Local Energy Distribution Research Articles

Bearing capacity analysis of RC slabs under cyclic loads: Dual numerical approaches

Shakedown analysis is a powerful and efficient tool for calculating the safety factors of structures under variable and repeated external quasi-static loads, that can prevent structures from incremental and alternative plasticity collapses. RC slabs in practical engineering applications are usually under long-tern variable and cyclic loads, but their fatigue behavior was rarely reported in the literature, particularly for those governed by the Nielsen yield condition. In this paper, dual static and kinematic shakedown formulations based on displacement-finite elements and conic programming are developed. The resulting optimization problems, characterized by a huge number of variables, are effectively solved. A wide range of practical RC slabs with diverse geometries, loading and boundary conditions are investigated, precisely capturing the collapse modes in terms localized plastic dissipation energy and presenting moment distribution at fatigue state. Strengthening strategies are performed in regions with localized plastic dissipation energy, showing that the load-bearing capacity of such slabs increases significantly while incremental and alternative collapse modes are prevented.

An intelligent model for efficient load forecasting and sustainable energy management in sustainable microgrids

Microgrids have emerged as a promising solution for enhancing energy sustainability and resilience in localized energy distribution systems. Efficient energy management and accurate load forecasting are one of the critical aspects for improving the operation of microgrids. Various approaches for energy prediction and load forecasting using statistical models are discussed in the literature. In this work, a novel energy management framework that incorporates machine learning (ML) techniques is presented for an accurate prediction of solar and wind energy generation. The anticipated approach also emphasizes time series-based load forecasting in microgrids with precise estimation of State of Charge (SoC) of battery. A unique feature of the proposed framework is that utilizes historical load data and employs time series analysis coupled with different ML models to forecast the load demand in a commercial microgrids scenario. In this work, Long Short-Term Memory (LSTM) and Linear Regression (LR) models are employed for an experimental analysis to study the proposed framework under three different cases, such as (i) prediction of energy generation, (ii) load demand forecasting and, (iii) prediction of SoC of battery. The results show that the Random Forest (RF) and LSTM models performs well for energy prediction and load forecasting respectively. On the other hand, the Artificial Neural Network (ANN) model exhibited superior accuracy in terms of SoC estimation. Further, in this work, a Graphical User Interface (GUI) is developed for evaluating the efficacy of the proposed energy management framework.

Robust detection of ductile fracture by acoustic emission data-driven unsupervised learning

The quantitative assessment of the formability of bulk metallic materials remains challenging, primarily due to considerable difficulties in accurately identifying the initiation of fractures. This study introduces a novel methodology for detecting the onset of ductile fracture by using acoustic emission signals. Unlike traditional methods that rely on standard characteristics, this approach utilizes acoustic emission signals that are depicted through vivid and direct feature images. These images represent short-term and relative energies, which are termed as energy allocation maps. These maps are generated utilizing a novel signal processing technique that employs the maximal overlap discrete wavelet transform for multi-resolution analysis. In this study, a parameter known as accumulative relative energy is developed to illustrate the global energy distribution across resolutions, while another parameter, normalized short-term energy, is designed to capture the local energy distribution of resolutions. The natural neighbor interpolation technique is subsequently employed to derive the energy allocation map. A set of stacked autoencoders is accordingly configured to transform this map into a singular value that represents the condition of the material. Consequently, a ductile fracture indicator is proposed to identify the onset of fracture. The accuracy and efficacy of the proposed method are validated through partial experiments. The study examines four bulk metallic materials, providing insights into their deformation capabilities under compression.

