bluuebunny/crossref_metadata_2025 huggingface dataset:
Hybrid Modulated DCDC Boost Converter for Wearable Devices
Authors: Li Tong , Gan Yebing
Published: October 2022

Wearable devices require power management systems to achieve high conversion efficiency over a wide range of load currents. Multi-mode mixed modulation can be used in DCDC converters to achieve high efficiency over a wide load current range. The DCDC boost converter proposed in this paper uses a hybrid modulation of DGM (Deep Green Control Mode), PCMC (Peak current mode control)-PFM (Pulse Frequency Modulation) and PCMC-PWM (Pulse Width Modulation). The converter switches smoothly from PCMC-PFM to PCMC-PWM mode under load-current-based conditions and without any mode selection module. The proposed DCDC boost converter is fabricated in a 0.18 μm CMOS process with a Die area of 1.24 × 0.78 μm2. The input voltage range is 0.8–5 V, the output voltage is 5 V, and the load current range is 5–300 mA. Experimental results show that the boost converter can achieve 94.7% peak efficiency. Efficiency of more than 90% can be achieved in the load current range of 30–300 mA.
Reflection Suppression through Modal Filtering for Wideband Antenna Measurement in a Non-Absorbent Environment
Authors: Su Yao , Gong Shuxi
Published: October 2022

In order to reduce the influence of multi-path effects on the measurement results of wideband antennas, this paper proposes a method for suppressing interference in wideband antenna measurements based on modal filtering technology. This paper introduces the theory and operation process of modal filtering, establishes the relationship between the distribution of modal coefficient terms and the location of the antenna and external interference sources, and clearly reveals the principle of filtering interference through modal filtering. It is pointed out that each location of interference sources corresponds to different pattern items. Filtering out the power of the pattern term generated by the interference source is equivalent to filtering out the interference caused by the interference source. The sources filtered by this technology are external sources that are spatially separated from the antenna, including external sources, environmental reflections, and device reflections, among others. This feature makes it possible to be used for testing in a non-absorbent environment. Its ability to operate at almost any frequency makes it ideal for suppressing interference effects in wideband antenna measurement. This paper demonstrates a recent advance wherein modal filtering techniques are used in interference suppression for wideband antenna non-absorbent measurement. In the full bandwidth range of the wideband antenna, we verify the method through numerical simulation analysis and practical measurement. In the numerical simulation, we obtain that 15 dB interference can be filtered out at the −25 dB level and 5 dB interference can be filtered out at the −35 dB level. In the experiments, within the broadband antenna bandwidth, we found that 2.5 dB can be filtered at the −10 dB level at 4 GHz, 3 dB is filtered at the −10 dB level at 6 GHz, and 5 dB is filtered at the −10 dB level at 7.5 GHz. All of the above results prove that the proposed method can effectively suppress the multi-path interference in wideband non-absorbent antenna measurement and improve the measurement results.
Research on the Characteristics and Influencing Factors of Chinese Urban Households’ Electricity Consumption Efficiency
Authors: Li Zhi , Lv Lu , Zhang Zuo
Published: October 2022

Improving energy efficiency is a key global policy goal for climate protection. Residential energy consumption has also increased rapidly with the acceleration of China’s urbanization process, there is still a lack of studies that deeply explore the microscopic urban household energy efficiency and the main determinants in China, although urban household energy efficiency has attracted the attention of many scholars. We use a two-step method to analyze the electricity consumption efficiency of Chinese urban households in 2014 and 2016, the changing characteristics of household electricity efficiency who live in two-bedroom houses are measured with data envelopment analysis (DEA) method in the first step and the driving factors of changes are analyzed with Tobit model in the second step. The results show that household electricity efficiency gained a small but significant improvement between 2014 and 2016. Household income, age, and education level of the head of household, and housing type are the main drivers of inefficiency. We also adopt robustness tests, such as Bootstrap truncated regression to find this effect still exists. This information can be used in activities such as subsidized energy-saving equipment, energy audits, and information campaigns that aimed at improving household electricity efficiency, thereby increasing their cost-effectiveness and minimizing electricity consumption.
Implication Linkage among Microfacies, Diagenesis, and Reservoir Properties of Sandstones: A Case Study of Dongying Formation, Nanpu Sag, Bohai Bay Basin
Authors: Yu Zhenghong , Chen Si , Xie Weidong , Zhao Shu’e , Ma Jianghao , Gong Tianhao
Published: October 2022

