Power Profile Research Articles

Design of a Supercapacitor Module and Control Algorithm for Practical Verification of a Hybrid Energy Storage System

This paper presents an approach to designing a supercapacitor (SC) module according to defined power profiles and providing a control algorithm for sharing the energy from the SC module and accumulator in a hybrid energy storage system (HESS). This paper also presents a view of a printed circuit board (PCB) of the SC module and an interconnection board between the bidirectional converter, accumulator, and SC module. The practical part of the paper presents the measurement of the voltages and currents on the SC module, accumulator, and output of the DC/DC converter to visualize the energy flow between them.

Multifocal Rigid Gas Permeable Contact Lenses with Multi-Tangential Positioning and Corrected Spherical Aberration for Myopia Control

Slowing the progression of myopia has become an extensive concern for parents of children with myopia. According to research findings in animals, eye growth is primarily influenced by the peripheral retina. Treatment options such as orthokeratology, daytime bifocal or multifocal soft contact lens usage are available because they can induce relative myopia in the periphery. In this work, a new multifocal rigid gas permeable (MFRGP) contact lens for myopia prevention and control in adolescents was designed specifically for preventing and controlling myopia in adolescents. This lens features a multi-tangent alignment curve, smaller spherical aberration, and transition defocus. FocalPoints and UPC 100 Vision were used for lens design and lathing, respectively. The lens structure and power profile were measured using IS830 and CONTEST 2, respectively. The elimination of lens aberrations was achieved through design optimization using ZEMAX with ray tracing. Lens fitting was evaluated using slit-lamp microscopy and corneal topography.

CFD Modeling of HBI/SCRAP Melting in Industrial EAF and the Impact of Charge Layering on Melting Performance

The melting of scrap and hot briquetted iron (HBI) in an AC electric arc furnace (EAF) is simulated by an advanced 3D computational fluid dynamics (CFD) model that captures the arc heating, the scrap/HBI melting process, and the solid collapse mechanisms. The CFD model is used to simulate a scenario where charge layering and EAF power profiles are provided by a real EAF operation. CFD simulation of the EAF operation shows proper prediction of the charge melting when compared with standard industry practice. Namely, the CFD model predicts a 32.5%/67.5% ratio of solid/liquid steel at the beginning of refining, which approaches the 30%/70% ratio used in standard practice. Based on this prediction, the melting rate in the CFD results differs by 8.3% from actual EAF operation. The impact of charge layering on melting is also investigated. CFD results show that distributing charge material into a greater number of layers in the first bucket (10 layers as compared to 4) enhances the melting rate by 12%. However, including dense material at the bottom of the furnace deteriorates melting performance, reducing the impact of the number of layers of the charge. The CFD platform can be used to optimize the use of HBI/scrap in real EAF operations and to determine best recipe practices.

Performance and Latency Efficiency Evaluation of Kubernetes Container Network Interfaces for Built-In and Custom Tuned Profiles

In the era of DevOps, developing new toolsets and frameworks that leverage DevOps principles is crucial. This paper demonstrates how Ansible’s powerful automation capabilities can be harnessed to manage the complexity of Kubernetes environments. This paper evaluates efficiency across various CNI (Container Network Interface) plugins by orchestrating performance analysis tools across multiple power profiles. Our performance evaluations across network interfaces with different theoretical bandwidths gave us a comprehensive understanding of CNI performance and overall efficiency, with performance efficiency coming well below expectations. Our research confirms that certain CNIs are better suited for specific use cases, mainly when tuning our environment for smaller or larger network packets and workload types, but also that there are configuration changes we can make to mitigate that. This paper also provides research into how to use performance tuning to optimize the performance and efficiency of our CNI infrastructure, with practical implications for improving the performance of Kubernetes environments in real-world scenarios, particularly in more demanding scenarios such as High-Performance Computing (HPC) and Artificial Intelligence (AI).

Distinguishing Artifactual Fatty Acid Dimers from Fatty Acid Esters of Hydroxy Fatty Acids in Untargeted LC-MS Pipelines.

