Solution Process Research Articles

Short-Term Optimal Scheduling of Power Grids Containing Pumped-Storage Power Station Based on Security Quantification

In order to improve grid security while pursuing a grid operation economy and new energy consumption rates, this paper proposes a short-term optimal scheduling method based on security quantification for the grid containing a pumped-storage power plant. The method first establishes a grid security evaluation model to evaluate grid security from the perspective of grid resilience. Then, a short-term optimal dispatch model of the grid based on security quantification is constructed with the new energy consumption rate and grid loss as the objectives. In addition, an efficient intelligent optimization algorithm, Dung Beetle Optimization, is introduced to solve the scheduling model, dynamically updating the evaluation intervals during the iterative solution process and evaluating the grid security level and selecting the best result after the iterative solution. Finally, the improvement in the term IEEE 30-bus grid connected to a pumped-storage power plant is used as an example to verify the effectiveness of the proposed method and model.

Fennel Seed Biochar: A Sustainable Approach for Methylene Blue Removal from Aqueous Solutions.

In this study, biochars were produced from by-products of the herbal industry, specifically fennel seeds (Foeniculum vulgare), through direct activation by carbon dioxide at two different temperatures. The biochar samples were comprehensively analysed. Additionally, adsorption studies were conducted for methylene blue. The resulting adsorbents exhibited a specific surface area ranging from 2.29 to 14.60 m2/g. The resulting materials displayed a basic character on their surface. The constants for adsorption models were determined for each dye as well as thermodynamic parameters and the kinetics of the process. The sorption capacities of methylene blue for the samples exhibited a range of 22 to 43 mg/g. The adsorption kinetics of the dye on the biochar materials were found to follow a pseudo-second-order model, with the adsorption process best described by the Langmuir isotherm for the DA-800 sample and the Freundlich isotherm for the DA-750 sample. This indicates the development of a monolayer adsorbate on the biochar surfaces. The efficacy of the adsorption process in aqueous solutions of methylene blue was found to increase with rising temperature. Furthermore, based on thermodynamic studies, the adsorption process was found to be spontaneous and endothermic.

Cover Picture: Novel low‐band gap non‐fullerene acceptors based on IDIC core as potential photovoltaic materials (BKCS 9/2024) Radhiha Ravindran, Inchan Kim, Yun‐Hi Kim, Soon‐Ki Kwon

Organic photovoltaics (OPVs) attracted a lot of research attention owing to its advantages such as convenient processing technique, unsubstantial weight, low cost, flexibility and use of environmentally benign materials. In general, these are bulk heterojunction (BHJ) OPVs obtained through a solution process and the large‐area OPV production is achieved via roll‐to‐roll process. In OPVs, the BHJ active layer consists of electron donor (D) and electron acceptor (A) materials blended together by dissolving them in a common organic solvent. The new low band gap non‐fullerene based acceptors could be used as potential candidates for the fabrication of OPVs in combination with suitable donor polymers. More details are available in the article by Radhiha Ravindran, Inchan Kim, Yun‐Hi Kim, Soon‐Ki Kwon image

Versatile Papertronics: Photo-Induced Synapse and Security Applications on Papers.

Paper is a readily available material in nature. Its recyclability, eco-friendliness, portability, flexibility, and affordability make it a favored substrate for researchers seeking cost-effective solutions. Electronic devices based on solution process are fabricated on paper and banknotes using PVK and SnO2 nanoparticles. The devices manufactured on paper substrates exhibit photosynaptic behavior under ultraviolet pulse illumination, stemming from numerous interactions on the surface of the SnO2 nanoparticles. A light-modulated artificial synapse device is realized on a paper at a low voltage bias of -0.01V, with an average recognition rate of 91.7% based on the Yale Face Database. As a security device on a banknote, 400 devices in a 20 × 20 array configuration exhibited random electrical characteristics owing to the local morphology of the SnO2 nanoparticles and differences in the depletion layer width at the SnO2/PVK interface. The security Physically Unclonable Functions (PUF) key based on the current distribution extracted at -1V show unpredictable reproducibility with 50% uniformity, 48.7% inter-Hamming distance, and 50.1% bit-aliasing rates. Moreover, the device maintained its properties for more than 210 days under a curvature radius of 8.75mm and bias and UV irradiation stress conditions.

