste, microalgae, and lignocellulosic biomass, in order to create high-value products, energy, alternative fuels, and bioactive compounds. Herein, a state-of-the-art review is presented, focused on presenting the greenest and least hazardous extraction processes that hav... [more]
Visual Impact of Renewable Energy Infrastructure: Implications for Deployment and Public Perception
Martin Beer, Radim Rybár, Ľubomíra Gabániová
September 20, 2023 (v1)
Keywords: questionnaire survey, renewable energy infrastructure, Slovak Republic, tourism, visual impacts
This study focuses on the specific topic of assessing the negative visual impacts associated with renewable energy infrastructure that may prevent their wider deployment in energy mix. The main objective of the paper is to quantify the perception of the visual impact of renewable energy infrastructure and to estimate potential changes in the visitation of a location after the construction of power plants. The research was conducted using a questionnaire survey in which 449 respondents evaluated edited photographic materials of seven locations with a fictitious power plant. The collected data served as input for the statistical testing of eight defined hypotheses using the U-Mann−Whitney test. The results confirmed trends regarding the influence of age, educational level, and power plant proximity on the overall acceptance of renewable energy infrastructure. Landscape-forming factors affecting the acceptance rate of power plants were also defined at the local level.
Multi-Fracture Growth Law for Temporary Plugging and Diversion Fracturing of Horizontal Well with Multiple Clusters in Shale Reservoir
Yanchao Li, Jianguo Shen, Longqing Zou, Yushi Zou, Xinfang Ma, Can Yang, Weiwei Wang
September 20, 2023 (v1)
Keywords: fracture morphology, fracturing stage, hydraulic fracturing, hydraulic sandblasting perforating, shale, temporary plugging and diversion
Temporary plugging and diversion fracturing (TPDF) is a common method to increase production and efficiency in shale gas reservoirs, but the growth law of diversion fractures and the temporary plugging mechanism are still unclear, which restricts the further optimization of temporary plugging fracturing schemes. Therefore, in this study, a series of simulation experiments of TPDF in a horizontal well with multi-clusters were carried out for the Longmaxi Shale outcrop by using a large true triaxial fracturing system. The laboratory method of “inner-fracture + inner-segment” TPDF with multiple clusters of perforation in horizontal wells was proposed, and the fracture initiation law and control factors, including the number of clusters and the method of perforating, were investigated. The experimental results show that the peak pressures of inner-fracture temporary plugging (IFTP) and inner-segment temporary plugging (ISTP) stages are higher, and the number of diversion fractures and the... [more]
Dyes and Heavy Metals Removal from Aqueous Solutions Using Raw and Modified Diatomite
Simona Gabriela Muntean, Maria Andreea Nistor, Raisa Nastas, Oleg Petuhov
September 20, 2023 (v1)
Subject: Environment
Keywords: Adsorption, equilibrium, kinetic, pollutant, Wastewater
The progress of the textile industry has led to a severe increase in the discharge of colored effluents, polluted with dyes and metal ions (non-biodegradable, carcinogenic to humans and environmental hazards). The implementation of effective methodologies and materials for the treatment of wastewater has become an urgent requirement. The present work describes the application of two samples of mineral materials—Ghidirim diatomite and modified diatomite—as adsorbents for the removal of dyes—Acid Blue 350, Methylene Blue, Basic Red 2—and of metal ions—copper, zinc, and lead—from aqueous solutions. In order to determine the optimal working conditions by which to ensure maximum removal efficiency, the influence of the nature and amount of the sorbent, the initial concentration of pollutant, and the temperature were studied. Working under normal conditions (room temperature, solution pH) efficiencies greater than 80% were obtained for the removal of dyes and metal ions. The adsorption fitte... [more]
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