Untargeted metabolomics is a powerful profiling tool for the discovery of possible biomarkers of disease onset and progression. Analytical pipelines applying liquid chromatography (LC) and mass spectrometry (MS)-based methods are widely used to survey a broad range of metabolites within various metabolic pathways, including organic acids, amino acids, nucleosides, and lipids. Accurate and complete identification of putative metabolites is an ongoing challenge in untargeted metabolomics studies. Highly sensitive instrumentation can result in the detection of adduct and fragment ions that form reproducibly and contain identifiable ions that are difficult to distinguish from metabolic pathway intermediates, which may result in false-positive identification. At concentrations as low as 10μM, free fatty acids have been found to form homo- and heterodimers in untargeted metabolomics pipelines that resemble the lipid class fatty acid esters of hydroxy fatty acids (FAHFAs), resulting in misidentification. This chapter details a protocol for LC-MS-based untargeted metabolomics using hydrophilic interaction chromatography (HILIC) that specifically aids in distinguishing artifactual fatty acid dimers from endogenous FAHFAs.

Power profile and optical performance of two extended range-of-vision intraocular lens designs.

To assess the power profile and optical performance of 2 extended range-of-vision (ERV) intraocular lenses (IOLs), TECNIS Eyhance (ICB00) and LuxSmart, and compare them with their monofocal counterpart lenses with similar platforms and materials: TECNIS 1-piece (ZCB00) and LuxGood, respectively. Optics and Optometry Faculties of Complutense University (Madrid) and Universitat Politècnica de Catalunya BarcelonaTech (Terrassa) in Spain. Laboratory investigation on optical bench. For each design, the power distribution and (fourth and sixth-order) spherical aberration (SA) across the lens aperture were measured as well as the optical performance using modulation transfer function-based metrics with through-focus evaluation. 3 nominal powers (+10.00 diopters [D], +20.00 D, and +30.00 D) and 3 pupil sizes (2.0 mm, 3.0 mm, and 4.5 mm) were considered to assess whether the base power of the lens and pupillary dynamics have an influence on the depth-of-focus extension. TECNIS Eyhance and LuxSmart IOLs had different power and SA profiles, but both designs shared a positive add power in their central region in comparison with their monofocal counterparts. LuxSmart had a greater add power while TECNIS Eyhance showed higher peak optical quality but smaller depth of focus. Differences of focus extension between the 2 ERV IOL designs are related to differences of power and SA profile. The nominal base power of the IOLs has little effect on their optical quality. However, pupil dynamics plays a key role since it determines the effective add power and optical performance of the ERV IOLs.

Coupled heat transfer and chemical kinetics in a calcium oxide/hydroxide fixed bed thermochemical energy storage reactor

Among energy storage technologies, thermochemical heat storage despite its unique advantages, remains at a nascent state due to varied technical challenges. One of the key unknowns in the otherwise well-studied calcium oxide/hydroxide chemistry, is a lack of understanding of the possible output power profiles. Here, we investigate the theoretical power output from a fixed-bed, modular, honeycomb-geometry thermochemical energy storage (TCS) reactor based on a calcium oxide/hydroxide, using finite element modeling of heat transfer coupled with reaction kinetics. We calculate the extent of reaction and temperature profiles in a lattice of honeycomb cells that make up the bed, while varying heat transfer related parameters. We find that the size of the unit cell can limit energy discharge, for example, increasing the time to completion for the reaction to ∼7 hours as the cell size increases to 6 cm, even though the reaction kinetics is fast at ∼2 mins. The time constant of the transient power profile increases by a factor of ∼4 as the cell size increases by a factor of ∼3, when considering cells in the nominal size range 2–6 cm. Besides cell size, we investigate how the power profile is affected by the following parameters: the thermal conductivity of the bed, the initial temperature, the material of the cell wall and the heat transfer coefficient of external flows. In particular, we identify the combination of parameters that can vary the power profile on demand to operate the same reactor as either a thermal capacitor or alternately, a thermal battery. This work informs future design possibilities with oxide-hydroxide, solid–gas reaction TCS and provides insight into critical heat transfer parameters.

Optical Activities of Organic Crystals: Crystal Orbital Formulation of Anisotropic Gyration.