Mid-Deep Circulation in the Western South China Sea and the Impacts of the Central Depression Belt and Complex Topography

As a key component of meridional overturning circulation, mid-deep circulation plays a crucial role in the vertical and meridional distribution of heat. However, due to a lack of observation data, current knowledge of the dynamics of mid-deep circulation currents moving through basin boundaries and complicated seabed topographies is severely limited. In this study, we combined oceanic observation data, bathymetric data, and numerical modeling of the northwest continental margin of the South China Sea to investigate (i) the main features of mid-deep circulation currents traveling through the central depression belt and (ii) how atmospheric-forcing (winds) mesoscale oceanic processes such as eddies and current–topography interactions modulate the mid-deep circulation patterns. Comprehensive results suggest that the convergence of different water masses and current–topography interactions take primary responsibility for the generation of instability and enhanced mixing within the central depression belt. By contrast, winds and mesoscale eddies have limited influence on the development of local circulation patterns at mid-deep depths (>400 m). This study emphasizes that the intensification and bifurcation of mid-deep circulation; specifically, those induced by a large depression belt morphology determine the local material cycle (temperature, salinity, etc.) and energy distribution. These findings provide insights for a better understanding of mid-deep circulation structures on the western boundary of ocean basins such as the South China Sea.

Monitoring Energy and Power Quality of the Loads in a Microgrid Laboratory Using Smart Meters

Microgrids are local energy production and distribution networks that can operate independently when disconnected from the main power grid thanks to the integration of power generation systems, energy storage units and intelligent control systems. However, despite their advantages, the optimal energy management of real microgrids remains a subject that requires further investigation. Specifically, an effective management of microgrids requires managing a large number of electrical variables related to the power generated by the microgrid’s power supplies, the power consumed by the loads and the aspects of power quality. This study analyzes how we can monitor different variables, such as the active power, reactive power, power factor, total harmonic distortion and frequency in the loads of a microgrid, using high-precision power meters. Our empirical study, conducted using a functional microgrid comprising a hybrid wind–solar power system and several household appliances, demonstrates the feasibility of using low-cost and high-performance power meters with IoT functionality to collect valuable power quality and energy consumption data that can be used to control the microgrid operation.

Process comparison of laser deep penetration welding in pure nickel using blue and infrared wavelengths

AbstractLaser sources with wavelengths in the visible blue spectrum are suitable for heat conduction mode welding of materials like copper and nickel due to the significantly increased Fresnel absorption compared to infrared laser radiation. Recently, blue laser sources with 445 nm wavelength have become available with sufficient power and beam parameters to exceed the intensity threshold for laser deep penetration welding. In laser beam deep penetration welding, the total absorption is significantly increased due to the multiple reflections in the keyhole compared to heat conduction mode welding. However, since the absorbed energy per reflection inside the keyhole is wavelength-dependent, it can be hypothesized that the choice of laser wavelength causes changes in the local energy distribution inside the keyhole, changing the keyhole dynamics. To investigate this, laser beam deep penetration welding experiments were carried out on 2.4068 pure nickel using an infrared laser source and a blue laser source with comparable beam properties. The experiments were monitored and compared by a multi-sensor setup and metallographic analyses. This setup included measurements of airborne acoustic emissions and two high-speed video cameras for spatter tracking and tracking of the keyhole area. The use of a blue laser beam led to a lower spatter quantity, an increase of porosity and a significant change of acoustic emissions, proving the hypothesis for pure nickel.

Elastocaloric effect with plateau-shape adiabatic temperature change in Ni–Co–Fe–Ga strain glass alloy

Elastocaloric effect (eCE) is a very promising candidate for using in non-vapor compression refrigeration, which is highly efficient and eco-friendly. However, designing elastocaloric alloys with a wide reversible working temperature window at low stress is still challenging. In this work, the transition behaviors, microstructural evolutions and the eCE of a series of Ni55−x Co x Fe19Ga27 alloys were systematically studied. The Ni44Co11Fe19Ga27 strain glass (STG) alloy exhibits a plateau-shape eCE, which show an average temperature change (ΔT Adia) of ∼2.3 K covering a wide reversible working temperature range (ΔT rev) from 135 K to 200 K. The unique eCE behavior of STG stems from that the random distribution of local free energy of the martensite coupled with the small transition energy barriers, which leads to a wide transition-temperature range and decreased hysteresis. The Ni44Co11Fe19Ga27 STG alloy achieves a balance between the considerable ΔT Adia and wide ΔT rev, resulting in an optimal comprehensive elastocaloric performance and contributing to improving the efficiency of elastocaloric refrigeration.