Solitary wave type solutions of nonlinear improved mKdV equation by modified techniques

In this paper, the improved and modified version of the Sardar sub-equation method (IMSSEM) and the improved generalized Riccati equation mapping method (IGREMM) are manipulated effectively and generously to determine the exact solitary wave soliton solutions of the improved modified KdV (mKdV) equation. The purpose of this study is to provide novel exact solutions to the improved mKdV equation. Specifically, we utilized IMSSEM and IGREMM to study different solutions of the nonlinear improved mKdV equation, focusing on exponential, trigonometric, and trigonometric hyperbolic type solutions. Furthermore, the plotting of various solutions for direct viewing analysis is provided in two and three-dimensional graphs. The new strategies are straightforward, quick, and efficient and have many other advantages, whereas, they provide the most accurate and unique solution to many other types of nonlinear partial differential equations (NPDEs), which usually arise in engineering and applied sciences. It should be noted that these methodologies are novel mathematical instruments that have shown to be the most effective mathematical tools for solving higher-order nonlinear partial differential equations in mathematical physics. Symbolic computation was used to validate all of the solutions that were established. Thus, it is also hoped that these techniques will ultimately reduce the cumbersome workload involved during the process of solutions to complicated NLPDEs.

Petrophysical parameter estimation using a rock-physics model and collaborative sparse representation

The estimation of petrophysical parameters is key in the identification of underground reservoirs. Current petrophysical parameter estimation methods are typically constrained by the choice of particular rock-physics models, necessitating the use of distinct models for various reservoirs. Furthermore, the inherent pronounced nonlinearity of these models presents significant challenges to the solution process in reservoir parameter inversion. Although linearized petrophysical inversion methods can simplify the solving process, they can introduce errors due to linearization. To address these limitations, we develop a petrophysical parameter estimation method driven by a rock-physics model and collaborative sparse representation (CSR). In this approach, the rock-physics model governs the fundamental pattern of the petrophysical parameters, with the CSR introducing perturbations to minimize model errors. Our method maximizes the use of well-log data and the rock-physics model, thereby reducing errors associated with linearized rock-physics (LRP) models and enhancing the method’s adaptability. We use the joint dictionary method to learn features and correlations among multiple parameters from the existing well-log data. This learned dictionary is then used as a CSR regularization constraint and applied to refine the LRP inversion objective function. Finally, the objective function is minimized using the block coordinate descent method to predict the petrophysical parameters. The effectiveness of this method in enhancing the adaptability and accuracy of petrophysical parameter estimation is confirmed through synthetic and field data tests.

An ellipse-based locating method for flexible deployment of emergency UAVs

Unmanned Aerial Vehicles (UAVs), or drones, are gaining attention in emergency response for their rapid mobility in dynamic scenarios. Constrained by limited endurance and payload, UAVs typically operate in a ”depot-customer-depot” paradigm. Thus, optimally locating multiple depots is critical to achieving operational efficiency and flexibility. Traditional location models, which rely on circular coverage, fail to capture the actual reachable area for UAV round-trips between multiple depots within a given endurance range. This drawback restricts deployment flexibility or results in excessive redundancy, even making it impractical. To address this limitation, we introduce an ellipse-based locating method for flexible UAV deployment, inspired by UAV reachability and process flexibility in manufacturing. This approach attempts to optimize the redundancy of multi-depot coverage for demand points to achieve a better balance between deployment flexibility and resource requirements. To tackle the model’s computational challenge, we present an improved Benders decomposition algorithm that speeds up the solution process by analytically addressing subproblems and implementing dominance rules to manage the master problem’s size. Simulations show that the proposed model greatly improves the ability to handle uncertainties by incorporating slight redundancy in emergency resources, and the fulfillment rate of demand fluctuations is increased by 5%–20%, which shows the superiority of enhancing the mobility and flexibility of UAV deployment.