To describe the optical activities of crystals, gyration tensors are necessary for all wavelengths of incident light. To date, few studies on direct calculations of gyration tensors from Bloch states have been conducted. Herein, a practical procedure to obtain gyration tensors of organic crystals is presented using the crystal orbital method. The extended Hückel method was adopted to evaluate the gyration tensors, epitomizing the one-electron formulation. To confirm the validity of the formulation, the optical rotatory power of alanine and γ-glycine was examined. The reproduced profiles of the optical rotatory power were consistent with the results of recent experiments. This is a general formulation of the one-electron theory of optical activities for three-dimensional crystals. In principle, the optical rotatory strength tensor is not invariant with translation. For systems with small unit cells, however, the formalism is quasi-invariant with respect to translation. The quasi origin-independent formalism is sufficiently substantial to be applicable to modern crystal optics.

Enhancing C+L-band transmission performance through OSNR flatting and link damage recovery algorithms

The rapid growth of data-intensive services has driven the need for high-capacity optical networks. C+L band optical communication systems have emerged as a potential solution by extending the operational bandwidth. However, the wider spectrum introduces significant stimulated Raman scattering (SRS) effects that impact signal power profile, Kerr nonlinearity, and amplified spontaneous emission (ASE) noise. To address these challenges, this paper proposes an optical power control strategy designed to achieve a flat optical signal-to-noise ratio (OSNR) across all transmitted channels, which is particularly effective in mitigating SRS effects in C+L band systems. Furthermore, a link damage recovery algorithm is developed to ensure system robustness against localized fiber degradations. Extensive simulations are conducted to compare the performance of the proposed strategy with the conventional flat launch power approach under single-span and multi-span transmission scenarios. The results demonstrate that the proposed strategy achieves a higher minimum generalized signal-to-noise ratio (GSNR), exhibits stronger resilience to link damage across a wide range of transmission conditions.

Incorporation of uranium nitride fuel capability into the ENIGMA fuel performance code: Model development and validation

Uranium dioxide (UO2) is the primary fuel form for nuclear reactors but its moderate uranium density and low thermal conductivity have prompted the exploration of alternative materials. Uranium nitride (UN) has emerged as a promising candidate for a variety of reactors, offering higher uranium density and thermal conductivity. This paper details the development and implementation of UN fuel capabilities within the ENIGMA fuel performance code for Light Water Reactor (LWR) applications. The new UN capability in ENIGMA includes correlations for theoretical density at room temperature, thermal conductivity, specific heat capacity, enthalpy, thermal expansion strain, Young’s modulus, Poisson’s ratio, thermal creep strain rate, irradiation creep strain rate and emissivity. Additionally, it incorporates models for densification, solid fission product swelling, fission gas bubble swelling, and fission gas release, along with a modified RADAR model for determining the pellet radial power profile and helium generation. Validation of the UN model was conducted using data from the L414 pin irradiation in the JOYO fast reactor in Japan. Further validation efforts are planned using datasets from JOYO and the Siloé thermal reactor in France. The paper also outlines areas of future work to address experimental data gaps and enhance model accuracy to cover a broader range of cladding materials, manufacturing parameters (including porosity volume fraction) and operating conditions (including fuel temperatures and burnups). Although focused on LWR applications, the work outlined supports the use of UN fuel across various reactor systems.

One-pot synthesis of FeNi3/FeNiOx nanoparticles for PGM-free anion exchange membrane water electrolysis

