Solution Method Research Articles

DECENTRALIZED PLATFORM FOR FINANCING CHARITY PROJECTS

The rapid development of new technologies, together with the emergence of new military conflicts and humanitarian crises, creates the need for quick response and the introduction of new methods of effective assistance to the affected population and the restoration of damaged territories. Decentralized charity became one of these methods of assistance. To implement the task, the latest technologies were used, which combine maximum transparency and complete security when forming and working with charitable payments. The main technologies that were used: blockchain and smart contracts on it, protocols of liquidity pools and profitable farming, as well as web development technologies for creating a web application. The research analyzed existing approaches, methods of software solutions for financing decentralized charity; developed and improved the mathematical model and architecture of the software application. A system of smart contracts was created using additional administrative modules, and on its basis, a decentralized charitable platform for assistance to Ukraine was implemented in the form of a web application. Such a decentralized system can be freely used and implemented nowadays to finance the most necessary charitable projects of our country with crypto-assets in various spheres: humanitarian, social or in matters of security and weapons.

Ambient-temperature aqueous electrochemical route for direct Re-functionalization of spent LFP cathodes of lithium-ion batteries

Relithiation is a critical step in the direct recycling process, which is the most promising method for spent LiFeIIPO4 (LFP) batteries recycling. It involves the reduction of FeIIIPO4 (FP) in a Li-ion-rich environment and is generally performed by high-temperature sintering or hydrothermal methods. This study proposes an ambient temperature electrochemical relithiation method in an aqueous solution. It follows a preliminary delithiation step described in our previous publications. The results confirmed that FP can be efficiently relithiated in either Li2SO4 or LiHCO3 electrolyte. The reaction follows mostly a Cottrellian behavior, determined from potentiostatic experiments, indicating that diffusion in solution is a critical mechanism. Application of this electrochemical relithiation process to FP originating from spent LFP resulted in a 96 % relithiation yield at a current efficiency of 91 %. The overall recycling process successfully re-functionalized deeply damaged spent LFP by recovering up to 99 % of the LFP's original discharge capacity, achieving up to 153 mAh g−1 at C/12. Meanwhile, the initial discharge capacity of the re-functionalized LFP at 1C attained 119 mAh g−1, which interestingly increased upon cycling, reaching 131 mAh g−1 after 225 cycles. This increase could be associated with electrochemical activation promoted by cycling-induced LFP crystal annealing and/or by electrochemical milling.

Hybrid finite element and laplace transform method for efficient numerical solutions of fractional PDEs on graphics processing units

Fractional Partial Differential equations (FPDEs) are essential for modeling complex systems across various scientific and engineering areas. However, efficiently solving FPDEs presents significant computational challenges due to their inherent memory effects, often leading to increased execution times for numerical solutions. This study proposes a highly parallelizable hybrid computational approach that combines the Finite Element Method (FEM) for spatial discretization with Numerical Inversion of the Laplace Transform (NILT) for time-domain solutions, optimized for execution on Graphics Processing Units (GPUs). The NILT method’s high parallelizability, stemming from the independence of its series terms, combined with the robust spatial discretization provided by FEM, enables the efficient and accurate solution of FPDEs on GPUs, demonstrating substantial performance improvements over traditional CPU-based implementations. We observe a generalized pattern in execution time behavior that accounts for both the number of nodes and the number of NILT terms. Specifically, execution time scales quadratically with the number of nodes, while showing only a logarithmic marginal increase with the number of NILT terms These behaviors not only enables consistent performance assessment but also highlights potential areas for algorithm optimization. Validation against exact solutions of fractional diffusion and wave equations, employing Caputo, modified Caputo-Fabrizio, and modified Atangana-Baleanu derivatives, demonstrates the accuracy and convergence of the hybrid FEM-NILT method. Notably, the exact solutions of wave equation are novel in literature. The results highlight the method’s potential for enabling high-precision, large-scale simulations in fractional calculus applications, thereby advancing computational capabilities and efficiency in the field.