Experimental and theoretical study on corrosion mechanism of aluminium alloy in different corrosive solutions

A detailed comparison of the corrosion behaviour of Al–O (1 1 1) surfaces on 7A46 aluminium alloy in 1.0 M hydrochloric acid and sulfuric acid solutions was conducted using electrochemical, surface analysis, and density function theory calculations. The results show that the corrosion current density is around 80.62 μA.cm−2 in HCl solution and 104.21 μA.cm−2 in H2SO4 solution. Uncovered defects in the oxide film on the alloy surface can contribute to local erosion and degradation during the corrosion process. In addition, the amounts of charge transferred from the surface of the alloy to Cl− and O2− were 0.811 and 0.178e, respectively, suggesting the formation of an Al–O bond on the surface, which expedites the corrosion process in the HCl solution. In contrast to HCl, the O atoms on the surface of the aluminium alloy obtained 2.032 e and 1.611 e electrons from Al on the Al–O (1 1 1) surfaces and S atoms in H2SO4 solution, respectively, indicating a strong adsorption affinity for SO42−. Both Cl–Al and S–Al bonds form covalent bonds. It is worth mentioning that the resonance peaks in the HCl adsorption system was between −6 eV and 2 eV, whereas that in the H2SO4 adsorption system show a more pronounced shift to the right (−10 eV to 0 eV), suggesting heightened system activity and increased electronic interactions among the atoms in H2SO4 adsorption system. This research contributes to a comprehensive understanding of the surface corrosion behaviour of aluminium alloys, providing valuable insights for the design and application of aluminium alloys across diverse environmental contexts.

Three-phase power flow using binary tree search algorithm for unbalanced distribution networks

The main objective of this study is to examine a binary tree (BT) three-phase (3Φ) power flow analysis method for unbalanced distribution networks. A simple and efficient 3Φ power flow solution method for unbalanced radial distribution networks was proposed. This method is based on the BT search structure. Large-scale distribution network problems can be evaluated using current-injection techniques and two-port network models. The power flow solution process was simplified into a set of 3 × 3 matrix operations using the BT-based method. The solution complexity remained unchanged, regardless of the size of the power system. In other words, the performance and robustness of the proposed algorithm were maintained at relatively high values with increasing system size. Furthermore, programming complexity was reduced by standardising the solution process. The effectiveness and accuracy of the proposed model and algorithm were validated using four IEEE standard benchmark feeders and a series of random cases.

Highly enhanced photoelectrocatalytic activity of NiFe/Ni/BiVO4 photoanode by a facile photoelectron-activation process in neutral solution

Photoelectrocatalytic water splitting is a promising approach to convert solar energy to hydorgen energy. Delicate design of photoanode is crucial for the excellent catalytic activity. Here, a NiFe-LDH/Ni/BiVO4 composite photoanode was prepared by magnetron sputtering of Ni followed by electrochemical deposition of NiFe-LDH on BiVO4 photoelectrode. Interestingly, after a concise photoelectron-activation process, a photocurrent of 4.9 mA/cm2 (1.23 V vs. RHE) was obtained in neutral solution, which is 4 times of the pristine BiVO4 photoanode. The photoelectro-activation process not only enhances the photocurrent, but also significantly supresses the positive spiking phenomenon of the photocurrent. A series of characterizaitons including XRD, SEM, EDX, HRTEM, and XPS ect. were performed, which revealed that the photoelectron-activation process led to the reconstruction of the surface structure of NiFe-LDH/Ni/BiVO4. The dynamic characterizaitons including stepped potential chronoamperometry, steady-state photoluminescence (PL) spectra, open-circuit potential diagrams, and electrochemical impedance spectroscopy (EIS) ect. were performed. It indicates that the activated samples can provide an enhanced internal electric field and enable the charge carriers being efficiently injected into the electrode/electrolyte interface to promote the water oxidation reaction. This investigation provided a facile activation method for BiVO4-based composite photoanode, and highly increase the PEC performance in neutral condition.

Modulating Surface-Adsorbed Oxygen Species of Bismuth Silicate by a Solid Solution Strategy for Efficient Adsorption and Photocatalytic Activity.