Low-temperature anion exchange membrane water electrolysis (AEMWE) is one of the most promising technologies to produce green hydrogen. To date, membrane-electrode assembly (MEA) based on platinum group metal (PGM) electrocatalysts shows higher performance than PGM-free ones. Here, a single and easy synthesis for non-noble metal electrocatalysts (PGM-free) for both hydrogen and oxygen evolution reactions (HER and OER) was developed. Both electrocatalysts consist of FeNi3/FeNiOx nanoparticles obtained through chemical reduction using hydrazine. The electrocatalyst exhibits an overpotential of 210 mV and 234 mV for HER and OER respectively, at a current density of 10 mA cm−2 in 1 M KOH electrolyte, allowing a comparison between mass activity and geometric activity compared to PGM catalysts. In addition to a preliminary electrochemical characterization of the FeNi3/FeNiOx, the electrocatalyst were integrated into a pilot-scale AEMWE at both anode and cathode, which reaches (without iR-correction) 1.72 V and 1.94 V at a current density of 0.4 A cm−2 and 1 A cm−2 respectively at 60 °C. This PGM-free MEA outperforms the one based on Pt/C at cathode and RuO2 at anode with a voltage gap of 284 mV at 1 A cm−2. The aforementioned MEA was tested for 150 h with a discontinuous power profile, in order to get an idea of the possible degradation trends for a future industrial application, the reversible and irreversible voltage losses were calculated resulting in a degradation rate of 886 µV/h. This work demonstrates a simple and scalable synthesis of earth-abundant electrocatalytic materials for high-efficiency AEM water electrolysis.

Fault-Tolerant Decentralized Control for Large-Scale Inverter-Based Resources for Active Power Tracking

Abstract Integration of Inverter Based Resources (IBRs) which lack the intrinsic characteristics such as the inertial response of the traditional synchronous generator (SG) based sources presents a new challenge in the form of analyzing the grid stability under their presence. While the dynamic composition of IBRs differs from that of the SGs, the control objective remains similar in terms of tracking the desired active power. This letter presents a decentralized primal-dual-based fault-tolerant control framework for the power allocation in IBRs. Overall, a hierarchical control algorithm is developed with a lower level addressing the current control and the parameter estimation for the IBRs and the higher level acting as the reference power generator to the low level based on the desired active power profile. The decentralized network-based algorithm adaptively splits the desired power between the IBRs taking into consideration the health of the IBRs transmission lines. The proposed framework is tested through a simulation on the network of IBRs and the high-level controller performance is compared against the existing framework in the literature. The proposed algorithm shows significant performance improvement in the magnitude of power deviation and settling time to the nominal value under faulty conditions as compared to the algorithm in the literature. Better active power tracking performance compared to the existing method in literature.

Lens Power and Associated Factors in Nonhuman Primate Subjects: A Cross-sectional Study.

We aimed to examine the normative profile of crystalline lens power (LP) and its associations with ocular biometric parameters including age, axial length (AL), spherical equivalent refraction (SE), corneal radius (CR), lens thickness, anterior chamber depth, and AL/CR ratio among a cynomolgus monkey colony. This population-based cross-sectional Non-human Primate Eye Study recruited middle-aged subjects in South China. All included macaques underwent a detailed ophthalmic examination. LP was calculated using the modified Bennett's formula, with biometry data from an autorefractometer and A-scan. SPSS version 25.0 was used for statistical analysis. A total of 301 macaques with an average age of 18.75 ± 2.95years were collected in this study. The mean LP was 25.40 ± 2.96 D. Greater LP was independently associated with younger age, longer AL, and lower SE (P = 0.028, P = 0.025, and P = 0.034, respectively). LP showed a positive correlation with age, SE, CR, AL, lens thickness, and anterior chamber depth, whereas no correlation was observed between LP and AL/CR ratio. Our results suggested the LP distribution in the nonhuman primate colony and indicated that AL and SE strongly influenced the rate of LP. Therefore, this study contributed to a deeper understanding of the relative significance of the LP on the optics of the crystalline lens study.

Refractive power profiles of commercially available soft multifocal contact lenses for myopia control.