The reservoir quality of sandstones is significantly impacted and transformed by sedimentation and diagenesis. It is necessary to clarify the internal relationship among them to precisely predict the sweet reservoir. In this study, five types of sedimentary microfacies are recognized through core observation and logging data: submerged distributary channel (fan delta), submerged interdistributary bay, submerged distributary channel (braided delta), distal bar, and turbidite fan. The major diagenetic processes, including compaction, cementation, and dissolution, have been analyzed based on petrography, scanning electron microscopy, and X-Ray diffraction. The dominant diagenetic cement includes calcite, smectite, kaolinite, illite, and I/S mixed-layer minerals, with small quantities of chlorite, pyrite, siderite, feldspar, and quartz cement. The reservoir quality is best in the submerged distributary channel (fan delta) sandstones, followed by submerged distributary channel (braided delta). Submerged interdistributary bay, distal bar, and turbidite fan are of poor reservoir quality. The grain size is the primary reservoir quality controlling factor, highly affected by sedimentary microfacies. Subsequent controls are diagenetic processes such as mechanical compaction, clay minerals formation, grain replacement, and dissolution that collectively influence the porosity and permeability.
Research on Aerodynamic Characteristics of Crescent Iced Conductor Based on S-A Finite Element Turbulence Model
Authors: Liao Shaokai , Zhang Yan , Chen Xi , Cao Pengcheng
Published: October 2022

Galloping is a typical wind-induced phenomenon in iced conductors, which can have serious impacts on the safe and stable operation of power systems. The aerodynamic characteristics of an iced conductor are the key factor in the study of galloping, which can be determined mainly by the numerical simulation of flow past an iced conductor. Based on the Reynolds-averaged Navier-Stokes (RANS) equations closed by the Spalart-Allmaras (S-A) turbulence model, the third-order Runge-Kutta method along the uniform streamline and Galerkin method are used for temporal and spatial discretization, respectively. The convection and diffusion terms in the discretization scheme are treated semi-implicitly, and the finite element scheme based on the S-A turbulence model is presented and used to numerically simulate flow past a crescent iced conductor. We systematically investigate the effects of icing thickness, wind speed, and wind attack angle on aerodynamic coefficients and flow patterns. Based on the experimental results, the effectiveness of the present algorithm is verified. Using the streamline diagram and pressure distribution diagram of the crescent-shaped iced conductor, the mechanism for the sharp peak of the lift coefficient is explored. Combined with the galloping mechanism of Den Hartog and Nigol, the galloping instability zone of the crescent-shaped iced conductor is analyzed.
Blowout Prediction on a Salt Cavern Selected for a Hydrogen Storage Pilot
Authors: Djizanne Hippolyte , Murillo Rueda Carlos , Brouard Benoit , Bérest Pierre , Hévin Grégoire
Published: October 2022

To prevent climate change, Europe and the world must shift to low-carbon and renewable energies. Hydrogen, as an energy vector, provides viable solutions for replacing polluting and carbon-emitting fossil fuels. Gaseous hydrogen can be stored underground and coupled with existing natural gas pipe networks. Salt cavern storage is the best suited technology to meet the challenges of new energy systems. Hydrogen storage caverns are currently operated in the UK and Texas. A preliminary risk analysis dedicated to underground hydrogen salt caverns highlighted the importance of containment losses (leaks) and the formation of gas clouds following blowouts, whose ignition may generate dangerous phenomena such as jet fires, unconfined vapor cloud explosions (UVCEs), or flashfires. A blowout is not a frequent accident in gas storage caverns. A safety valve is often set at a 30 m depth below ground level; it is automatically triggered following a pressure drop at the wellhead. Nevertheless, a blowout remains to be one of the significant accidental scenarios likely to occur during hydrogen underground storage in salt caverns. In this paper, we present modelling the subterraneous and aerial parts of a blowout on an EZ53 salt cavern fully filled with hydrogen.
A New Voltage Based Fault Detection Technique for Distribution Network Connected to Photovoltaic Sources Using Variational Mode Decomposition Integrated Ensemble Bagged Trees Approach
Authors: Nsaif Younis M. , Hossain Lipu Molla Shahadat , Hussain Aini , Ayob Afida , Yusof Yushaizad , Zainuri Muhammad Ammirrul A. M.
Published: October 2022

The increasing integration of renewable sources into distributed networks results in multiple protection challenges that would be insufficient for conventional protection strategies to tackle because of the characteristics and functionality of distributed generation. These challenges include changes in fault current throughout various operating modes, different distribution network topologies, and high-impedance faults. Therefore, the protection and reliability of a photovoltaic distributed network relies heavily on accurate and adequate fault detection. The proposed strategy utilizes the Variational Mode Decomposition (VMD) and ensemble bagged trees method to tackle these problems in distributed networks. Primarily, VMD is used to extract intrinsic mode functions from zero-, positive-, and negative-sequence components of a three-phase voltage signal. Next, the acquired intrinsic mode functions are supplied into the ensemble bagged trees mechanism for detecting fault events in a distributed network. Under both radial and mesh-soft normally open-point (SNOP) topologies, the outcomes are investigated and compared in the customarily connected and the island modes. Compared to four machine learning mechanisms, including linear discriminant, linear support vector mechanism (SVM), cubic SVM and ensemble boosted tree, the ensemble bagged trees mechanism (EBTM) has superior accuracy. Furthermore, the suggested method relies mainly on local variables and has no communication latency requirements. Therefore, fault detection using the proposed strategy is reasonable. The simulation outcomes show that the proposed strategy provides 100 percent accurate symmetrical and asymmetrical fault diagnosis within 1.25 ms. Moreover, this approach accurately identifies high- and low-impedance faults.
The Development of the Use of Water Energy in the Mountain Catchment from a Sociohydrological Perspective
Authors: Witkowski Karol
Published: October 2022