Bismuth silicate photocatalysts suffer from insufficient photocatalytic activity due to an insufficient number of surface active sites and low carrier separation and transport efficiency, which can be solved by defect modulation. Herein, Bi12SiO20/Bi2O2SiO3-BiOClxBr1-x (BSOCB) photocatalysts with a high concentration of surface-adsorbed oxygen species (SAOS) are synthesized by introducing a BiOClxBr1-x solid solution to modify nonhomogeneous BSO via an ion exchange strategy. The introduction of a solid solution enables the generation of dispersed nanoflowers and the regulation of SAOS due to the fact that anion-cation copolymerization guides the crystal growth, and the defects generated by the lattice distortion modulate the concentration of SAOS on the catalysts during the solid solution process. The obtained typical BSOCB photocatalyst possesses both high adsorption and photocatalytic properties, and the results show that it not only can almost completely degrade the traditional pollutant RhB within 20 min but also strongly degrades antibiotics, such as CIP (light for 150 min, 96%), NFX (light for 150 min, 87%), and TC (light for 150 min, 77%). This work provides a new approach for obtaining bismuth-based photocatalysts with controllable morphology and a large number of surface active sites and provides a theoretical and experimental basis for expanding the application scenarios of photocatalysts.

A novel meshless radial basis reproducing kernel particle approach for 3D thermo-mechanical analysis of mushy zone phase-change problems

This paper presents a three-dimensional thermo-elastoplastic computational model for the analysis of phase change problems involving the mushy zone. The model utilizes a novel meshless radial basis reproducing kernel particle approach, incorporating a high-order kernel that integrates Gaussian and cosine functions. An energy balance equation for the entire domain is formulated using the effective heat capacity method, based on the enthalpy formulation. The governing equations are discretized using the Galerkin weak form to compute thermal residual stresses, with essential boundary conditions enforced through the penalty method. Plastic deformation is characterized using the von Mises criterion with isotropic hardening, and the strain term resulting from temperature-dependent material properties is incorporated into the incremental solution process. Determination of the plastic strain increment is based on the Prandtl–Reuss flow rule. The accuracy and efficiency of the proposed meshless approach were rigorously evaluated through numerical examples encompassing two- and three-dimensional problems. The computational results were compared against available analytical and validated numerical solutions. This comprehensive assessment substantiated the robustness and precision of the developed technique. The case studies presented elucidate the capacity of the novel meshless model to effectively predict temperature distributions and residual stress fields within mushy zone phase change phenomena, accommodating both regular and irregular geometries under various boundary conditions. Notably, the model demonstrated consistent stability and high accuracy across the spectrum of simulated scenarios, thus underscoring its potential as a valuable tool for investigating complex phase change processes.

An accurate and efficient second-order J2 model for the draper semianalytic satellite theory

Semi-analytical orbit propagation methods combine the advantages of analytical and numerical methods to achieve an excellent balance between efficiency and accuracy. The increasingly congested space has led to the growing prevalence of semi-analytical methods, driven by the requirements for efficient and accurate orbit propagation in Space Situational Awareness (SSA). However, the accuracy of semi-analytical methods is only retained by considering the contribution of the J2 zonal harmonic second order terms, namely the J22 term, which has not been completely modeled in semi-analytical methods due to the complex mathematical formulations. This paper proposes a complete semi-analytical solution for the J22 contribution consistent with the Draper Semianalytic Satellite Theory (DSST), including the fully closed-form and nonsingular mean element rate equations and computationally efficient short-period terms. Firstly, for the direct application of DSST in the construction of the J22 solution, the difficulties of high computational costs induced by multiplying infinite Fourier series together are analyzed. Next, an improved construction process for the J22 solution is developed by introducing a new general form of the partial derivatives of osculating elements rates to eliminate these difficulties. Considering the complexity of the construction process, the computation details for each term in this process are then presented. Numerical experiments demonstrate that the proposed J22 solution achieves remarkable accuracy and efficiency compared to previous works.

