bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated Pavement Construction Inspection Using Uncrewed Aerial Systems (UAS)—Hot Mixed Asphalt (HMA) Temperature Segregation
Authors: Samsami Reihaneh , Mukherjee Amlan , Brooks Colin
Published: June 2023

Temperature segregation in Hot Mixed Asphalt (HMA) pavement construction leads to performance problems, such as reduced fatigue life. During construction, Quality Assurance (QA) inspection procedures are required to evaluate the pavement condition and detect the segregated areas. In traditional HMA highway construction inspection processes, temperature differences are investigated manually, by sampling the HMA behind the paver. In these processes, inspectors are required to work adjacent to traffic and alongside moving or backing equipment. These processes do not provide a complete temperature profile of the mat, endanger the inspectors’ safety, and require on-site experienced inspectors. An Uncrewed Aerial System (UAS) enables HMA pavement construction inspection to be conducted within a remote, non-destructive, safe, and efficient framework. The objective of this research is to design an automated UAS imaging workflow for HMA pavement construction inspection, mainly locating temperature segregation. The primary contribution of this paper is to provide Departments of Transportations (DOTs) and contractors with workflows for creating enhanced remote inspection procedures and detailed thermal profiles of the placed HMA mat. The application of the proposed workflow is illustrated using an HMA construction project in Michigan.
Chattering Reduction of Sliding Mode Control for Quadrotor UAVs Based on Reinforcement Learning
Authors: Wang Qi , Namiki Akio , Asignacion Abner , Li Ziran , Suzuki Satoshi
Published: June 2023

Sliding mode control, an algorithm known for its stability and robustness, has been widely used in designing robot controllers. Such controllers inevitably exhibit chattering; numerous methods have been proposed to deal with this problem in the past decade. However, in most scenarios, ensuring that the specified form and the parameters selected are optimal for the system is challenging. In this work, the reinforcement-learning method is adopted to explore the optimal nonlinear function to reduce chattering. Based on a conventional reference model for sliding mode control, the network output directly participates in the controller calculation without any restrictions. Additionally, a two-step verification method is proposed, including simulation under input delay and external disturbance and actual experiments using a quadrotor. Two types of classic chattering reduction methods are implemented on the same basic controller for comparison. The experiment results indicate that the proposed method could effectively reduce chattering and exhibit better tracking performance.
Some Remarks on the Boundary of Thermodynamic Stability
Authors: Toikka Alexander , Misikov Georgii , Toikka Maria
Published: June 2023

In this paper, we have considered some elements of the classical phenomenological theory of thermodynamic stability, which seem controversial and ambiguous. The main focus is on the conditions of the stability boundary; a new version of the derivation of the relations defining the specified boundary is proposed. Although the final results, in general, coincide with the classical relations, the described approach, from our point of view, provides a clearer and more accurate idea of the stability conditions and their boundaries.
Multilayer Perceptron Network Optimization for Chaotic Time Series Modeling
Authors: Qiao Mu , Liang Yanchun , Tavares Adriano , Shi Xiaohu
Published: June 2023

Chaotic time series are widely present in practice, but due to their characteristics—such as internal randomness, nonlinearity, and long-term unpredictability—it is difficult to achieve high-precision intermediate or long-term predictions. Multi-layer perceptron (MLP) networks are an effective tool for chaotic time series modeling. Focusing on chaotic time series modeling, this paper presents a generalized degree of freedom approximation method of MLP. We then obtain its Akachi information criterion, which is designed as the loss function for training, hence developing an overall framework for chaotic time series analysis, including phase space reconstruction, model training, and model selection. To verify the effectiveness of the proposed method, it is applied to two artificial chaotic time series and two real-world chaotic time series. The numerical results show that the proposed optimized method is effective to obtain the best model from a group of candidates. Moreover, the optimized models perform very well in multi-step prediction tasks.
A Lightweight CP-ABE Scheme with Direct Attribute Revocation for Vehicular Ad Hoc Network
Authors: Liu Yilong , Xu Shengwei , Yue Ziyan
Published: June 2023

Ciphertext-Policy Attribute-Based Encryption (CP-ABE) technology provides a new solution to address the security and fine-grained access control of traffic information in vehicular ad hoc networks (VANETs). However, in most CP-ABE schemes for VANETs, attribute revocation suffers from high system consumption and complex revocation operations, as well as from high computational overhead and low efficiency due to the use of bilinear pairwise operations. Based on this, this paper proposes a lightweight CP-ABE scheme that supports direct attribute revocation in VANETs. The scheme implements an agent-based direct attribute revocation mechanism by separating dynamic and static attributes of vehicle terminals, which reduces system consumption and simplifies the revocation operation process. The scheme uses scalar multiplication on elliptic curves instead of bilinear pairing operations and uses computational outsourcing techniques to reduce the terminal decryption cost and improve the efficiency of the scheme. The security and performance analysis shows that the overall efficiency of our scheme is better than the existing schemes under the premise of ensuring data confidentiality and integrity.
Developing a Burn-Specific Family-Centered Care (BS-FCC) Framework: A Multi-Method Study
Authors: Bayuo Jonathan , Agbeko Anita Eseenam
Published: June 2023