Investigation on the vibration localization of mistuned bladed disk with frictional contact

The mistuning phenomenon is commonly seen in the bladed assemblies of turbomachinery, leading to an unreasonably localized energy distribution that may increase the risk of high cycle fatigue and potentially cause blade failure. The friction coupling interaction is often introduced to attenuate the effect of excessive amplification on the structural vibration. To investigate the vibration localization of damped and mistuned bladed-disk system, a typical mistuning characterization is applied to an improved four-degree-of-freedom lumped parameter model to explicit the vibratory properties with coupled frictional contact. The statistical findings of natural frequency and modal localization factor are obtained by employing the Monte Carlo simulation to explore the influence of mistuned variance and coupled stiffness on the modal localization of free and damped bladed-disk system, respectively. The forced response sensitivity featured in the mistuned variance is quantitatively analyzed from the perspective of vibration localization and energy distribution by the nonlinear solution method. The influence of excitation order and normal load are further, respectively, discussed on the response localization level of the mistuned system. The results can provide fundamental knowledge of the impact of the mistuning pattern on vibration localization for the early design of the aeroengine.

A Review on Energy Management of Community Microgrid with the use of Adaptable Renewable Energy Sources

The main objective of this paper is to review the energy management of a community microgrid using adaptable renewable energy sources. Community microgrids have grown up as a viable strategy to successfully integrate renewable energy sources (RES) into local energy distribution networks in response to the growing worldwide need for sustainable and dependable energy solutions. This study presents an in-depth examination of the energy management tactics employed in community microgrids using adaptive RES, covering power generation, storage, and consumption. Energy communities are an innovative yet successful prosumer idea for the development of local energy systems. It is based on decentralized energy sources and the flexibility of electrical users in the community. Local energy communities serve as testing grounds for innovative energy practices such as cooperative microgrids, energy independence, and a variety of other exciting experiments as they seek the most efficient ways to interact both internally and with the external energy system. We discuss several energy management tactics utilized in community microgrids with flexible RES, Which include various renewable energy sources (wind, solar power, mechanical vibration energy) and storage devices. Various energy harvesting techniques have also been discussed in this paper. It also includes information on various power producing technology. Given the social, environmental, and economic benefits of a particular site for such a community, this paper proposes an integrated technique for constructing and efficiently managing community microgrids with an internal market. The report also discusses the obstacles that community microgrids confront and proposed methods for overcoming them. This paper analyzes future developments in community microgrids with adaptive RES. The study discusses potential developments in community microgrids with flexible energy trading systems.

Numerical Simulation and Optimization of a Phase-Change Energy Storage Box in a Modular Mobile Thermal Energy Supply System

Featuring phase-change energy storage, a mobile thermal energy supply system (M-TES) demonstrates remarkable waste heat transfer capabilities across various spatial scales and temporal durations, thereby effectively optimizing the localized energy distribution structure—a pivotal contribution to the attainment of objectives such as “carbon peak” and “carbon neutral”. To heighten the efficiency of energy transfer for mobile heating, this research introduces the innovative concept of modular storage and transportation. This concept is brought to life through the development of a meticulously designed modular mobile phase-change energy storage compartment system. Employing computational fluid dynamics (CFD), an in-depth exploration into the performance of the modular M-TES container and the adapted phase-change material (PCM) is conducted. By implementing fin arrangements on the inner wall of the heat storage module, a remarkable upsurge in the liquid phase-transition rate of the phase-change material is achieved in comparison to the design lacking fins—this improvement approximating around 30%. However, it is essential to acknowledge that the augmentation in heat transfer gradually recedes with the proliferation of fins or an escalation in their height. Moreover, the integration of expanded graphite into erythritol emerges as profoundly effective in amplifying the thermal conductivity of the PCM. Notably, with the addition of a 15.2% volume fraction of expanded graphite to erythritol, the duration of heat storage experiences a drastic reduction to nearly 10% of its original duration, thereby signifying a momentous advancement in thermal performance.