ASSESSMENT OF AGGREGATE MIXTURE REACTIVITY IN CONCRETE AT 60°C

Research on the durability of structural concrete requires careful selection of aggregates, particularly considering their reactivity to alkali-silica reaction (ASR). The Miniature Concrete Prism Test (MCPT) allows for shortened testing time and eliminates the need for aggregate crushing, making it a practical alternative to other methods. The aim of the research is to evaluate the reactivity of aggregate mixtures with varying mineral compositions. Research results confirm the significant impact of fine aggregates on concrete expansion in the MCPT method in NaOH solution at 60°C. The observed expansion correlates with a reduction in concrete’s elastic modulus.

A nested primal–dual iterated Tikhonov method for regularized convex optimization

AbstractProximal–gradient methods are widely employed tools in imaging that can be accelerated by adopting variable metrics and/or extrapolation steps. One crucial issue is the inexact computation of the proximal operator, often implemented through a nested primal–dual solver, which represents the main computational bottleneck whenever an increasing accuracy in the computation is required. In this paper, we propose a nested primal–dual method for the efficient solution of regularized convex optimization problems. Our proposed method approximates a variable metric proximal–gradient step with extrapolation by performing a prefixed number of primal–dual iterates, while adjusting the steplength parameter through an appropriate backtracking procedure. Choosing a prefixed number of inner iterations allows the algorithm to keep the computational cost per iteration low. We prove the convergence of the iterates sequence towards a solution of the problem, under a relaxed monotonicity assumption on the scaling matrices and a shrinking condition on the extrapolation parameters. Furthermore, we investigate the numerical performance of our proposed method by equipping it with a scaling matrix inspired by the Iterated Tikhonov method. The numerical results show that the combination of such scaling matrices and Nesterov-like extrapolation parameters yields an effective acceleration towards the solution of the problem.

ЖАСӨСПІРІМДЕР ҚАРЫМ-ҚАТЫНАСЫНДАҒЫ ЖАНЖАЛ МӘСЕЛЕСІ

The article is devoted to the theoretical analysis and experimental study of various phenomena encountered in communication in adolescence. The causes and factors influencing the conflict, which is most often found in adolescents in everyday life, its negative impact on development and personality formation are analyzed. In the course of practical work, it has been proved that the process of positive communication of children in adolescence can be developed and adjusted through work aimed at special practical improvement. It is proved that the organization of special programs, by implementing them, allows you to achieve effective results in the development of communication characteristics of adolescents in the process of educational activities. In the course of the study, the results of the test "Schwarzlander success rate study" "methods of finding solutions" were presented. The purpose of the research work proved that it is possible to choose a number of defining directions and achieve an effective result of the application of developmental and correctional work. During the continuous work, the ways out of the conflict situation for teenagers were identified. In the course of correctional and developmental work with adolescents, such game and situational methods as communicating with them on equal terms, getting into various situations, getting out of them, and the emergence of psychological conflict situations were used. It was only with continuous psychological work that the possibilities and ways of prevention and correction of adolescent conflict were identified, recommendations were developed, and effective results were achieved.

Modification of the dimensional doma method for linear elliptic equations

Currently, one of the most common methods for the numerical solution of boundary value problems are difference methods (grid method, finite difference method). These methods are well suited for solving problems in regular domains. In areas of complex structure, their use leads to a number of difficulties both in the construction of difference schemes, and in the implementation on a computer. One of the methods to overcome these difficulties is the method of fictitious regions. There are four interrelated directions in the development of the method of fictitious regions: study of various ways to continue the original problems in a fictitious area; obtaining unimprovable estimates in stronger metrics; extension of the class of problems on the application of the method of fictitious areas; construction of effective difference schemes for solving auxiliary problems constructed by the method of fictitious areas. For the first time, the fictitious domain method for the Navier-Stokes equation was studied in the work of A.N. Bugrova, Sh. Smagulov, Smagulov Sh. This article discusses the method of additional areas, which is an analogue of the method of fictitious areas for solving linear boundary value problems, but in the auxiliary problem of this method there is no small perimeter. This method is based on the variational principle of solving linear boundary value problems of elliptic type in an arbitrary region. The existence of a solution is proved by the Galerkin uniqueness method.