A burn has been described as a family injury warranting the delivery of family-centered care (FCC) across the continuum of burns management. This assertion notwithstanding, only limited progress has been made to develop and implement FCC interventions in the burn unit. As a starting point, this study sought to formulate a tentative framework to underpin FCC in burn care. A multi-method design comprising an umbrella review and the secondary data analysis of qualitative datasets was employed. Following these, the findings were merged and aligned to the Universal Model of FCC to formulate the burn-specific FCC framework. For the umbrella review, four review articles met the criteria for inclusion. Following a data synthesis of the review findings and their integration with the qualitative dataset, four meta-themes that encapsulate the shared needs/concerns of family members of both pediatric and adult burn survivors emerged: (1) psychosocial concerns, (2) issues relating to role changes, (3) logistical concerns, and (4) requiring information. These issues were mapped to the following components of the Universal Model of FCC: family support, education, collaboration, and communication. All these are underpinned by dedicated policies, procedures, and consideration of the family context. Testing and further empirical work are needed to refine and implement the framework across the continuum of burn management.
The Impact of Openness on Human Capital: A Study of Countries by the Level of Development
Authors: Dao Thi Bich Thuy , Khuc Van Quy
Published: June 2023

This study investigates the impact of openness on human capital in 112 countries worldwide in 2000–2019. An two-stage least square fixed-effect model with instrumental variables is used to unravel the complicated relationship between human capital and its key determinants. The empirical results show that the impacts of openness vary greatly among different groups of countries. For example, while FDI has no effect on human capital in developed and upper-middle-income developing countries, its effect is positive in lower-middle-income countries and negative in low-income countries. Exports stimulate human capital formation in developed countries but in low-income developing countries, they act as an impediment to human capital formation. Imports have a positive effect on human capital in developing countries; however, in developed countries, the effect of imports on human capital is negative. International cooperation effectively raises the level of human capital in developed, upper-middle-income and low-income countries; however, it has no effect in lower-middle-income countries. In light of mindsponge—mindspongeconomics and the SM3D knowledge management system, the study’s findings particularly shed light on the long-term development roadmap associated with human capital and openness expansion in less developed and emerging countries in years to come.
Conditional Encoder-Based Adaptive Deep Image Compression with Classification-Driven Semantic Awareness
Authors: Lei Zhongyue , Zhang Weicheng , Hong Xuemin , Shi Jianghong , Su Minxian , Lin Chaoheng
Published: June 2023

This paper proposes a new algorithm for adaptive deep image compression (DIC) that can compress images for different purposes or contexts at different rates. The algorithm can compress images with semantic awareness, which means classification-related semantic features are better protected in lossy image compression. It builds on the existing conditional encoder-based DIC method and adds two features: a model-based rate-distortion-classification-perception (RDCP) framework to control the trade-off between rate and performance for different contexts, and a mechanism to generate coding conditions based on image complexity and semantic importance. The algorithm outperforms the QMAP2021 benchmark on the ImageNet dataset. Over the tested rate range, it improves the classification accuracy by 11% and the perceptual quality by 12.4%, 32%, and 1.3% on average for NIQE, LPIPS, and FSIM metrics, respectively.
A Semi-Elliptical UWB Folded Dipole Antenna
Authors: Greard Romain , Himdi Mohamed , Lemur Dominique , Le Dem Gwenal , Thaly Pierre , Le Meins Cyrille
Published: June 2023

In this paper, a novel structure of a semi-elliptical folded dipole for ultra-wideband (UWB) receiving applications is discussed. This proposed antenna has a directive radiation pattern resulting in a high gain over the bandwidth. The design uses a planar technology including a microstrip line to slot line transition and optimized curves to obtain a measured impedance bandwidth of 2.3–26 GHz with the condition of S11 < −6 dB (level accepted for receiving antenna) and meets S11 < −10 dB in several bands. Additionally, the simulated gain ranges from 5 dBi to 9.5 dBi across the entire bandwidth with an efficiency of at least 75%. This antenna model offers a reconfiguration capability. The symmetrical feeding used in this antenna creates the directive behavior. Characteristics of this semi-elliptical folded dipole antenna make it suitable for modern wireless communications, such as 5 G around 3.5 GHz, and easy to integrate in antenna arrays (MIMO systems). The four ports of the antenna also make it a candidate for radiation pattern reconfigurability applications reducing in this way the number of elements in network antennas.
Beyond Land: A Review of Benchmarking Datasets, Algorithms, and Metrics for Visual-Based Ship Tracking
Authors: Rocha Ranyeri do Lago , de Figueiredo Felipe A. P.
Published: June 2023