SELECTION OF THE NON-ISOLATED UNIDIRECTIONAL DC-DC CONVERTERS FOR PHOTOVOLTAIC APPLICATIONS

The rising prominence of renewable energy sources and the demand for efficient power distribution has led to the emergence of DC microgrids as a promising solution for localized energy generation and distribution. The effective operation of DC microgrids heavily relies on the performance of their DC-DC converters, which play a crucial role in regulating power flow and voltage. Selecting suitable DC-DC converters is thus essential to ensure optimal performance and stability of photovoltaic systems. This academic article presents a comprehensive comparative analysis of different non-isolated DC-DC converter topologies and their appropriateness for DC microgrid applications. The research delves into various converter types, including buck, boost, buck-boost, SEPIC, and Zeta converters, thoroughly examining their operating principles, control strategies, and advantages within the context of DC microgrids. The focus is on key performance metrics essential for a comprehensive evaluation, including efficiency, voltage regulation, transient response, power density, and cost-effectiveness. Through meticulous comparative analysis, it is established that the SEPIC and Zeta converters stand out as exceptional choices for DC microgrids. Their distinct advantages, such as reduced output ripple, improved efficiency, and wide input voltage range, position them as valuable contenders for modern power electronics applications, showcasing their excellence in addressing diverse voltage regulation needs. This academic article contributes valuable insights into the selection and application of DC-DC converters in DC microgrid systems, providing researchers, engineers, and industry stakeholders with a comprehensive understanding of the comparative advantages of these converters. The findings underscore the significance of choosing appropriate converters to achieve efficient energy conversion, optimal power distribution, and the advancement of renewable energy technologies in the context of DC microgrids. Keywords: DC-DC converters, SEPIC, ZETA, BUCK, BOOST.

Plasmonic Cavity-Catalysis by Standing Hot Carrier Waves.

Manipulating active sites of catalysts is crucial but challenging in catalysis science and engineering. Beyond the design of the composition and structure of catalysts, the confined electromagnetic field in optical cavities has recently become a promising method for catalyzing chemical reactions via strong light-matter interactions. Another form of confined electromagnetic field, the charge density wave in plasmonic cavities, however, still needs to be explored for catalysis. Here, we present an unprecedented catalytic mode based on plasmonic cavities, called plasmonic cavity-catalysis. We achieve direct control of catalytic sites in plasmonic cavities through standing hot carrier waves. Periodic catalytic hotspots are formed because of localized energy and carrier distribution and can be well tuned by cavity geometry, charge density, and excitation angle. We also found that the catalytic activity of the cavity mode increases several orders of magnitude compared with conventional plasmonic catalysis. We ultimately demonstrate that the locally concentrated long-lived hot carriers in the standing wave mode underlie the formation of the catalytic hotspots. Plasmonic cavity-catalysis provides a new approach to manipulate the catalytic sites and rates and may expand the frontier of heterogeneous catalysis.

Experimental observation of a field-aligned ion beam produced by magnetic reconnection of two flux ropes

An ion beam field-aligned to the background guide field (B0=330 G) was observed in a reconnection experiment on the Large Plasma Device and, to the authors' knowledge, is the first experimental observation of its kind. Two kink-unstable flux ropes (L = 11 m, d = 7.6 cm) were made to collide, which allows magnetic reconnection to occur. Sub-Alfvénic ion beams with energies of up to 15 eV were then observed from measurements of the local ion energy distribution function. The beam ions do not appear to be heated. They were correlated with the collision of the ropes and appear to be energized by magnetic reconnection. The results and interpretation of the measurements are supported by three-dimensional gyrokinetic particle simulations of the merging flux ropes and electric field measurements from previous experiments [W. Gekelman et al., Astrophys. J. 853, 33 (2018)]. The mechanism behind the acceleration appears to be non-local.

