Hasil untuk "Electricity and magnetism"

Mirko Schäfer, Tiernan Buckley, Frank Boerman et al.

In 2023, Germany's electricity trade balance shifted from net exports to net imports for the first time since 2002, resulting in an increasing discussion of these imports in the public debate. This study discusses different data driven approaches for the analysis of Germany's cross-border trade, with a focus on the methodological challenges to determine the origin of imported electricity within the framework of European electricity market coupling. While scheduled commercial flows from ENTSO-E are often used as indicators, generally these do not correspond to bilateral exchanges between different market actors. In particular, for day-ahead market coupling only net positions have an economically reasonable interpretation, and scheduled commercial exchanges are defined through ex-post algorithmic calculations. Any measure of the origin of electricity imports thus depends on some underlying interpretation and corresponding method, ranging from local flow patterns to correlations in net positions. To illustrate this dependence on methodological choices, we compare different approaches to determine the origin of electricity imports for hourly European power system data for 2024.

Lian Farhadian, Samira Amiri Khoshkar Vandani, Hai-Feng Ji

Dielectric barrier discharge (DBD) plasma provides a solvent-free and energy-efficient approach for the in situ polymerization of styrene on cotton textiles. Traditional methods for polystyrene (PS) coating often require elevated temperatures, chemical initiators, or organic solvents, conditions that are incompatible with porous, heat-sensitive substrates such as cotton. In this work, we demonstrate that DBD plasma can initiate and sustain styrene polymerization directly on cotton fibers under ambient conditions. FT-IR spectroscopy confirms the consumption of the vinyl C=C bond and the formation of atactic, amorphous polystyrene. Thermogravimetric analysis indicates that the cotton coated with DBD polymerized PS exhibits enhanced thermal stability compared to cotton coated with commercial PS. Additionally, UV aging tests confirm that the plasma-deposited coating maintains its hydrophobicity after exposure to light. Together, these findings highlight DBD plasma as a sustainable and effective approach for producing hydrophobic, thermally robust, and UV-stable textile coatings without the need for solvents, initiators, or harsh processing conditions.

You-Seok Yeoh, Kyeong-Sik Min

This paper proposes a high-gain slotted waveguide array antenna design for Ku-band wave-monitoring radar systems. The antenna structure features a two-layer design that integrates the feeding and radiating sections. A grid cavity is stationed on top of the radiating section to suppress the first sidelobes and increase antenna gain. Subsequently, the antenna combined with the grid cavity is designed and fabricated, and its performance is analyzed. The measurement results show a frequency bandwidth of more than 2.8% based on the −10 dB reflection coefficients. The implementation of the grid cavity improves the first sidelobe level by approximately 2 dB. The measurement results also indicate that the proposed antenna achieves a gain of approximately 30.5 dBi—an improvement of approximately 2 dB over that of a conventional slotted waveguide array antenna without a grid cavity. Based on these results, the proposed antenna can be expected to significantly contribute to the development of Ku-band wave-monitoring radar systems for coastal erosion prevention.

Ruoqing Yin, Liz Varga

As renewable energy penetration and extreme weather events increase, accurately predicting power system behavior is essential for reducing risks and enabling timely interventions. This study presents a physics-informed learning approach to forecast transient voltage angles in power systems with integrated wind energy under gusty wind conditions. We developed a simulation framework that generates wind power profiles with significant gust-induced variations over a one-minute period. We evaluated the effectiveness of physics-informed neural networks (PINNs) by integrating them with LSTM (long short-term memory) and GRU (gated recurrent unit) architectures and compared their performance to standard LSTM and GRU models trained using only mean squared error (MSE) loss. The models were tested under three wind energy penetration scenarios—20%, 40%, and 60%. Results show that the predictive accuracy of PINN-based models improves as wind penetration increases, and the best-performing model varies depending on the penetration level. Overall, this study highlights the value of physics-informed learning for dynamic prediction under extreme weather conditions and provides practical guidance for selecting appropriate models based on renewable energy integration levels.