Object tracking has gained much interest in the last few years, especially in the context of multiple object tracking. Many datasets used for tracking provide video sequences of people and objects in very different contexts. Although it has been attracting much attention, no dataset or tracking algorithm has been applied to coastal surveillance and ship tracking. Besides image/video-based tracking technologies, other technologies, such as radar and automatic identification systems (AISs), are also used for this task, especially in maritime applications. In the AIS case, commonly known issues, such as information omission, remain to be dealt with. As for radars, the most important issue is the impossibility of identifying the ship type/class and correlating it with AIS information. However, image/video-based solutions can be combined with these technologies to mitigate or even solve these issues. This work aims to review the most recent datasets and state-of-the-art tracking algorithms (also known as trackers) for single or multiple objects tracking for objects in general and its possibilities for maritime scenarios. The goal is to gain insights for developing novel datasets; benchmarking metrics; and mainly, novel ship tracking algorithms.
A Robust LC-π Matching Network for 112 Gb/s PAM4 Receiver in 28 nm CMOS
Authors: Han Gengshi , Zheng Xuqiang , Xu Hua , Wang Zedong , Wen Zhanhao , He Yu , Chen Bao , Liu Xinyu
Published: June 2023

This article presents analysis, design details, and simulation results of an impedance matching network designed for a 112 Gb/s pulse-amplitude-modulation-4 (PAM4) receiver using an LC-π structure. We designed the bonding wire as a part of the matching network, which reduced design pressure on the equalizer as there will be no need to compensate the loss of the chip package. To avoid robustness issues caused by the fluctuation of the bonding wire inductance, the matching network is designed to bw adjustable by the capacitance on PCB and the terminal resistance. We analyzed the parasitics in the layout and the influence of nearby and dummy metals and obtained reliable simulation results through electromagnetic field simulation. This matching network is designed with a 28 nm CMOS process. Post-layout simulation results show that with bonding wire inductance changing from 150 pH to 250 pH, it can always meet CEI-112G-XSR-PAM4 Extra Short Reach Interface requirements.
The Closed-Loop Control of the Half-Bridge-Based MMC Drive with Variable DC-Link Voltage
Authors: Espinoza Mauricio , Diaz Matias , Espina Enrique , Mora Andrés , Letelier Arturo , Donoso Felipe , Cárdenas Roberto
Published: June 2023

The modular multilevel converter (MMC) based on half-bridge modules is a power converter topology suitable for high-power medium-voltage variable-speed drives. However, the voltage of its flying capacitors is negatively affected when low frequencies appear at the AC port. This paper analyzes the influence of using a variable DC port voltage in a machine-side MMC by implementing a closed-loop approach, ensuring a constant voltage fluctuation in the capacitors of the MMC during the whole operating range. The effectiveness of the proposed control scheme is demonstrated through simulation studies and experimental validation tests conducted using a 7.5 kW experimental prototype composed of an induction machine fed by an MMC with 18 half-bridge cells.
Grouping Sensors for the Key Distribution of Implicit Certificates in Wireless Sensor Networks
Authors: Chang Ray-I , Chiang Chien-Wen , Hung Yu-Hsin
Published: June 2023

As sensor nodes communicate via wireless channels, information security is essential for wireless sensor networks. Efficient protection mechanisms to ensure data security among nodes are critical. This study developed the bi-directed grouping (top-down grouping (TDG) and bottom-up grouping (BUG)) methods. In this study, we propose a group-based key distribution method, “aggregator-based grouping” (ABG), which combines the advantages of TDG and BUG to address the security issues of nodes. It employs horizontal and vertical searches, which are based on breadth-first and aggregator searches, respectively. A node performs encryption and decryption only when it requires either data aggregation or inter-group communication. The secure aggregation method can be applied to key-grouping management. We compared the proposed method with TDG and BUG using the same number of groups and network structure. For a network with maximum group members of 50 (total sensor nodes = 1000), compared with TDG and BUG, ABG reduced the number of encryption and decryption operations by ~36%. ABG avoids unnecessary encryption and decryption in the network.
Co-Combustion of Hydrogen with Diesel and Biodiesel (RME) in a Dual-Fuel Compression-Ignition Engine
Authors: Tutak Wojciech , Jamrozik Arkadiusz , Grab-Rogaliński Karol
Published: June 2023

The utilization of hydrogen for reciprocating internal combustion engines remains a subject that necessitates thorough research and careful analysis. This paper presents a study on the co-combustion of hydrogen with diesel fuel and biodiesel (RME) in a compression-ignition piston engine operating at maximum load, with a hydrogen content of up to 34%. The research employed engine indication and exhaust emissions measurement to assess the engine’s performance. Engine indication allowed for the determination of key combustion stages, including ignition delay, combustion time, and the angle of 50% heat release. Furthermore, important operational parameters such as indicated pressure, thermal efficiency, and specific energy consumption were determined. The evaluation of dual-fuel engine stability was conducted by analyzing variations in the coefficient of variation in indicated mean effective pressure. The increase in the proportion of hydrogen co-combusted with diesel fuel and biodiesel had a negligible impact on ignition delay and led to a reduction in combustion time. This effect was more pronounced when using biodiesel (RME). In terms of energy efficiency, a 12% hydrogen content resulted in the highest efficiency for the dual-fuel engine. However, greater efficiency gains were observed when the engine was powered by RME. It should be noted that the hydrogen-powered engine using RME exhibited slightly less stable operation, as measured by the COVIMEP value. Regarding emissions, hydrogen as a fuel in compression ignition engines demonstrated favorable outcomes for CO, CO2, and soot emissions, while NO and HC emissions increased.
Stochastic Multi-Objective Optimal Reactive Power Dispatch with the Integration of Wind and Solar Generation
Authors: Bhurt Faraz , Ali Aamir , Keerio Muhammad U. , Abbas Ghulam , Ahmed Zahoor , Mugheri Noor H. , Kim Yun-Su
Published: June 2023