Lens power profiles can provide valuable insights on the imposed optical defocus and visual experience of contact lens wearers, especially in the context of myopia control. This study measured the refractive power profiles of multifocal soft contact lenses (MFCLs) currently used or that have the potential for use in myopia control using high spatial resolution aberrometry. The instrument's repeatability for determining MFCLs power profiles was also assessed. The power profiles of 10 MFCLs of various designs (centre-distance, centre-near and extended depth of focus) were measured using the Lambda-X NIMOEVO, a phase shifting Schlieren-based device. Power profiles were graphically expressed as measured power at each chord position and the maximum add power was calculated. The repeatability of the NIMOEVO was expressed as the within-subject standard deviation at each chord position for a subset of five MFCLs. The measured distance powers differed from nominal powers for more than half of the MFCLs with a definable distance zone. There were variations in the chord position of the distance and near correction zones, rate of power transitions and calculated maximum add between the MFCLs which did not depend on lens design. For half of the MFCLs, the power profile shape was inconsistent between different nominal back vertex powers of the same design. The repeatability of the NIMOEVO was dependent on the lens design, with designs featuring faster rates of power change exhibiting worse repeatability. Significant differences in MFCL power profiles were found which were not adequately represented in labelling. This is likely due to the small number of parameters used to define lens power characteristics. Eye health care practitioners should be aware of potential differences in power profiles between different MFCLs, which will impact the retinal defocus introduced during lens wear and the wearer's visual experience.

Surrogate-Based Multidisciplinary Optimization for the Takeoff Trajectory Design of Electric Drones

Electric vertical takeoff and landing (eVTOL) aircraft attract attention due to their unique characteristics of reduced noise, moderate pollutant emission, and lowered operating cost. However, the benefits of electric vehicles, including eVTOL aircraft, are critically challenged by the energy density of batteries, which prohibit long-distance tasks and broader applications. Since the takeoff process of eVTOL aircraft demands excessive energy and couples multiple subsystems (such as aerodynamics and propulsion), multidisciplinary analysis and optimization (MDAO) become essential. Conventional MDAO, however, iteratively evaluates high-fidelity simulation models, making the whole process computationally intensive. Surrogates, in lieu of simulation models, empower efficient MDAO with the premise of sufficient accuracy, but naive surrogate modeling could result in an enormous training cost. Thus, this work develops a twin-generator generative adversarial network (twinGAN) model to intelligently parameterize takeoff power and wing angle profiles of an eVTOL aircraft. The twinGAN-enabled surrogate-based takeoff trajectory design framework was demonstrated on the Airbus A3 Vahana aircraft. The twinGAN provisioned two-fold dimensionality reductions. First, twinGAN generated only realistic trajectory profiles of power and wing angle, which implicitly reduced the design space. Second, twinGAN with three variables represented the takeoff trajectory profiles originally parameterized using 40 B-spline control points, which explicitly reduced the design space while maintaining sufficient variability, as verified by fitting optimization. Moreover, surrogate modeling with respect to the three twinGAN variables, total takeoff time, mass, and power efficiency, reached around 99% accuracy for all the quantities of interest (such as vertical displacement). Surrogate-based, derivative-free optimizations obtained over 95% accuracy and reduced the required computational time by around 26 times compared with simulation-based, gradient-based optimization. Thus, the novelty of this work lies in the fact that the twinGAN model intelligently parameterized trajectory designs, which achieved implicit and explicit dimensionality reductions. Additionally, twinGAN-enabled surrogate modeling enabled the efficient takeoff trajectory design with high accuracy and computational cost reduction.

A Novel Approach to Energy Management with Power Quality Enhancement in Hydrogen Based Microgrids through Numerical Simulation

A hydrogen-based microgrid (MG) is an energy system that uses hydrogen as a primary energy carrier within a localized grid. Numerous alternative approaches and concepts are found concerning the management of renewable energy systems. This study proposes a novel approach to assess the energy management system (EMS) and optimal hydrogen-based Energy Storage Systems (HBESS) at minimal total cost, employing particle swarm optimization (PSO) and fuzzy control in stand-alone microgrids. Together, these methods effectively address control and management challenges within hybrid microgrids (HMGs). This has been proposed to enhance energy management and to improve power quality. The findings reveal that PSO is the most advantageous and efficient approach. Its utilization proves instrumental in reducing costs, boosting reliability, and optimizing operational schedules within HMGs. Furthermore, the power profile holds considerable importance in this study, significantly enhancing system reliability and stability. This study has achieved an impressive 6.147% improvement in cost-effectiveness compared to traditional methods. This has been put into practice and validated through implementation within a MATLAB (9.13.0 (R2022b))/Simulink framework.