X. Gu, Xiao-bin Guo, Wenhua Li et al.

High-entropy materials (HEMs) have recently emerged as a prominent research focus in materials science, gaining considerable attention because of their complex composition and exceptional properties. These materials typically comprise five or more elements mixed approximately in equal atomic ratios. The resultant high-entropy effects, lattice distortions, slow diffusion, and cocktail effects contribute to their unique physical, chemical, and optical properties. This study reviews the electrical, magnetic, and optical properties of HEMs and explores their potential applications. Additionally, it discusses the theoretical calculation methods and preparation techniques for HEMs, thereby offering insights and prospects for their future development.

D. Tiruneh, Mieke De Cock, Ataklti G. Weldeslassie et al.

Although the development of critical thinking (CT) is a major goal of science education, adequate emphasis has not been given to the measurement of CT skills in specific science domains such as physics. Recognizing that adequately assessing CT implies the assessment of both domain-specific and domain-general CT skills, this study reports on the development and validation of a test designed to measure students’ acquisition of CT skills in electricity and magnetism (CTEM). The CTEM items were designed to mirror the structural components of items identified in an existing standardized domain-general CT test, and targeted content from an introductory Electricity and Magnetism (E&M) course. A preliminary version of the CTEM test was initially piloted on three groups of samples: interviews with physics experts (N = 3), student cognitive interviews (N = 6), and small-scale paper and pencil administration (N = 19). Modifications were made afterwards and the test was administered to a different group of second-year students whose major was mechanical engineering (N = 45). The results showed that the internal consistency (Cronbach’s α = .72) and inter-rater reliability (Cohen’s kappa = .83) of the CTEM test are acceptable. The findings overall suggest that the CTEM test can be used to measure the acquisition of domain-specific CT skills in E&M, and a good basis for future empirical research that focuses on the integration of CT skills within specific subject matter instruction. A broader CT assessment framework is proposed and possible research questions that can be addressed through the CTEM test are discussed.

Pouya Janghorban, Temilade Sesan, Muhammad-Kabir Salihu et al.

Rural electrification initiatives worldwide frequently encounter financial planning challenges due to a lack of reliable market insights. This research delves into the preferences and marginal willingness to pay (mWTP) for upfront electricity connections in rural and peri-urban areas of Nigeria. We investigate discrete choice experiment data gathered from 3,599 households and 1,122 Small to Medium-sized Enterprises (SMEs) across three geopolitical zones of Nigeria, collected during the 2021 PeopleSuN project survey phase. Employing conditional logit modeling, we analyze this data to explore preferences and marginal willingness to pay for electricity connection. Our findings show that households prioritize nighttime electricity access, while SMEs place a higher value on daytime electricity. When comparing improvements in electricity capacity to medium or high-capacity, SMEs exhibit a sharp increase in willingness to pay for high-capacity, while households value the two options more evenly. Preferences for the electricity source vary among SMEs, but households display a reluctance towards diesel generators and a preference for the grid or solar solutions. Moreover, households with older heads express greater aversion to connection fees, and male-headed households show a stronger preference for nighttime electricity compared to their female-headed counterparts. The outcomes of this study yield pivotal insights to tailor electrification strategies for rural Nigeria, emphasizing the importance of considering the diverse preferences of households and SMEs.

Di ZHU, Fulai WANG, Chen PANG et al.

Distinguishing between ships and corner reflectors is challenging in radar observations of the sea. Traditional identification methods, including high resolution range profiles, polarization decomposition, and polarization modulation, improve radial range resolution to the target by transmitting signals with a large bandwidth. The latter two methods use polarization to improve target identification. Single-carrier pulse signals, often used in civil marine radars owing to their low hardware cost, pose challenges in identifying ships and corner reflectors owing to their low range resolution and pulse compression gain. This article proposes a novel method for identifying ships and corner reflectors using polarization modulation in civil marine radars. This approach aims to fully exploit the target identification potential of the narrowband signal joint polarization modulation technology. Through constructing the polarization-range 2D images, the method differentiates between ships and corner reflectors through their unique polarization scattering characteristics. The process involves calculating the average Pearson correlation coefficient between each polarization image and the range image, which serves as the correlation feature parameter. A support vector machine is then employed to achieve accurate target identification. Electromagnetic simulations show that by increasing the device bandwidth to 2～6 times the original signal bandwidth (2 MHz), civil marine radar can achieve a comprehensive identification rate of 90.18%～92.31% at a Signal to Noise Ratio (SNR) of 15 dB and a sampling rate of 100 MHz. The study also explores the influence of missing 50% of pitch angle and azimuth angle data in the training set, finding that identification rates in all four cases exceed 85% when the SNR is above 15 dB. Comparisons with the polarization decomposition method under the same narrowband observation conditions show that when the SNR is 15 dB or higher and the device bandwidth is increased sixfold, the average identification rate of the proposed method improves by 22.67%. This strongly supports the effectiveness of the proposed method. In addition, two cases with different polarization scattering characteristics are constructed in the anechoic chamber using dihedral and trihedral setups. Five sets of measured data show that when the SNR of the echo is 8～12 dB, the experiments demonstrate strong intra-class aggregation and clear inter-class separability. These results effectively support the electromagnetic simulation findings.