The exponential growth of unpredictable renewable power production sources in the power grid results in difficult-to-regulate reactive power. The ultimate goal of optimal reactive power dispatch (ORPD) is to find the optimal voltage level of all the generators, the transformer tap ratio, and the MVAR injection of shunt VAR compensators (SVC). More realistically, the ORPD problem is a nonlinear multi-objective optimization problem. Therefore, in this paper, the multi-objective ORPD problem is formulated and solved considering the simultaneous minimization of the active power loss, voltage deviation, emission, and the operating cost of renewable and thermal generators. Usually, renewable power generators such as wind and solar are uncertain; therefore, Weibull and lognormal probability distribution functions are considered to model wind and solar power, respectively. Due to the unavailability and uncertainty of wind and solar power, appropriate PDFs have been used to generate 1000 scenarios with the help of Monte Carlo simulation techniques. Practically, it is not possible to solve the problem considering all the scenarios. Therefore, the scenario reduction technique based on the distance metric is applied to select the 24 representative scenarios to reduce the size of the problem. Moreover, the efficient non-dominated sorting genetic algorithm II-based bidirectional co-evolutionary algorithm (BiCo), along with the constraint domination principle, is adopted to solve the multi-objective ORPD problem. Furthermore, a modified IEEE standard 30-bus system is employed to show the performance and superiority of the proposed algorithm. Simulation results indicate that the proposed algorithm finds uniformly distributed and near-global final non-dominated solutions compared to the recently available state-of-the-art multi-objective algorithms in the literature.
Energy Savings for Various Residential Appliances and Distribution Networks in a Malaysian Scenario
Authors: Seva Bala Sundaram Mithila , Tan ChiaKwang , Selvaraj Jeyraj , Bakar Ab. Halim Abu
Published: June 2023

This paper presents a detailed study of the energy savings that can be achieved through residential appliances by implementing conservation voltage reduction (CVR). The computed energy savings are derived from the ZIP coefficients of a load model (static) under varying voltage conditions that represent the power consumed by each appliance tested. Multiple studies have shown energy savings at the substation level but not at the level of a specific residence and appliance; hence, the latter is the focus of this analysis. The appliances are determined based on the type of heating and cooling loads, and the daily duration of use for each appliance, which contributes to the total monthly consumption that is billed for a household are included in this study. Energy savings in Malaysia has been a focus of many current studies, and this study is the first attempt to achieve energy savings through the implementation of CVR. No published work has compared individual appliances that truly benefits from CVR, and this is addressed in this study. The main contribution of this study is that it provides very detailed and measured data that are used to analyze and generate energy savings for very specific residential appliances intended to meet every 1% voltage drop. The load model is developed for the common household appliances in Malaysia, and then a voltage reduction study is applied to the appliances as well as the Malaysian distribution networks. Here, we also provide insight for performing voltage reduction at an electric vehicle (EV) charging station in Malaysia. The results of this study should serve as a foundation for all practicing utilities engineers to address the issue of CVR in Malaysia. The CVR factors for residential, commercial, and industrial networks in Malaysia are also published in this paper.
Evaluation of Machine Learning Methods on Large-Scale Spatiotemporal Data for Photovoltaic Power Prediction
Authors: Sauter Evan , Mughal Maqsood , Zhang Ziming
Published: June 2023

The exponential increase in photovoltaic (PV) arrays installed globally, particularly given the intermittent nature of PV generation, has emphasized the need to accurately forecast the predicted output power of the arrays. Regardless of the length of the forecasts, the modeling of PV arrays is made difficult by their dependence on weather. Typically, the model projections are generated from datasets at one location across a couple of years. The purpose of this study was to compare the effectiveness of regression models in very short-term deterministic forecasts for spatiotemporal projections. The compiled dataset is unique given that it consists of weather and output power data of PVs located at five cities spanning 3 and 6 years in length. Gated recurrent unit (GRU) generalized the best for same-city and cross-city predictions, while long short-term memory (LSTM) and ensemble bagging had the best cross-city and same-city predictions, respectively.
Analysis of Photovoltaic Plants with Battery Energy Storage Systems (PV-BESS) for Monthly Constant Power Operation
Authors: Tejero-Gómez Juan A. , Bayod-Rújula Ángel A.
Published: June 2023