Linear stability analysis of a combustor model with a delayed feedback tube

We conducted a linear stability analysis of a laboratory-scale combustor to develop a delayed feedback method for mitigating combustion oscillations. We employed linearized hydrodynamic equations and a flame transfer function in the frequency domain to assess the stability under various feedback tube configurations, including changes in the length, radius, and connection position. The results of the stability analysis demonstrated a significant improvement in stability when the length of the feedback tube was 0.56 times the wavelength of the unstable mode. Furthermore, the tube radius had an optimal value for stabilizing the system. The connection position also played a crucial role in stability. The effective feedback tube conditions determined in the analysis were applied to a real combustor to demonstrate the successful suppression of oscillations experimentally. The suppression mechanism is discussed using the acoustic power based on the calculation results. The acoustic power profile of the system revealed that the oscillation suppression was not simply an addition of acoustic dissipation, but importantly, a reduction in acoustic power generation at the flame.

Optimization of IPOP-connected dissimilar power-rated converters: An equal incremental cost-based approach

As electric vehicles gain prominence, optimizing the efficiency of charging stations has become a critical issue. This paper explores the application of dual active bridge (DAB) converters arranged in an input-parallel-output-parallel (IPOP) configuration, offering a flexible solution for power conversion across varied power-rated loads. While previous research mainly focused on optimizing single DABs and establishing the system using identical converters, this study leverages dissimilar modules, enhancing flexibility and operational efficiency. We introduce a novel IPOP system incorporating diverse modules and corresponding switch regulators. Additionally, an efficiency optimization strategy featuring dynamic load allocation is proposed. Herein, each module or each group of modules is responsible for its corresponding power range. Based on curve-fitted power profiles, an equal incremental cost-based method is employed to formulate the path of power allocation. Moreover, a simulated annealing algorithm determines the optimal power output strategy to accommodate dynamic power flow requirements. Experimental comparisons with the conventional equal-power sharing scheme underscore the proposed method’s effectiveness and superiority.

Electric vehicle supply equipment monitoring and early fault detection through autoencoders

This paper presents a novel approach to detecting anomalies in Electric Vehicle charging unit power profiles using a combination of Autoencoders with LSTM techniques. This study presents a robust methodology, combining the two Machine Learning techniques, for early fault estimation in a real-world case study. The proposed methodology offers significant advantages over existing methods by providing a more comprehensive analysis of anomalous trends. To validate the effectiveness of the proposed methodology, the authors tested it on real Electric Vehicles charging power curves provided by an Italian Distribution System Operator recorded on a historical database and compared the performances with the ones of a traditional anomaly detection technique. The results of the study, tested on Electric Vehicles Supply Equipment or charging stations, demonstrate that the proposed approach is highly effective in detecting anomalous trends in Electric Vehicles charging profiles.

Biomechanical Characterization of the CrossFit® Isabel Workout: A Cross-Sectional Study

A cross-sectional study was conducted to biomechanically characterize Isabel’s workout (30 snatch repetitions with 61 kg fixed weight), focusing on eventual changes in knee, hip and shoulder angles. A three-dimensional markerless motion capture system was used to collect data from 11 highly trained male crossfitters along the Isabel workout performed at maximal effort. The routine was analyzed globally and in initial, middle and final phases (10, 20 and 30 repetitions, respectively). Lift total time increased (1.51 ± 0.18 vs. 1.97 ± 0.20 s) and maximal lift velocity (2.64 ± 0.12 vs. 2.32 ± 0.13 m/s) and maximal lift power (15.58 ± 2.34 vs. 13.80 ± 2.49 W/kg) decreased from the initial to final phases, while the time from lift until the bar crossed the hip and shoulder (34.20 ± 4.00 vs. 27.50 ± 5.10 and 39.70 ± 16.80 vs. 30.90 ± 13.90%) decreased along the Isabel workout. In addition, a decrease in hip flexion was observed during the last two phases when the bar crosses the knee (62.62 ± 24.80 vs. 53.60 ± 19.99°). Data evidence a decrease in the power profile and a change in hip flexion throughout the Isabel workout, without compromising the other joints.