Effect of the local energy distribution of x-ray beams generated through inverse Compton scattering in dual-energy imaging applications.

X-ray sources based on the inverse Compton interaction between a laser and a relativistic electron beam are emerging as a promising compact alternative to synchrotron for the production of intense monochromatic and tunable radiation. The emission characteristics enable several innovative imaging techniques, including dual-energy K-edge subtraction (KES) imaging. The performance of these techniques is optimal in the case of perfectly monochromatic x-ray beams, and the implementation of KES was proven to be very effective with synchrotron radiation. Nonetheless, the features of inverse Compton scattering (ICS) sources make them good candidates for a more compact implementation of KES techniques. The energy and intensity distribution of the emitted radiation is related to the emission direction, which means different beam qualities in different spatial positions. In fact, as the polar angle increases, the average energy decreases, while the local energy bandwidth increases and the emission intensity decreases. The scope of this work is to describe the impact of the local energy distribution variations on KES imaging performance. By means of analytical simulations, the reconstructed signal, signal-to-noise ratio, and background contamination were evaluated as a function of the position of each detector pixel. The results show that KES imaging is possible with ICS x-ray beams, even if the image quality slightly degrades at the detector borders for a fixed collimation angle and, in general, as the beam divergence increases. Finally, an approach for the optimization of specific imaging tasks is proposed by considering the characteristics of a given source.

The impact of photovoltaic power plants on surface energy budget based on an ecohydrological model

Solar photovoltaic (PV) generation has become the major type of solar energy utilization as the world's energy demand grows. However, the layout of large-scale public PV plants changes the original underlying conditions and has an impact on the local surface energy budget and distribution. Based on the ecohydrological model T&C, taking the fixed utility-scale PV plants as the typical object proposes a PV module, and the T&C-PV model is developed to simulate the impact of PV plants on the regional surface energy budget. Compared with the original T&C model, a substantially improvement of the simulation of energy flux in the PV plant paved underlying surface has been achieved in the T&C-PV model. This model is applied to PV power plants in Xinjiang Province, China, and the results show that the sensible heat flux increased by 12% and the latent heat flux decreased by 25%, with the percentage of transpiration decreasing from 90.1% to 74.5% and the percentage of evaporation increasing from 9.9% to 25.5% after the PV power plants are set up.

Insight into the weak interaction between organic primary amine and propionic acid or phenol solvents in solvent extraction

The essence of solvent extraction is to change the interaction degree between extracted molecules and solvents in the system. The study of solvent extraction at the molecular level has important guiding significance for further design. Here, taking the extraction of organic weak acid (phenol/propionic acid) by primary amines N1923 through hydrogen bond association as an example, the quantitative calculation parameters of reactive molecules were discussed, such as the charge distribution, potential distribution, average local ionization energy (ALIE) distribution and abbreviated Fukui function, while the polar index and polar area percentage were calculated. Moreover, the region and intensity of weak interaction were analyzed and visualized by electronic density difference and Van der Waals (VDW) radius. At the same time, the electron density of the critical point of bond (BCP) and the corresponding predicted value of hydrogen bonding energy are calculated. Finally, the solubility energy of primary amines and the Gibbs free energy of extraction reaction were calculated, and the results show that the interaction between organic amine and propionic acid is stronger by the hydrogen bond mechanism. This study provides a set of systematic cases to analyze the interaction between extraction molecules. It provides a new perspective for understanding the essence of solvent extraction, thus promoting the theoretical development of separation science.