Photovoltaic generation is one of the key technologies in the production of electricity from renewable sources. However, the intermittent nature of solar radiation poses a challenge to effectively integrate this renewable resource into the electrical power system. The price reduction of battery storage systems in the coming years presents an opportunity for their practical combination with utility-scale photovoltaic plants. The integration of properly sized photovoltaic and battery energy storage systems (PV-BESS) for the delivery of constant power not only guarantees high energy availability, but also enables a possible increase in the number of PV installations and the PV penetration. A massive data analysis with long-term simulations is carried out and indicators of energy unavailability of the combined system are identified to assess the reliability of power production. The proposed indicators allow to determine the appropriate sizing of the battery energy storage system for a utility-scale photovoltaic plant in a planning stage, as well as suggest the recommended operating points made for each month through a set of graphs and indicators. The presence of an inflection zone has been observed, beyond which any increase in storage does not generate significant reductions in the unavailability of energy. This critical zone is considered the sweet spot for the size of the storage, beyond which it is not sensible to increase its size. Identifying the critical point is crucial to determining the optimal storage size. The system is capable of providing reliable supply of constant power in monthly periods while ensuring capacity credit levels above 95%, which increases the penetration of this renewable resource. Despite the fact that the study focuses exclusively on the analysis from an energy perspective, it is important to consider the constraints associated to real storage systems and limit their oversizing.
Enhancing Survey Efficiency and Predictive Ability in Energy System Design through Machine Learning: A Workflow-Based Approach for Improved Outcomes
Authors: Chapman Andrew
Published: June 2023

The design of a desirable, sustainable energy system needs to consider a broad range of technologies, the market landscape, and the preferences of the population. In order to elicit these preferences, both toward lifestyle factors and energy system design, stakeholder engagement is critical. One popular method of stakeholder engagement is the deployment and subsequent analysis of a survey. However, significant time and resources are required to design, test, implement and analyze surveys. In the age of high data availability, it is likely that innovative approaches such as machine learning might be applied to datasets to elicit factors which underpin preferences toward energy systems and the energy mix. This research seeks to test this hypothesis, utilizing multiple algorithms and survey datasets to elicit common factors which are influential toward energy system preferences and energy system design factors. Our research has identified that machine learning models can predict response ranges based on preferences, knowledge levels, behaviors, and demographics toward energy system design in terms of technology deployment and important socio-economic factors. By applying these findings to future energy survey research design, it is anticipated that the burdens associated with survey design and implementation, as well as the burdens on respondents, can be significantly reduced.
Efficient and Reliable Power-Conditioning Stage for Fuel Cell-Based High-Power Applications
Authors: Iqbal Mehroze , Benmouna Amel , Claude Frederic , Becherif Mohamed
Published: June 2023

Mainstream power-conditioning devices such as boost converters are frequently utilized for developing a compatible interface between a fuel cell, electrical storage, and high power loads. The conventional power stage comprising a unique boost converter suffers from low efficiency and poor reliability due to excessive power losses, particularly in high-power applications. Additionally, the presence of high ripple contents can reduce the lifespan of the fuel cell itself. With this background, this paper proposes and experimentally validates a physical components-assisted equivalent power-sharing strategy between parallel-coupled boost converters (PCCs) that is subjected to a wide spectrum of low-voltage–high-power conditions. The operation of PCCs is bottlenecked by several practical limitations, such as the presence of inner circulating currents (ICCs) and stability issues associated with the equivalent sharing of power. To overcome these limitations, a module of reverse blocking diodes is suggested to avoid ICCs between the PCCs. Further, an equalization filter is properly placed to improve the equivalent power-sharing capability. The proposed strategy is theoretically assessed in a MATLAB/Simulink environment with a 6 kW proton exchange membrane fuel cell (PEMFC) as the main power source. A scaled-down laboratory setup consisting of an 810 W PEMFC stack, an electronic load, three boost converters, and a filter circuit is then designed and critically evaluated. A consistent agreement is observed between the experimental findings and the simulation results under realistic operating conditions.
Time Estimation Algorithm of Single-Phase-to-Ground Fault Based on Two-Step Dimensionality Reduction
Authors: Lin Xin , Chen Haoran , Xu Kai , Xu Jianyuan
Published: June 2023

The fault detection time identified by relying on the over-voltage criterion of zero-sequence voltage often lags behind the actual occurrence time of ground faults, which may cause fault protection methods based on transient quantity principles to miss fault characteristics and lose their protection capability. To accurately estimate the time of occurrence of a single-phase-to-ground fault, this paper proposes a two-step dimensionality reduction algorithm for estimating the time of occurrence of a single-phase-to-ground fault in a distribution network. This algorithm constructs a filter based on Empirical Mode Decomposition (EMD) to establish a high-dimensional feature dataset based on the zero-sequence current of all feeders. After Principal Component Analysis and Hilbert Mapping Algorithm, the high-dimensional data are reduced to two dimensions to construct a two-dimensional feature dataset. The density-based clustering method is used to adaptively divide the data into two categories, fault data and non-fault data, so as to estimate the time of occurrence of the fault. The paper designs 11 sets of experiments including 7 common high-resistance grounding mediums to verify the accuracy of the fault time recognition of this algorithm. The accuracy of this algorithm is within 7.3 ms and it exhibits better detection performance compared to the threshold detection method.
Structural, Thermal, and Electrochemical Properties of Ce 0.8−2x Sm 0.2 Zrx Mgx O2−d, {x = 0.05, 0.1 & 0.15} Promising Electrolyte Compounds for (IT-SOFCs) Applications
Authors: Abdalla Abdalla. M. , Azad Abul K. , Dawood Mohamed M. K. , Taweekun Juntakan
Published: June 2023