Man has been using the energy of flowing water since antiquity. Water milling flourished in Europe in the Middle Ages, reaching its maximum development in the 19th century. Since the beginning of the 20th century, water energy has been used to produce electricity. Acquiring the energy of water involves modifying the natural environment. Milling is considered to be the activity that started the emergence of fluvial anthropospheres in Europe. For centuries, the construction of watermills and millraces has caused the densification of the river network, raised the level of groundwater, and forced the deposition of sediments. From the point of view of sociohydrology, milling has been an expression of the economic and technological development of societies. The milling industry and, therefore, the natural environment have also been affected by political factors and beliefs. At the beginning of the 20th century, water drives were replaced with steam and later electric drives in mills. These changes resulted in the abandonment of millraces and the liquidation of weirs, which reversed the hydromorphological processes regulated by milling since the Middle Ages. The development of hydropower seems to be environmentally friendly owing to the use of renewable energy, but the environmental costs associated with the construction of a hydroelectric power plant cannot go unnoticed. The problem of the development of water energy use over the centuries has been studied on the basis of the example of the catchment of the mountain River Skawa. The study shows how many factors determined the development of the milling industry and, consequently, the transformation of the natural environment. These factors were largely local or regional, which shows that comprehensive analyses of anthropopressure cannot be of a global nature.
Energy Consumption Analysis of Helicopter Traction Device: A Modeling Method Considering Both Dynamic and Energy Consumption Characteristics of Mechanical Systems
Authors: Liu Qian , Zhang Zhuxin , Jia Tuo , Wang Lixin , Zhao Dingxuan
Published: October 2022

Since modern times, the increase in shipborne equipment has brought tremendous pressure to the energy supply system. Establishing an accurate and reliable energy consumption model that reflects the dynamic characteristics of the system will provide an essential theoretical reference for energy efficiency optimization. This paper proposes a modeling method that considers both the dynamic characteristics and energy consumption characteristics of the system, based on the power bond-graph theory. Firstly, the transmission principle and energy transfer process of hydraulic and electric helicopter traction devices are analyzed. Then, the energy consumption is analyzed, and the state equation and energy equation of the system are established. Finally, the simulation tests are carried out. The results show that the proposed dynamic modeling method is reasonable and effective and can well reflect the dynamic characteristics and energy consumption characteristics of the system.
Effect of Actual Recuperators’ Effectiveness on the Attainable Efficiency of Supercritical CO2 Brayton Cycles for Solar Thermal Power Plants
Authors: Stamatellos George , Stamatelos Tassos
Published: October 2022

One of the most promising concentrated solar power technologies is the central receiver tower power station with heliostat field, which has attracted renewed research interest in the current decade. The introduction of the sCO2 recompression Brayton cycles in the near future installations instead of the Rankine cycle is very probable, due to the prospects of a significant efficiency improvement, process equipment size and capital cost reduction. In this study, energy and exergy analysis of a recompression Brayton cycle configuration for a central receiver power station are performed. Special emphasis is given to the computation of actual performance for the High-Temperature Recuperator and the Low-Temperature Recuperator. The results define realistic thermal and exergetic efficiency limits for the specific cycle configurations applied on a central receiver solar power plant with variable turbine entry temperature. Thermal efficiency, predicted with the improved accuracy of heat exchanger computations, does not exceed the 50% target. Overall, a realizable total power plant efficiency of 37% at 900 K turbine entry temperature is predicted, which is a significant improvement on the current state-of-the-art with steam Rankine cycles.
Design of a Chamfered Structure on Consequent-Pole Vernier Permanent-Magnet Machine
Authors: Ma Jien , Xu Bowen , Wu Qiyi , Luo Chao , Lin Qiu , Fang Youtong
Published: October 2022

The consequent-pole (CP) Vernier permanent-magnet (VPM) machine has been developed over the last decade. In VPM machine, the CP structure can produce considerable torque with a half volumn of the PMs compared with the regular structure, so the cost is reduced and the mechanical strength is increased. In this paper, an improvement of chamfering structure on a CPVPM machine is proposed to alleviate the flux leakage and increase the torque density. The chamfered structure is easily machined and will not influence the robustness of the rotor. The comparison results show that under the same volume and copper loss constraint, the proposed structure has smaller cogging torque, smaller torque ripple, larger torque density and larger power factor.
Electricity Markets in the Context of Distributed Energy Resources and Demand Response Programs: Main Developments and Challenges Based on a Systematic Literature Review
Authors: da Costa Vinicius Braga Ferreira , de Doile Gabriel Nasser Doyle , Troiano Gustavo , Dias Bruno Henriques , Bonatto Benedito Donizeti , Soares Tiago , de Freitas Filho Walmir
Published: October 2022