A quantitative theory for heterogeneous combustion of nonvolatile metal particles in the diffusion-limited regime

The paper presents an analytical theory quantitatively describing the heterogeneous combustion of nonvolatile (metal) particles in the diffusion-limited regime. It is assumed that the particle is suspended in an unconfined, isobaric, quiescent gaseous mixture and the chemisorption of the oxygen takes place evenly on the particle surface. The analytical solution of the particle burn time is derived from the conservation equations of the gas-phase described in a spherical coordinate system with the utilization of constant thermophysical properties, evaluated at a reference film layer. This solution inherently takes the Stefan flow into account. The approximate expression of the time-dependent particle temperature is solved from the conservation of the particle enthalpy by neglecting the higher order terms in the Taylor expansion of the product of the transient particle density and diameter squared. Coupling the solutions for the burn time and time-dependent particle temperature provides quantitative results when initial and boundary conditions are specified. The theory is employed to predict the burn time and temperature of 10–100 μm iron particles, which are then compared with measurements, as the first validation case. The theoretical burn time agrees with the experiments almost perfectly at both low and high oxygen levels. The calculated particle temperature matches the measurements fairly well at relatively low oxygen mole fractions, whereas the theory overpredict the particle peak temperature due to the neglect of evaporation and the possible transition of the combustion regime.Novelty and significance statementFor the first time, we present a comprehensive and quantitative analytical theory elucidating the heterogeneous combustion of nonvolatile (metal) particles in the diffusion-limited regime. This novel theoretical model exhibits a remarkable capacity for quantitative prediction, obviating the need for supplementary information from numerical simulations or experimental data. The derivation process of analytical solutions for burn time and time-dependent particle temperature from conservation equations is elaborated, offering transparency and insight into the model’s foundations. To demonstrate the practical utility of the theory, we apply it to analyze the combustion of iron particles, providing valuable mathematical perspectives on the underlying processes. The model’s predictions for burn time and temperature align closely with experimental results, offering a partial validation of the theory within the realm of its applicable assumptions. This pioneering work contributes a robust and versatile analytical framework, advancing our understanding of diffusion-limited combustion phenomena of nonvolatile particles.

New discrete fractional accumulation Grey Gompertz model for predicting carbon dioxide emissions

Predicting carbon dioxide emissions is crucial for addressing climate change and achieving environmental sustainability. Accurate emission forecasts provide policymakers with a basis for evaluating the effectiveness of policies, facilitating the design and implementation of emission reduction strategies, and helping businesses adjust their operations to adapt to market changes. Various methods, such as statistical models, machine learning, and grey prediction models, have been widely used in carbon dioxide emission prediction. However, existing research often lacks comparative analysis with other forecasting techniques. This paper constructs a new Discrete Fractional Accumulation Grey Gompertz Model (DFAGGM(1,1) based on grey system theory and provides a detailed solution process. The Whale Optimization Algorithm (WOA) is used to find the hyperparameters in the model. By comparing it with five benchmark models, the effectiveness of DFAGGM(1,1) in predicting carbon dioxide emissions data for China and the United States is validated.

H∞ Differential Game of Nonlinear Half-Car Active Suspension via Off-Policy Reinforcement Learning

This paper investigates a parameter-free H∞ differential game approach for nonlinear active vehicle suspensions. The study accounts for the geometric nonlinearity of the half-car active suspension and the cubic nonlinearity of the damping elements. The nonlinear H∞ control problem is reformulated as a zero-sum game between two players, leading to the establishment of the Hamilton–Jacobi–Isaacs (HJI) equation with a Nash equilibrium solution. To minimize reliance on model parameters during the solution process, an actor–critic framework employing neural networks is utilized to approximate the control policy and value function. An off-policy reinforcement learning method is implemented to iteratively solve the HJI equation. In this approach, the disturbance policy is derived directly from the value function, requiring only a limited amount of driving data to approximate the HJI equation’s solution. The primary innovation of this method lies in its capacity to effectively address system nonlinearities without the need for model parameters, making it particularly advantageous for practical engineering applications. Numerical simulations confirm the method’s effectiveness and applicable range. The off-policy reinforcement learning approach ensures the safety of the design process. For low-frequency road disturbances, the designed H∞ control policy enhances both ride comfort and stability.