CSZM compounds were synthesized by dry chemistry route with 5, 10, and 15% dopant of Mg dopants in the Ce 0.8−2x Sm 0.2 Zrx Mgx O2−d, {x = 0.05, 0.1 & 0.15}. The newly investigated materials were physically, chemically, and electrochemically studied and have shown promising results. The CSZM was crystalized in a fluorite structure with a pure cubic phase in a space group Fm3m and cell parameter a = 5.401742 °A and theoretical density from 7.6 to 8.9 after firing in the air with a final temperature of 1400 °C. Characterization of the structure and indexing of electrolyte materials were made after X-ray diffraction (XRD) testing. A Scanning electron microscope (SEM) morphological analysis was used to examine the microstructure details. Electrochemical impedance spectroscopy (EIS) measurements were performed from 400 °C to 700 °C which show the highest conductivity value of 1.0461 × 10+1 S/cm at 700 °C. In comparison, the minimum value was 2.7329 × 10−2 S/cm at 400 °C, and the total activation energy (Ea°A) was found to be 0.6865 eV under 5% H2/Ar.
Energy Retrofitting Technologies of Buildings: A Review-Based Assessment
Authors: Madushika U. G. D. , Ramachandra Thanuja , Karunasena Gayani , Udakara P. A. D. S.
Published: June 2023

Demand for energy and resources is increasing day by day. The construction industry plays a major role in the consumption of energy and resources. Buildings that were built before energy-efficient sustainable practices became popular consume a larger portion of energy as compared to the new buildings. As a result, enhancing energy performance through retrofitting of those old buildings is a major concern in the construction industry. In the modern built environment, there are many technologies available in the market to enhance the energy performance of such buildings. However, the body of knowledge regarding energy retrofitting technologies is still scattered. Therefore, in this study, a review-based assessment was undertaken to identify energy retrofitting technologies that could enhance energy performance in existing buildings. The Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was followed during the article screening and selection for this study. Following a systematic filtering process, a total of 149 out of 643 research contributions have been considered for in-depth analysis of energy retrofitting classification and respective energy retrofitting technologies. According to the review, energy retrofitting technologies are categorized into three main aspects; building envelope retrofitting, building system retrofitting, and renewable energy. The study found thirty-seven (37) energy-related retrofitting technologies in the current context. Further, 25 possible energy retrofitting technologies were identified under the six main subcategories, including façade, roof floor, window, door, and orientation. In terms of building system retrofitting, 10 possible energy retrofitting technologies were identified under the HVAC system and lighting system. The remaining two technologies identified under the renewable energy category were solar and wind technology. The review further confirms that the application of energy-related retrofitting technologies has the highest contribution in terms of energy and cost saving of existing buildings. It is expected that this outcome would better guide stakeholders in decision-making with regard to the selection of energy retrofitting technologies in a given context.
A 600 W Photovoltaic Groundwater Pumping System Based on LLC Converter and Constant Voltage MPPT
Authors: Palmiro Flavio , Godoy Ruben B. , Mateus Tiago H. d. A. , de Andrade Nicholas D.
Published: June 2023

The work consists of the development of a market-friendly 600 W photovoltaic battery-less water pumping system. The system is composed of four 280 Wp solar panels, an auxiliary 10 W solar panel, a three-phase converter and a ½ horsepower (hp) submersible water pump. The electronic stage involves a resonant DC-DC converter in series with a voltage source three-phase inverter. The novelties of this work are related to the use of a resonant DC-DC converter with fixed duty-cycle and frequency for water pumping application, the use of Silicon Carbide Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) for solving converter startup issues, and the use of a constant voltage maximum power tracking (MPPT) algorithm with auxiliary panels. The work displays the design of the converter, simulation and experimental results, discussions, and cost evaluation. The feasibility of the system is studied for the water requirements of a beef cattle farm in Brazil.
A Real-Time Calculation Method to Improve Boiler Safety in Deep Peak Shaving Cases
Authors: Guo Xin , Zhao Guangbo , Zhang Zhecheng , Feng Dongdong , Wang Yongjie , Zhang Zhengshun
Published: June 2023