Distributed energy resources have been increasingly integrated into electrical grids. Consequently, electricity markets are expected to undergo changes and become more complex. However, while there are many scientific publications on the topic, a broader discussion is still necessary. Therefore, a systematic literature review on electricity markets in the context of distributed energy resources integration was conducted in this paper to present in-depth discussions on the topic, along with shedding light on current perspectives, the most relevant sources, authors, papers, countries, metrics, and indexes. The software R and its open-source tool Bibliometrix were used to perform the systematic literature review based on the widely recognized databases Web of Science and Scopus, which led to a total of 1685 articles after removing duplicates. The results demonstrate that demand response, renewable energy, uncertainty, optimization, and smart grid are the most-used keywords. By assessing highly impactful articles on the theme, emphasis on energy storage systems becomes clear compared to distributed generation and electric vehicles. However, electric vehicles draw attention in terms of citations. Furthermore, multi-level stochastic programming is the most-applied methodology among highly impactful articles. Due to the relevance of the demand response keyword, this paper also conducts a specific review on the topic aligned with electricity markets and distributed energy resources (296 articles). The results demonstrate that virtually all high-impact publications on the topic address day-ahead or real-time pricing. Based on the literature found, this paper presents a discussion on the main challenges and future perspectives related to the field. The complexity of electrical power systems and electricity markets is increasing substantially according to what this study found. Distributed generation development is already advanced, while energy storage systems and electric vehicles are limited in many countries. Peer-to-peer electricity trading and virtual power plant are newer concepts that are currently incipient, and DR programs showcase an intermediate stage of evolution. A particular lack of research on social issues is verified, and also a lack of all-encompassing studies that address multiple interconnected topics, which should be better addressed in the future. The in-depth assessment carried out in this paper is expected to be of high value to researchers and policy-makers and facilitate future research on the topic.
Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks
Authors: Jiménez-Aparicio Miguel , Hernández-Alvidrez Javier , Montoya Armando Y. , Reno Matthew J.
Published: October 2022

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.
Large Stress-Gradient Creep Tests and Model Establishment for Red Sandstone Treated at High Temperatures
Authors: Ren Xiaopeng , Xin Yajun , Jia Baoshan , Gao Kun , Li Xuping , Wang Yu
Published: October 2022

Red sandstone samples treated at high temperatures feature complex creep properties. Uniaxial compression tests and the incremental creep tests at different stress gradients were conducted on 10 red sandstone samples of the same specifications divided into five groups on an RLW-2000 triaxial servo rheometer in the laboratory. Relationships of the instantaneous strain and creep strain of red sandstone samples treated at high temperatures with the stress level were explored, and the creep properties and strength of the samples at different temperature gradients were investigated. In addition, the creep failure patterns and failure mechanism of the red sandstone samples were determined, and a creep constitutive model was established for the samples considering the effects of temperature. The conformity between test data and theoretical curves was discussed. Results show that as the stress increases, the instantaneous strain tends to decrease rapidly, slowly, then increase slowly; the creep strain tends to decrease, steadily increase, then increase substantially. At the same stress, as the stress gradient is doubled, the instantaneous strain decreases by 47.45%, and the creep strain decreases by 48.30%. For samples treated at 300~900 °C, the number of stress levels experienced gradually decreases; as the temperature increases, the creep failure strength of samples first increases, then decreases in an arcuate form, and the creep strain tends to decrease, increase, then increase rapidly. In the temperature range, the creep strain at the two stress gradients has a growing difference, with the maximum difference reaching 0.0134%; there is an inflection point at 300 °C in the creep failure strength of samples. At the same stress, the more the stress levels experienced, the lower the creep failure strength, and the temperature, creep failure strength, and creep strain can be characterized by a quadratic polynomial. At 300 °C, mineral particles in samples are sintered and cemented into chains, and there is a significant primary control plane, so the samples show oblique shear failure of a single primary control plane. At 600~900 °C, particles and blocks in samples begin to be sintered and flow, and the cemented chains are broken. Under the condition, the samples mainly show failure dominated by mixed and crossed primary and secondary control planes and crushing failure due to transverse compression. The established Burgers–Kelvin-Temperature (BKT) creep constitutive model is sensitive to changes in temperature; the theoretical curves are consistent with the test data.
Numerical Simulation Analysis Method of the Surrounding Rock and Support Bearing Capacity in Underground Cavern
Authors: Xiao Ming , Ren Junqing , Zhao Binxin , Chen Chen , Chen Shijie
Published: October 2022