Learners’ algebraic and geometric connections when solving Euclidean geometry riders

In this article, we explored Grade 11 learners’ algebraic and geometric connections when solving Euclidean geometry riders. A qualitative interpretive case study design was followed. Thirty Grade 11 learners from a non-fee-paying secondary school in the Capricorn North district of South Africa were conveniently sampled to participate in this study. Data were collected through learners’ responses to classwork, homework exercises, and task-based interviews. Data were analysed thematically. The findings revealed that to solve Euclidean geometry riders successfully, learners need to establish the feature connections embedded in the given figure or diagram. The ability to make feature connections provides a point of departure in the solution process of a geometric problem.Contribution: Once the feature connection is established, other connections will subsequently emerge. In addition, the reversibility connections become a form of feature connection when solving Euclidean geometry riders. Therefore, we recommend that mathematics teachers emphasise and use mathematical connections in their daily teaching of mathematics.

A new solution to force analysis including Coulomb friction in mechanism joints

The objective of this paper is to propose a novel approximate solution for determining the reactions of joints in mechanical systems, which involves the influence of Coulomb friction. It is widely acknowledged that if Coulomb friction is used in determining an exact solution to the equilibrium equations for a mechanism, then it will involve nonlinear systems of equations. With the abundance of computer tools now available, tasks of this kind, especially numerical computations, are not particularly challenging. However, new analytically tractable approximate methods are still valuable as a straightforward way of solving the problem. Several studies have been carried out in this field to find a simple solution. In this paper, a new approach based on friction circle concept and Babylonian algorithm is developed for various mechanisms, which is exceptionally well-suited for calculating and streamlining the solution process for mechanical systems by eliminating the necessity for iterative steps at each stage of the force analysis.

Understanding the Catalytic Effect on the CO2 Regeneration Performance of Amine Aqueous Solutions

To address the high energy consumption of the carbon capture and storage process in the shipping industry, the effects of several commonly used commercial catalysts, such as HZSM-5-25, γ-Al2O3, and SiO2, as well as a self-prepared catalyst, Zr-HZSM-5-25, on the regeneration of MEA solution and MEA + MDEA mixed solution were investigated in this paper. The results showed that Zr-HZSM-5-25 had the best catalytic effect on the regeneration process of the MEA aqueous solution, which could increase the instantaneous maximum CO2 regeneration rate of the MEA-rich solution by about 8.25% and the average regeneration rate by about 5.28%. For the MEA + MDEA mixed solution, the reaction between tertiary amine MDEA and CO2 produced a large amount of HCO3− in the reaction system, which could accelerate the release of CO2 to a large extent, which resulted in the catalytic effect of the Zr-HZSM-5-25 catalyst on the regeneration process of the mixed amine solution being significantly lower than that on the single MEA solution, with an increase of 4.91% in the instantaneous maximum regeneration rate. This instantaneous maximum regeneration rate was only increased by 4.91%. While Zr-HZSM-5-25 showed a better performance in the bench-scale test, it reduced CO2 regeneration energy consumption by 7.3%.

A Bilevel Approach for Compensation and Routing Decisions in Last-Mile Delivery

In last-mile delivery logistics, peer-to-peer logistic platforms play an important role in connecting senders, customers, and independent carriers to fulfill delivery requests. As the carriers are not under the platform’s control, the platform has to anticipate their reactions while deciding how to allocate the delivery operations. Indeed, carriers’ decisions largely affect the platform’s revenue. In this paper, we model this problem using bilevel programming. At the upper level, the platform decides how to assign the orders to the carriers; at the lower level, each carrier solves a profitable tour problem to determine which offered requests to accept, based on her own profit maximization. Possibly, the platform can influence carriers’ decisions by determining also the compensation paid for each accepted request. The two considered settings result in two different formulations: the bilevel profitable tour problem with fixed compensation margins and with margin decisions, respectively. For each of them, we propose single-level reformulations and alternative formulations where the lower-level routing variables are projected out. A branch-and-cut algorithm is proposed to solve the bilevel models, with a tailored warm-start heuristic used to speed up the solution process. Extensive computational tests are performed to compare the proposed formulations and analyze solution characteristics. Funding: The research of E. Fernandez was partially funded through the Spanish Ministerio de Ciencia y Tecnología and European Regional Development Funds (ERDF) [Grant MTM2019-105824GB-I00]. The research of C. Archetti, M. Cerulli, and I. Ljubić was partially funded by CY Initiative of Excellence, France [Grant “Investissements d’Avenir ANR-16-IDEX-0008”]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.0129 .