To tackle the overheating problem of the heating surface in deep peak shaving, it is urgent to develop working substance (steam) temperature regulation and heating surface safety control technologies that combine combustion and hydrodynamic instability evaluation. This work relies on a 1000 MW boiler involved in deep peak shaving, and adopts CFD numerical simulation technology to obtain reasonable holographic heat load data of the boiler. The heat load data and the working substance side data are coupled to develop a real-time performance calculation model that combines combustion and hydrodynamic steam temperature. Real-time monitoring of the local position of the boiler water wall and the convection heating surface can be achieved through the three steps: heat load screening, heat exchange process calculation, and result display. The results show that through the corresponding expression of on-site industrial parameters and CFD simulation data, the effective analysis, extraction, modeling and optimization of the operation data can be realized for real-time online monitoring and intelligent early warning of the entire working condition. The model error is less than 2 °C and the model can realize early warnings at 5 min, so as to ensure the safety and stability of boiler operation and save the operating cost of the power plant to a certain extent.
Simulation and Control Strategy Study of the Hydrogen Supply System of a Fuel Cell Engine
Authors: Zhao Ming , Wang Wenbin , Zhu Xiaochun , Cao Mengxue , Gao Zhengyuan , Sun Ke , Bai Shuzhan , Li Guoxiang
Published: June 2023

The hydrogen supply system is one of the important components of a hydrogen fuel cell engine, and its performance has an important impact on the economy and power of the engine system. In this paper, a hydrogen supply system based on cyclic mode is designed for a hydrogen fuel cell stack with a full load power of 150 kW, and the corresponding hydrogen fuel cell engine simulation model is built and validated. The control strategy of the fuel cell hydrogen supply system is developed, and its effect is verified through bench tests. The results show that the developed control strategy can keep the volume fraction of nitrogen below 6%, the hydrogen excess ratio does not exceed 1.5 under medium and high operating conditions, the anode pressure is relatively stable, and the stack can operate efficiently and reliably.
A Novel Model for the Real-Time Evaluation of Hole-Cleaning Conditions with Case Studies
Authors: Al-Rubaii Mohammed , Al-Shargabi Mohammed , Al-Shehri Dhafer
Published: June 2023

The main challenge in deviated and horizontal well drilling is hole cleaning, which involves the removal of drill cuttings and maintaining a clean borehole. Insufficient hole cleaning can lead to issues such as stuck pipe incidents, lost circulation, slow rate of penetration (ROP), difficult tripping operations, poor cementing, and formation damage. Insufficient advancements in real-time drilling evaluation for complex wells can also lead to drilling troubles and an increase in drilling costs. Therefore, this study aimed to develop a model for the hole-cleaning index (HCI) that could be integrated into drilling operations to provide an automated and real-time evaluation of deviated- and horizontal-drilling hole cleaning based on hydraulic and mechanical drilling parameters and drilling fluid rheological properties. This HCI model was validated and tested in the field in 3 wells, as it was applied when drilling 12.25″ intermediate directional sections and an 8.5″ liner directional section. The integration of the HCI in Well-A and Well-B helped achieve much better well drilling performance (50% ROP enhancement) and mitigate potential problems such as pipe sticking due to hole cleaning and the slower rate of penetration. Moreover, the HCI model was also able to identify hole-cleaning efficiency during a stuck pipe issue in Well-C, which highlights its potential usage as a real-time model for optimizing drilling performance and demonstrates its versatility.
Investigation of the Kinetics of Pressure Coal Char Hydrogasification
Authors: Gil Stanisław , Bialik Wojciech , Mocek Piotr , Rimár Miroslav , Kizek Ján , Polivka Nikolas
Published: June 2023

The authors of the study focused on the problem of hydrogasifying coal extracted from a particular location. Since hydrogen is transparent to radiation, it can only be heated by convection. To achieve this, we developed a swirler and utilized Fluent software (version 19.0) to simulate the primary flow vectors and the temperature distribution of hydrogen in the hydrogasification reactor. The process was carried out under varying conditions, including temperatures ranging up to 1173 K, pressures of up to 8 MPa, and gas flow rates between 0.5 and 5 dmn3 min−1. The results showed that the carbon reactivity of the char was high up to a certain level of carbon conversion. In this study, the kinetic equations of the hydrogasification process were developed based on the theory of active centers. The researchers also evaluated the kinetic constants at the maximum reaction rate for the analyzed chars. The analysis was conducted for four extreme cases of process parameters, which included temperatures of 973 and 1173 K as well as pressures of 6 and 8 MPa. The results showed that the maximum hydrogasification reactivity of chars could be accurately described using equations for both the first- and second-order reactions toward hydrogen. This was likely due to the use of a narrow pressure range of 6–8 MPa during the experiments. The kinetic equations developed in the study could be used to model the process on a technical scale.
Parametric Study and Optimization of No-Blocking Heliostat Field Layout
Authors: Derbal Dhikra , Abderrezak Abdallah , Chehaidia Seif Eddine , Amin Majdi T. , Mosaad Mohamed I. , Abdul-Fattah Tarek A.
Published: June 2023