Fuping Zeng, Xiaoxuan Feng, Xiaoyue Chen et al.

Abstract Trace hydrogen sulphide (H2S) could reflect the severity of insulation faults in gas‐insulated switchgear (GIS), therefore, accurate and fast detection of low‐concentration H2S is important for on‐line monitoring, fault diagnosis, and state evaluation in GIS. Ag‐Ti3C2Tx chemiresistive‐type sensors were fabricated via drop‐coating with self‐reduction synthesised Ag‐doped Ti3C2Tx. The as‐prepared sensors exhibited an excellent sensitivity and selectivity to H2S with an extremely low detection of limit of 18.57 parts per billion (ppb) at 25°C (room temperature). The response of Ag‐Ti3C2Tx sensor to 10 parts per million (ppm) H2S was enhanced ∼12 times than that of the pristine Ti3C2Tx sensor. The compositing of Ti3C2Tx with Ag nanoparticles (NPs) enabled the fast response/recovery time for H2S detection. Further analysis found that the enhanced H2S sensing performances could be attributed to chemical sensitisation, adsorbed oxygen species regulation and high Brunauer–Emmett–Teller (BET) surface area. This study paves the way for Ag‐Ti3C2Tx as room‐temperature sensing materials to detect low‐concentration H2S in GIS.

Sara J. Ríos, Elio Sánchez G., Andrés Intriago et al.

This paper presents the design of a predictive controller for a boost converter and validation through real-time simulation. First, the boost converter was mathematically modeled, and then the electronic components were designed to meet the operation requirements. Subsequently, a model-based predictive controller (MBPC) and a digital PI (Proportional–Integral) controller were designed, and their performance was compared using MATLAB/SIMULINK^®. The controls were further verified by implementing test benches based on an FPGA (Field-Programmable Gate Array) with an OPAL-RT real-time simulator, which included the RT-LAB and RT-eFPGAsim simulation packages. These tests were successfully carried out, and the methodology used for this design was validated. The results showed a better response obtained with MBPC, both in terms of stabilization time and lower overvoltage.

L. Brigandat, M. Laux, C. Marteau et al.

<p>We assigned the side-chain resonances of the Crimean–Congo hemorrhagic fever virus (CCHFV) glycoprotein n (Gn) cytosolic domain that is 69 amino acids long to complete the backbone resonances previously published by Estrada et al. (2011). The process was facilitated by three factors. First, sample preparation using cell-free protein synthesis (CFPS) was completed in less than 2 d and allowed for correct zinc finger formation by adding zinc ions to the reaction. Second, access to NMR platforms with standardized pulse sequences allowed for data acquisition in 18 d. Third, data analysis using the online platform NMRtist allowed sequential resonance assignments to be made in a day, and assignments were verified and finalized in less than a week. Our work thus provides an example of how NMR assignments, including side chains, of small and well-behaved proteins can be approached in a rapid routine, at protein concentrations of 150 <span class="inline-formula">µ</span>M.</p>

A. Mason, Jessica M. McCardell, P. White et al.

Gary White, Tiffany-Rose Sikorski, J. Landay et al.

Esmeralda Campos, Eder Hernandez, Pablo Barniol et al.