After the excavation of an underground cavern, how the surrounding rock and the support work together to bear the excavation load is an important prerequisite to correctly analyze the joint force characteristics; effectively play the role of support; and ensure the safety, efficiency, and economy of underground cavern construction. Starting from the elastic-plastic load release characteristics of surrounding rock, this paper proposes a calculation method of the elastic load coefficient of surrounding rock and a graded release method of plastic load, which ensures the actual effect of the synergistic action of the first support and surrounding rock. Based on the elastic-plastic damage evolution characteristics of surrounding rock, a weighted iterative calculation method of elastic-plastic damage is proposed, and an evaluation method of load release ultimate bearing capacity of surrounding rock is determined. By monitoring the change law of rock acoustic wave velocity with surrounding rock damage, the relationship between the wave velocity and the damage coefficient of the surrounding rock in the excavation process is deduced, and it is proposed to determine the latest support time for first support by using the measured rock damage wave velocity. Through the numerical simulation analysis of a diversion tunnel excavation and support, the damage evolution law of the surrounding rock with the release of the excavation load is studied. The ultimate bearing capacity of various surrounding rocks and supporting opportunity is determined. The results demonstrate the validity and practicality of the analysis and calculation methods in this paper, which provide a new idea and analysis method for quantifying the bearing capacity of surrounding rock and determining the support timing in the excavation and support design of underground caverns.
Influence of Standard Image Processing of 3D X-ray Microscopy on Morphology, Topology and Effective Properties
Authors: Guibert Romain , Nazarova Marfa , Voltolini Marco , Beretta Thibaud , Debenest Gerald , Creux Patrice
Published: October 2022

Estimating porous media properties is a vital component of geosciences and the physics of porous media. Until now, imaging techniques have focused on methodologies to match image-derived flows or geomechanical parameters with experimentally identified values. Less emphasis has been placed on the compromise between image processing techniques and the consequences on topological and morphological characteristics and on computed properties such as permeability. The effects of some of the most popular image processing techniques (filtering and segmentation) available in open source on 3D X-ray Microscopy (micro-XRM) images are qualitatively and quantitatively discussed. We observe the impacts of various filters such as erosion-dilation and compare the efficiency of Otsu’s method of thresholding and the machine-learning-based software Ilastik for segmentation.
Non-Intrusive Load Monitoring Based on Swin-Transformer with Adaptive Scaling Recurrence Plot
Authors: Shi Yongtao , Zhao Xiaodong , Zhang Fan , Kong Yaguang
Published: October 2022

Non-Intrusive Load Monitoring (NILM) is an effective energy consumption analysis technology, which just requires voltage and current signals on the user bus. This non-invasive monitoring approach can clarify the working state of multiple loads in the building with fewer sensing devices, thus reducing the cost of energy consumption monitoring. In this paper, an NILM method combining adaptive Recurrence Plot (RP) feature extraction and deep-learning-based image recognition is proposed. Firstly, the time-series signal of current is transformed into a threshold-free RP in phase space to obtain the image features. The Euclidean norm in threshold-free RP is scaled exponentially according to the voltage and current correlation to reflect the working characteristics of different loads adaptively. Afterwards, the obtained adaptive RP features can be mapped into images using the corresponding pixel value. In the load identification stage, an advanced computer vision deep network, Hierarchical Vision Transformer using Shifted Windows (Swin-Transformer), is applied to identify the adaptive RP images. The proposed solution is extensively verified by four real, measured load signal datasets, including industrial and household power situations, covering single-phase and three-phase electrical signals. The numerical results demonstrate that the proposed NILM method based on the adaptive RP can effectively improve the accuracy of load detection.
SSA-LSTM: Short-Term Photovoltaic Power Prediction Based on Feature Matching
Authors: Huang Zhengwei , Huang Jin , Min Jintao
Published: October 2022

To reduce the impact of volatility on photovoltaic (PV) power generation forecasting and achieve improved forecasting accuracy, this article provides an in-depth analysis of the characteristics of PV power outputs under typical weather conditions. The trend of PV power generation and the similarity between simultaneous outputs are found, and a hybrid prediction model based on feature matching, singular spectrum analysis (SSA) and a long short-term memory (LSTM) network is proposed. In this paper, correlation analysis is used to verify the trend of PV power generation; the similarity between forecasting days and historical meteorological data is calculated through grey relation analysis; and similar generated PV power levels are searched for phase feature matching. The input time series is decomposed by singular spectrum analysis; the trend component, oscillation component and noise component are extracted; and principal component analysis and reconstruction are carried out on each component. Then, an LSTM network prediction model is established for the reconstructed subsequences, and the external feature input is controlled to compare the obtained prediction results. Finally, the model performance is evaluated through the data of a PV power plant in a certain area. The experimental results prove that the SSA-LSTM model has the best prediction performance.
Properties of Modified Warm-Mix Asphalt Mixtures Containing Different Percentages of Reclaimed Asphalt Pavement
Authors: Obaid Hayder Abbas , Hashim Tameem Mohammed , Al-Abody Ahmed Awad Matr , Nasr Mohammed Salah , Abbas Ghadeer Haider , Kadhim Abdullah Musa , Sadique Monower
Published: October 2022