Generating electric power using solar thermal systems is effective, particularly for countries with high solar potential. In order to decide on a relevant location to implement the solar tower plant and develop the mathematical model of a no-blocking heliostat field, a meteorological assessment was discussed in this paper. In addition, a parametric study was examined to evaluate the effect of the designed parameters (heliostat size, heliostat height from the ground, tower height, receiver aperture, and the minimum radius) on the solar field’s performance. The preliminary solar field was then compared to the final design using the optimal design parameters. The obtained results showed that “Tamanrasset City” satisfied the necessary conditions for implementing a solar tower plant. According to preliminary solar field generation, no heliostat blocked its neighbor with a blocking efficiency of 100%. An analysis of its performance revealed that the optimized solar field would be capable of producing 15, 6571 MW, operating at an optical efficiency of 76.95%, and the enhancement rate of both efficiency and power output was 8.1%.
Outbreak Investigation of Typhoid Fever in the District of Gabes, South of Tunisia
Authors: Hechaichi Aicha , Bouguerra Hind , Letaief Hajer , Safer Mouna , Missaoui Lamia , Cherif Amal , Farah Saffar , Jabrane Houcine , Atawa Taoufik , Yahia Hamdi , Hamdouni Hayet , Zitoun Khadija , Chahed Karim , Laamouri Ramzi , Daaboub Jaber , Rabhi Mohamed , Salah Afif Ben , Chahed Mohamed Kouni , Bouafif Ben Alaya Nissaf
Published: June 2023

Typhoid fever is a significant public health concern in many parts of the world, particularly in developing countries with poor sanitation and hygiene conditions. In July 2016, an outbreak of typhoid fever occurred in Ghannouche, located in the south of Tunisia. This paper reports the results of a field investigation undertaken to identify possible transmission pathways and risk factors in order to propose control and preventive measures. A retrospective cohort study including a passive and active case finding, as well as an environmental and bacteriological investigation was conducted from July to September 2016. A case was defined as a person residing or having stayed in Ghannouche and having presented from the beginning of June clinical signs suggestive of typhoid fever, with, for a confirmed case, laboratory isolation of S.Tyhi, and for a probable case, an epidemiological link with a confirmed case. Attack rates were determined, and risk ratios were estimated with respect to exposures. Unadjusted and adjusted odds ratios were estimated using binary logistic regression. Among the 628 subjects investigated, 102 cases of typhoid fever were identified (74 confirmed and 28 probable) with an overall attack rate of 16.24%. Over 56% of cases were male and those under 10 years old were most affected (38.2%% of cases) with a median age of 12 years (interquartile range 5 to 25 years). The main clinical signs were fever (95%) and diarrhea (57%). Young age (adjusted OR = 0.95 and 95% CI = 0.93–0.97), low level of education (adjusted OR = 4.76 and 95% CI = 1.34–16.81), and the habitat type Arab or rudimentary house (adjusted OR = 4.93 and 95% CI = 2.61–8.27) were the socio-demographic factors independently associated with typhoid fever. Typhoid fever was found to be associated with drinking softened water (adjusted OR = 2.64 and 95% CI = 1.16–4.82), eating raw fruit and vegetables from family gardens (adjusted OR = 6.13 and 95% CI = 3.66–11.06), and using uncontrolled waste disposal (adjusted OR = 3.52 and 95% CI = 2.03–6.94). A total of 110 drinking water samples were analyzed; out of the 38 samples of softened water, 12 were non-compliant and 5 were positive for Salmonella. The screening activity identified two asymptomatic carriers, one of whom was a softened water seller. We concluded that drinking softened water from informal or unauthorized sale units, consuming fruit and vegetables from family gardens, uncontrolled dumping of household waste, and poor socio-economic conditions increase the risk of typhoid fever in this region. Many recommendations were implemented to stop this outbreak and to prevent further episodes.
Research on Spatiotemporal Changes in Carbon Footprint and Vegetation Carbon Carrying Capacity in Shanxi Province
Authors: Yang Xiaojing , Bai Bing , Bai Zhongke
Published: June 2023

The climate and ecological problems caused by excessive carbon dioxide emissions are attracting more and more attention, and the need for carbon reduction has reached a consensus. Carbon peak and carbon neutrality is a solemn commitment made by China to the world and a strategic arrangement to achieve economic and social transformation. This study focused on Shanxi Province, a base of power source and heavy chemical industry in China. Based on energy consumption data, carbon emission data set at the county level, land use data and socioeconomic data, we built a carbon ecological pressure index in order to analyze the spatiotemporal evolution characteristics of the carbon footprint, carbon carrying capacity and carbon ecological security status of each county in Shanxi Province from 2000 to 2020. The results showed that: (1) the total carbon footprint of Shanxi Province increased, and the number of high carbon emission counties showed an increasing trend. The largest part of carbon footprint was coal. (2) The vegetation carbon-carrying capacity showed an increasing trend in general, and forest land was the main contributor to the carbon-carrying capacity. (3) The carbon deficit of Shanxi Province was greater than 0 and behaved as a carbon source. The carbon ecological security decreased from a relatively safe level to a general safe level. (4) The carbon ecological pressure index gradually increased. It was predicted that the carbon ecological security level of each county will remain basically unchanged by 2025 and some will still be at a carbon ecological insecurity level. In general, the carbon ecological pressure index of some counties was still large. It is necessary to strengthen the use of clean energy, optimize the industrial structure and increase the carbon sink of forest land in order to reduce carbon emissions and increase the carbon sink, so as to ensure carbon ecological security and realize the goal of a low-carbon economy.