Due to the similarities between Gauss’s and Ampere’s laws, students can present cognitive interference when learning these laws in the introductory physics course. This study aims to analyze the interference patterns that emerge in students’ answers when solving problems that involve Gauss’s and Ampere’s laws and related concepts (e.g., electric flux and magnetic circulation). We conducted a study of 322 engineering students attending a private Mexican university. We applied two open-ended questionnaires with questions that prompted using Gauss’s and Ampere’s laws. We analyzed students’ answers to identify whether they presented some word or element of an equation from the opposite context and coded them into coding families. We analyzed the consistency of interference by counting the times each student presented some interference in general and by coding family. The results indicated that the interferences related to the shape of the Gaussian surface or Amperian trajectory and field-related concepts are shared among contexts. However, the interference related to the source of the field (charge or current) is predominant in magnetism. In contrast, the interference related to using elements from the opposite context in an equation predominates in electricity. In other words, students referred to currents as charges and wrote equations that contained B (for magnetic field) or other similar elements in Gauss’s law. The general consistency analysis revealed that around half the students presented at least one interference in both contexts. We recommend that the interference between electricity and magnetism in Gauss’s and Ampere’s laws must not be overlooked. This study’s findings can guide introductory and intermediate electricity and magnetism instructors to address this interference phenomenon.

W. Qian

Zhou Lan, Ben Liu, Yi Feng et al.

Daily electricity consumption forecasting is a classical problem. Existing forecasting algorithms tend to have decreased accuracy on special dates like holidays. This study decomposes the daily electricity consumption series into three components: trend, seasonal, and residual, and constructs a two-stage prediction method using piecewise linear regression as a filter and Dilated Causal CNN as a predictor. The specific steps involve setting breakpoints on the time axis and fitting the piecewise linear regression model with one-hot encoded information such as month, weekday, and holidays. For the challenging prediction of the Spring Festival, distance is introduced as a variable using a third-degree polynomial form in the model. The residual sequence obtained in the previous step is modeled using Dilated Causal CNN, and the final prediction of daily electricity consumption is the sum of the two-stage predictions. Experimental results demonstrate that this method achieves higher accuracy compared to existing approaches.

Zemenu Mihret, Mekbib Alemu, Shimeles Assefa

This study examined the effect of blended laboratory experiments on pre-service physics teachers’(PSPTs’) attitudes toward physics laboratories. The research design was a quasi-experimental pre-test and post-test comparing groups. Participants were 63 2nd-year PSPTs’ enrolled in a physics diploma program from three colleges of teacher education. The treatment groups performed blended and virtual laboratory experiments, whereas the comparison group conducted real laboratory experiments. Data were collected before and after intervention using a 34-item adapted attitude toward physics laboratory questionnaire with a Cronbach alpha value of 0.765. Data were analyzed using descriptive statistics, paired-sample t-test, one-way ANOVA, and Tukey post hoc comparisons. The findings revealed a statistically significant difference in mean post-test results between the treatment and comparison group. The Tukey HSD post hoc analysis revealed that the difference in mean between blended and real was statistically significant, but not on other combinations. Descriptive statistics showed slight attitudinal improvement from pre-test to post-test. This improvement was statistically significant for blended and virtual groups but not in real groups. Blending physics laboratory experiments can be used to enhance attitudes toward physics laboratories. Based on the conclusions, recommendations are made.

Y. Yeh, T. Dhurumraj, U. Ramnarain

A. Maries, M. Brundage, C. Singh

The Conceptual Survey of Electricity and Magnetism (CSEM) is a multiple-choice survey that contains a variety of electricity and magnetism concepts from Coulomb's law to Faraday's law at the level of introductory physics used to help inform instructors of student mastery of those concepts. Prior studies suggest that many concepts on the survey are challenging for introductory physics students and the average student scores after traditional instruction are low. The research presented here investigates the progression in student understanding on the CSEM. We compare the performance of students in introductory and advanced level physics courses to understand the evolution of student understanding of concepts covered in the CSEM after traditional lecture-based instruction. We find that on all CSEM questions on which less than 50% of the introductory physics students answered a question correctly after instruction, less than two thirds of the upper-level undergraduate students provided the correct response after traditional instruction. We also analyzed the CSEM data from graduate students for benchmarking purposes. We discuss the CSEM questions that remain challenging and the common alternative conceptions among upper-level students. The findings presented here at least partly point to the fact that traditional instruction in upper-level courses which typically focuses primarily on quantitative problem solving and incentivizes use of algorithmic approaches is not effective for helping students develop a solid understanding of these concepts. However, it is important for helping students integrate conceptual and quantitative aspects of learning in order to build a robust knowledge structure of basic concepts in electricity and magnetism.