The Rapid reduction of energy resources and the escalated effects of global warming have created a strong motivation to find some new techniques in the field of paving construction. Adopting new technologies, such as warm-mix asphalt (WMA) or the recycling process of asphalt can be very helpful for the economy and have a significant impact on the environmental footprint. Thus, this research aimed to study the mechanical and durable characteristics of modified WMA mixtures using (1.0%, 1.5%, and 2.0%) Sasobit REDUX®, (0.3%, 0.4%, and 0.5%) Aspha-Min®, and (0.07%, 0.1%, and 0.125) ZycoTherm® additives corresponding to three percentages of reclaimed asphalt pavement (RAP) (20%, 40%, and 60%). Three mixing temperatures have been conducted in this study to generate WMA mixtures at (135 °C, 125 °C, and 115 °C) corresponding to three compacting temperatures (125 °C, 115 °C, and 105 °C). The mechanical properties of the developed WMA mixtures have been evaluated using the Superpave volumetric properties (air voids, voids filled with asphalt, and voids in mineral aggregate), while the durable properties have been investigated using the resilient modulus test (MR) at 25 °C, resilient modulus ratio (RMR), and Hamburg wheel-track test in terms of permanent deformation, moisture susceptibility, and rutting resistance. To make the WMA mixtures accept high quantities of RAP (>25%), an insignificant increase in the amounts of WMA additives was needed to produce mixtures carrying sustainability labels. Results indicated that all the used additives had pushed the WMA mixtures to achieve considerable mechanical properties, whereas the best properties for the WMA mixtures containing 0%, 20%, 40%, and 60% of RAP have been achieved by mixing with (1.0% Sasobit REDUX® @ 125 °C), (1.0% Sasobit REDUX® or 0.3% Aspha-Min® @ 135 °C), (1.5% Sasobit REDUX® @ 125 °C), and (2.0% Sasobit REDUX® or 0.5% Aspha-Min® @ 135 °C), respectively. On another hand, the best durable properties have been achieved by mixing the mentioned WMA mixtures containing 0%, 20%, 40%, and 60% of RAP with 0.07%, 0.07%, 0.1%, and 0.125% of ZycoTherm® at 153 °C, respectively. Using such additives in the recycled WMA mixtures made it possible to activate waste recycling in the paving industry.
A Review of Compensation Topologies and Control Techniques of Bidirectional Wireless Power Transfer Systems for Electric Vehicle Applications
Authors: Venkatesan Murugan , Rajamanickam Narayanamoorthi , Vishnuram Pradeep , Bajaj Mohit , Blazek Vojtech , Prokop Lukas , Misak Stanislav
Published: October 2022

Owing to the constantly rising energy demand, Internal Combustion Engine (ICE)-equipped vehicles are being replaced by Electric Vehicles (EVs). The other advantage of using EVs is that the batteries can be utilised as an energy storage device to increase the penetration of renewable energy sources. Integrating EVs with the grid is one of the recent advancements in EVs using Vehicle-to-Grid (V2G) technology. A bidirectional technique enables power transfer between the grid and the EV batteries. Moreover, the Bidirectional Wireless Power Transfer (BWPT) method can support consumers in automating the power transfer process without human intervention. However, an effective BWPT requires a proper vehicle and grid coordination with reasonable control and compensation networks. Various compensation techniques have been proposed in the literature, both on the transmitter and receiver sides. Selecting suitable compensation techniques is a critical task affecting the various design parameters. In this study, the basic compensation topologies of the Series–Series (SS), Series–Parallel (SP), Parallel–Parallel (PP), Parallel–Series (SP), and hybrid compensation topology design requirements are investigated. In addition, the typical control techniques for bidirectional converters, such as Proportional–Integral–Derivative (PID), sliding mode, fuzzy logic control, model predictive, and digital control, are discussed. In addition, different switching modulation schemes, including Pulse-Width Modulation (PWM) control, PWM + Phase Shift control, Single-Phase Shift, Dual-Phase Shift, and Triple-Phase Shift methods, are discussed. The characteristics and control strategies of each are presented, concerning the typical applications. Based on the review analysis, the low-power (Level 1/Level 2) charging applications demand a simple SS compensation topology with a PID controller and a Single-Phase Shift switching method. However, for the medium- or high-power applications (Level 3/Level 4), the dual-side LCC compensation with an advanced controller and a Dual-Side Phase-Shift switching pattern is recommended.
A Review of Data-Driven Approaches for Measurement and Verification Analysis of Building Energy Retrofits
Authors: Alrobaie Abdurahman , Krarti Moncef
Published: October 2022