Microscopic reaction mechanism for CO2 gasification of cellulose based on reactive force field molecular dynamics simulations

Gasification is the key process of biomass conversion and utilization, which has been proved to be one of the most promising technologies. In this study, the CO2 gasification process of cellulose was explored by reactive force field molecular dynamics simulations. Firstly, the distribution of average local ionization energy was analyzed. The results showed that the oxygen and hydrogen atoms might be reactive sites. In addition, the product evolution, bond-breaking behavior and carbon conversion during CO2 gasification were investigated. It was found that the bond dissociation energy of glycosidic bond was low and the bond breaking was easy to occur. The CO2 gasification of cellulose was divided into two stages, first the cellulose molecules broke down into small molecular fragments, and then they reacted with CO2. Finally, the effects of CO2/steam ratio and CO2/O2 ratio on the gasification process were analyzed. As the CO2/steam ratio decreased, the H2 yield increased, while the CO yield decreased. With the increase of CO2/O2 ratio, the carbon conversion rate had little change, while the contribution of CO2 gasification to carbon conversion decreased from 99.07% to 50%. The research provides a reference for revealing the microscopic mechanism for CO2 gasification of biomass.

A New Polymer Donor Enables Binary All-Polymer Organic Photovoltaic Cells with 18% Efficiency and Excellent Mechanical Robustness.

The development of polymerized small-molecule acceptors has boosted the power conversion efficiencies (PCEs) of all-polymer organic photovoltaic (OPV) cells to 17%. However, the polymer donors suitable for all-polymer OPV cells are still lacking, restricting the further improvement of their PCEs. Herein, a new polymer donor named PQM-Cl is designed and its photovoltaic performance is explored. The negative electrostatic potential and low average local ionization energy distribution of the PQM-Cl surface enable efficient charge generation and transfer process. When blending with a well-used polymer acceptor, PY-IT, the PQM-Cl-based devices deliver an impressive PCE of 18.0% with a superior fill factor of 80.7%, both of which are the highest values for all-polymer OPV cells. The relevant measurements demonstrate that PQM-Cl-based films possess excellent mechanical and flexible properties. As such, PQM-Cl-based flexible photovoltaic cells are fabricated and an excellent PCE of 16.5% with high mechanical stability is displayed. These results demonstrate that PQM-Cl is a potential candidate for all-polymer OPV cells and provide insights into the design of polymer donors for high-efficient all-polymer OPV cells.

The bands method for tabulating NLTE material properties

The use of Non-Local Thermal Equilibrium (NLTE) material properties within radiation-hydrodynamic simulations remains a major challenge. The plasma radiative and EOS properties in NLTE can depend on the detailed local radiation field and electron energy distribution. Fully characterizing each of these quantities may require 10’s to 100’s of parameters, making tabulation effectively impossible and requiring expensive calculations for each set of conditions within the simulation. In this work we present a new method that characterizes the local radiation field with a limited number of parameters. This permits pre-calculation and tabulation of the material properties, allowing codes to perform NLTE radiation-hydrodynamic simulations which would otherwise be computationally prohibitive.

Modeling impacts of mining activity-induced landscape change on local climate.

As a major energy source, coal has been mined on an increasingly larger scale as the social economy has continuously developed, resulting in drastic land type changes. These changes in turn cause changes in the local climate and affect the local ecological environment. Therefore, for coal cities, mining activities are an important factor influencing the local climate, and clarifying the impact of mining activities on the ecological environment is important for guiding regional development. In this paper, the impact of land use/cover changes (LUCCs) on local temperature in the spring and summer seasons from 1980 to 2018 was simulated using the Weather Research and Forecasting (WRF) model with Xilinhot city as the study area, and the regional distribution of local surface energy was analyzed in conjunction with the ground-air energy transfer process. The results show that the grassland area in Xilinhot remained above 85% from 1980 to 2018, so mining activities had a small impact on the average temperature of the whole region. However, in the mining area, the warming effect caused by mining activities was more obvious, with an average temperature increase of 0.822 K. Among other land transformation types, the conversion to water bodies had a very obvious cooling effect, lowering the temperature by an average of 2.405 K. By comparing the latent heat flux (LH), sensible heat flux (SH), and ground heat flux (GRD) under different land use types, it was found that in 2018, the LH decreased by 0.487 W/m2, the SH decreased by 0.616 W/m2, and the GRD decreased by 0.753 W/m2. The conversion to built-up urban land caused a significant decrease in the LH in the corresponding area, allowing more energy to be used to increase SH values, which resulted in significantly higher urban temperatures than in other areas.