Integrasi Analytic Network Processing dan Technique for Order Preference by Similarity to Ideal Solution sebagai Perancangan Strategi dalam Meningkatkan Daya Saing pada Perguruan Tinggi XYZ

Seizing consumer preferences is crucial for organisations amidst increasingly intense competition. Success in this competition depends on the product's ability to fulfil customer needs and wants. All universities in Indonesia are faced with similar challenges, namely how to formulate and plan for their future in the face of ever-evolving societal changes. To respond to this challenge, it is necessary to develop a strategy that increases the competitiveness of universities. From the literature review, the criteria for increasing the competitiveness of the XYZ Institute are obtained, namely, product, price, place, promotion, people, process, physical evidence. Each criterion, through the brainstorming, is broken down into sub-criteria. The process to determine the right strategy design can be done in many methods, and among them are the ANP (Analytical Network Process) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The results of weighting the criteria using the ANP method using the Super Decisions software are then ranked using the TOPSIS method. The result is that the three best strategies are to improve the Product, namely, Alumni Quality (score 0.713397108), followed by improving Promotion, namely, the Institute accreditation score (score 0.709584147) and the People aspect, namely, student input selection (score 0.704887758).

The impact of port green competitiveness on the hinterland economy: A case study of China.

In the global trade landscape, ports are not only critical nodes for the transportation of goods but also increasingly recognized as key factors driving sustainable development through their green competitiveness. This paper takes a green competitiveness perspective to delve into the interactive relationship between port development and the hinterland economy, aiming to provide a theoretical foundation and policy recommendations for the green development of ports. An evaluation index system for green competitiveness of ports was constructed, and a combination of the Slacks-Based Measure (SBM) and the Entropy Weighted-Technique for Order Preference by Similarity to Ideal Solution (EW-TOPSIS) method was employed to quantitatively measure and assess the 25 major coastal ports and their hinterland economic systems in China. The study reveals that the overall green competitiveness of these major coastal ports is on the rise, yet notable disparities exist among individual ports. Regionally, the green competitiveness of the Yangtze River Delta port group stands out, while that of the Bohai Rim, southeastern, Pearl River Delta, and southwestern coastal port groups is relatively low. Empirical analysis conducted in this paper demonstrates the positive impact of port green competitiveness on the hinterland economic system, particularly its significant role in enhancing the total and quality aspects of the hinterland economy. Furthermore, it was found that the green competitiveness of ports exerts a more pronounced promotional effect on the hinterland economies of the Yangtze River Delta and Pearl River Delta port groups compared to that on the Bohai Rim, southeastern, and southwestern coastal port groups. The results of this paper also hold important guiding value for optimizing the allocation of port resources, promoting port technological innovation, and improving port environmental management, contributing to the harmonious coexistence and long-term development of ports and their hinterlands.

Ação Direta de Inconstitucionalidade nº 5.779: a preponderância da efetividade do direito à saúde sobre a hierarquia das normas jurídicas

Objective: To reflect on whether the hierarchy of legal norms should be used as an infallible method of solution even when an apparent conflict between legal norms involving health law can be better resolved through a technical decision by the competent regulatory agency. Methodology: data was collected. In particular, Resolução de Diretoria Colegiada nº 52/2011, Law nº 13.454/2017 and Ação Direta de Inconstitucionalidade nº 5.779-DF. Specialized legal doctrine was sought on the central and peripheral themes. The data collected was analyzed using the critical-narrative review technique. Results: In Brazil, the adoption of regulatory agencies as normative agents and regulators of economic activities has made it possible to make decisions based less on political criteria than on technical criteria. The legislator, anchored in political criteria, according to the judiciary, cannot go beyond technical criteria. Conclusion: the judgment in Ação Direta de Inconstitucionalidade nº 5.779 shows that today's concept and the legal nature of the right to health impose new legal paradigms that validate the role of regulatory agencies (making technical decisions in favor of maximum effectiveness of the right to health), even to the detriment of politically legitimized decisions by the legislature. The formal paradigm cannot prevent the materialization of the right. Submission: 03/18/24| Review: 08/16/24| Approval: 08/16/24