Although the energy and cost benefits for retrofitting existing buildings are promising, several challenges remain for accurate measurement and verification (M&V) analysis to estimate these benefits. Due to the rapid development in advanced metering infrastructure (AMI), data-driven approaches are becoming more effective than deterministic methods in developing baseline energy models for existing buildings using historical energy consumption data. The literature review presented in this paper provides an extensive summary of data-driven approaches suitable for building energy consumption prediction needed for M&V applications. The presented literature review describes commonly used data-driven modeling approaches including linear regressions, decision trees, ensemble methods, support vector machine, deep learning, and kernel regressions. The advantages and limitations of each data-driven modeling approach and its variants are discussed, including their cited applications. Additionally, feature engineering methods used in building energy data-driven modeling are outlined and described based on reported case studies to outline commonly used building features as well as selection and processing techniques of the most relevant features. This review highlights the gap between the listed existing frameworks and recently reported case studies using data-driven models. As a conclusion, this review demonstrates the need for a flexible M&V analysis framework to identify the best data-driven methods and their associated features depending on the building type and retrofit measures.
Influence of Several Phosphate-Containing Additives on the Stability and Electrochemical Behavior of Positive Electrolytes for Vanadium Redox Flow Battery
Authors: Zhang Xukun , Meng Fancheng , Sun Linquan , Zhu Zhaowu , Chen Desheng , Wang Lina
Published: October 2022

The poor operational stability of electrolytes is a persistent impediment in building redox flow battery technology; choosing suitable stability additives is usually the research direction to solve this problem. The effects of five phosphate containing additives (including 1-hydroxyethylidene-1,1-diphosphonic acid (HEDP), hexamethylene diamine tetramethylene phosphonic acid (HDTMPA), amino trimethylene phosphonic acid (ATMPA), sodium ethylenediamine tetramethylene phosphonate (EDTMPS), and diethyl triamine pentamethylene phosphonic acid (DTPMP)) on the thermal stability and electrochemical performance of the positive electrolyte of vanadium redox flow battery were investigated. With 0.5 wt% addition, most of the selected additives were able to improve the thermal stability of the electrolyte. HEDP and HDTMPA extended the stability time of the pentavalent vanadium electrolyte at 50 °C from 5 days (blank sample) to 30 days and 15 days, respectively. The electrochemical performance of the electrolyte was further investigated by cyclic voltammetry, steady state polarization, and electrochemical impedance spectroscopy tests. It was found that most of the additives enhanced the electrochemical activity of the positive electrolyte, and the diffusion coefficients, exchange current densities, and reaction rate constants of V(IV) species became larger with the addition of these additives. It is verified that the thermal stability and electrochemical stability of the electrolyte are significantly improved by the combination of ATMPA + HEDP or ATMPA + HDTMPA. This study provides a new approach to improve the stability of the positive electrolyte for vanadium redox flow battery.
Comprehensive Performance Assessment of Dual Loop Organic Rankine Cycle (DORC) for CNG Engine: Energy, Thermoeconomic and Environment
Authors: Ping Xu , Yao Baofeng , Zhang Hongguang , Zhang Hongzhi , Liang Jia , Yuan Meng , Niu Kai , Wang Yan
Published: October 2022

The improvement of the overall utilization rate of compressed natural gas (CNG) engine fuel is the basis of efficient energy utilization. On the foundation of heat balance theory of internal combustion engines, this study fully considers the operation characteristics of CNG engines and systematically analyzes the distribution characteristics of different waste heat under variable working conditions. The nonlinear relationship between speed and intercooler heat source becomes evident with the increasing of intake mass flow rate. In accordance with the structural characteristics, the thermodynamic model, heat transfer model and environmental model of dual-loop organic Rankine cycle (DORC) are constructed. The system potential in full working environments is systematically evaluated. Compared with the speed, airmass flow has a significant effect on comprehensive performance of loop. The maximum power, heat transfer area and power output of per unit heat transfer area (POPA) of DORC are 36.42 kW, 23.34 m2, and 1.75 kW/m2, respectively. According to the operating characteristics of different loops, the variation laws of loop performance under the influence of multiple parameters are analyzed. The synergistic influence laws of multiple variables on system performance are also analyzed.
Towards Climate Management of District Heating Enterprises’ Innovative Resources
Authors: Borysiak Olena , Skowron Łukasz , Brych Vasyl , Manzhula Volodymyr , Dluhopolskyi Oleksandr , Sak-Skowron Monika , Wołowiec Tomasz
Published: October 2022

Tracking the trend of restricted access to natural fossil energy resources determines the need to search for alternative energy sources, introducing energy-efficient technologies, and optimizing the energy supply system based on intelligent networks. Understanding district heating enterprises’ readiness to work with innovative renewable resources based on climate neutrality plays a unique role. Thus, this article is devoted to the study of the features of providing and determining the district heating enterprises’ capacity to integrate climate management of innovative resources to produce green thermal energy. The research methodology is based on a combination of systemic, process and cybernetic approaches to determining the resource sustainability of district heating enterprises for implementing climate innovations. The scientific novelty of the study lies in a comprehensive assessment of the ability of district heating enterprises to use renewable resources (biomass, waste, hydropower, solar energy, wind energy) for the production of thermal energy according to such indicators as: an indicator of balanced resource use, an indicator of climate neutrality and an indicator of economic feasibility. The results became the basis to apply the set-theoretical approach to calculate the district heating enterprises’ coefficient of resource sustainability, based on the climate management of innovative resources to produce green thermal energy. The innovation of the fuzzy sets method lies in achieving the set goal without the deep formation of a data dynamics series, particularly interval models. The added scientific value of the method to determine the resource sustainability of district heating enterprises is used to justify the feasibility of integrating climate management with the use of innovative resources through the diversification of renewable energy sources for thermal energy production. The prospects for such results are the basis for future research to develop intersectoral clustering enterprises in the green energy production chain based on a closed cycle of renewable energy resources.
Fiber-Optic Gyroscope Thermal Calibration through Two-Dimensional N-Order Polynomial for Landslide Displacement Monitoring
Authors: Lu Guiying , Tang Huiming , Zhu Yu , Zhang Yongquan , Xu Haifeng
Published: October 2022

A fiber-optic gyroscope (FOG) with lower precision but higher cost advantage is typically selected according to working conditions and engineering budget. Thermal drift is the main factor affecting FOG precision. External thermal calibration methods by algorithms can effectively weaken the influence of thermal drift. This paper presents a thermal calibration method of a two-dimensional N-order polynomial (TDNP) and compares it with artificial neural network (ANN) methods to determine a software FOG thermal calibration method for landslide displacement monitoring. The TDNP thermal calibration coefficient matrix was established, and the thermal calibration capability of the TDNP method with different orders N was evaluated on the basis of error analysis. The ANN model with 1 to 18 hidden neural layers was established on the basis of LM, BR, and SCG algorithms to choose a suitable ANN. Finally, the mean absolute errors of FOG thermal calibration through the TDNP with different orders and the LM were compared. This method was applied in the Huangtupo landslide area, China. The results highlight that the TDNP method with order 5 had better performance and satisfied the requirements of landslide displacement monitoring. The research results can compensate for the lack of adaptability of the FOG thermal calibration method in landslide displacement monitoring.
Campus Microgrid Data-Driven Model Identification and Secondary Voltage Control
Authors: Escobar Eros D. , Manrique Tatiana , Isaac Idi A.
Published: October 2022

Microgrids deal with challenges presented by intermittent distributed generation, electrical faults and mode transition. To address these issues, to understand their static and dynamic behavior, and to develop control systems, it is necessary to reproduce their stable operation and transient response through mathematical models. This paper presents a data-driven low-order model identification methodology applied to voltage characterization in a photovoltaic system of a real campus microgrid for secondary voltage regulation. First, a literature review is presented focusing on secondary voltage modeling strategies and control. Then, experimental data is used to estimate and validate a low-order MIMO (multiple input–multiple output) model of the microgrid, considering reactive power, solar irradiance, and power demand inputs and the voltage output of the grid node. The obtained model reproduced the real system response with an accuracy of 88.4%. This model is used for dynamical analysis of the microgrid and the development of a secondary voltage control system based on model predictive control (MPC). The MPC strategy uses polytopic invariant sets as terminal sets to guarantee stability. Simulations are carried out to evaluate the controller performance using experimental data from solar irradiance and power demand as the system disturbances. Successful regulation of the secondary voltage output is obtained with a fast response despite the wide range of disturbance values.
Experimental Studies of Combustion and Emission Characteristics of Biomass Producer Gas (BPG) in a Constant Volume Combustion Chamber (CVCC) System
Authors: Teh Jun Sheng , Teoh Yew Heng , How Heoy Geok , Idroas Mohamad Yusof , Le Thanh Danh , Nguyen Huu Tho
Published: October 2022

Most of the world’s energy requirements are still derived from natural resources. This will result in a catastrophic energy crisis with negative environmental consequences. The increased energy supply will result in greater consumption of non-renewable sources. The production of biomass producer gas (BPG) from biomass gasification has received significant attention as an alternative fuel due to the depletion of non-renewable resources. This experimental study aimed to determine the flame propagation, flame propagation speed, and chamber pressure trace of BPG at different equivalence ratios. Understanding the characteristics of the BPG’s combustion, finding lower greenhouse gas emissions of BPG, and minimizing the use of fossil fuels is necessary to mitigate these problems. Using the direct visualization technique, an optical constant volume combustion chamber (CVCC) was developed to measure combustion characteristics. Liquid petroleum gas (LPG) was used to compare the flame propagation speed in the CVCC calibration. In comparison to wood pellet (WP), coconut husk (CH), and palm kernel shell (PKS), the chamber peak pressure at ϕ equal to 1 of CH for the combustion of BPG was the lowest at 20.84 bar. At ϕ of 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, and 1.3, the chamber peak pressure of CH was discovered to be around 17.77, 18.12, 18.81, 20.84, 20.39, 17.25, and 16.37 bar, respectively. Compared to the other two types of BPG, CH produced the lowest emissions of CO2 and CO at 2.03% and 0.022%, respectively. In conclusion, the CH had the lowest chamber peak pressure and emissions due to the lower heating value (LHV) being relatively lower.