Spectral eigenfunction decomposition of a Fokker–Planck operator for relativistic heavy-ion collisions

A spectral solution method is proposed to solve a previously developed non-equilibrium statistical model describing partial thermalization of produced charged hadrons in relativistic heavy-ion collisions, thus improving the accuracy of the numerical solution. The particle’s phase-space trajectories are treated as a drift-diffusion stochastic process, leading to a Fokker–Planck equation (FPE) for the single-particle probability distribution function. The drift and diffusion coefficients are derived from the expected asymptotic states via appropriate fluctuation–dissipation relations, and the resulting FPE is then solved numerically using a spectral eigenfunction decomposition. The calculated time-dependent particle distributions are compared to Pb–Pb data from the ATLAS and ALICE collaborations at the Large Hadron Collider.

Column generation approach for 1.5-dimensional cutting stock problem with technical constraints

In this study, the 1.5-dimensional cutting stock problem with technical constraints is considered. In the literature, this problem is also defined as a strip packing or open dimension problem. When given a strip of infinite length and bounded width, the problem is to define a packing of rectangular objects into a strip that minimizes its final length. Technical constraints, such as the order type and the number of strips, are indispensable in real life; however, they are often neglected in the literature because they make the problem difficult to solve. Only one study was reached in the literature that took into account technical constraints, but in that mentioned study, only a mathematical model was proposed for the problem. In this context, our aim is to solve the problem with a more effective approach. The research question in this study is the usability of the column generation technique to solve the 1.5-dimensional cutting stock problem. In this study, the column generation approach was proposed for the first time for the considered problem. To demonstrate the performance of the proposed solution method, randomly generated test problems were solved with GAMS/Cplex. As we report the results, proposed column generation approach (CG) reaches very close (such as %1 and %2 error) solutions to integrated mathematical model (IM) for small sized problems in a second. On the other hand, while CG solved all the problems in a reasonable time, IM could not produce a feasible solution to some problems. Numerical experiments showed that the column generation algorithm outperforms the integrated mathematical model for the problem.

Magnetohydrodynamic Stagnation Point Flow and Heat Transfer of Casson Fluids Over a Stretching Sheet

This research investigates the effects of heat transfer on the stagnation-point flow of a non-Newtonian Casson fluid in a two-dimensional magnetohydrodynamic (MHD) boundary layer over a stretched sheet, considering thermal radiation impacts. By employing similarity transformations, the governing partial differential equations are transformed into nonlinear ordinary differential equations. The obtained self-similar equations are numerically solved using the Optimal Homotopy Analysis Method (OHAM). The numerical results are graphically represented, showcasing the influence of various parameters on fluid flow and heat transfer characteristics. The study uncovers important dynamics in transport phenomena. Examining and illustrating the effects of dimensionless parameters on velocity, temperature, and concentration profiles reveal significant insights. Moreover, skin friction and Nusselt number results for Casson fluids are analyzed and presented. The findings indicate that the Casson parameter and Hartman number act in opposition to fluid momentum, while the thermal conductivity parameter enhances fluid temperature. Thus, this research provides valuable insights into MHD boundary layer flows of non-Newtonian Casson fluids with thermal radiation effects, and the OHAM solution method proves effective in predicting flow transport properties.

Flexibility-Oriented AC/DC Hybrid Grid Optimization Using Distributionally Robust Chance-Constrained Method

With the increasing integration of stochastic sources and loads, ensuring the flexibility of AC/DC hybrid distribution networks has become a pressing challenge. This paper aims to enhance the operational flexibility of AC/DC hybrid distribution networks by proposing a flexibility-oriented optimization framework that addresses the growing uncertainties. Notably, a comprehensive evaluation method for operational flexibility assessment is first established. Based on this, this paper further proposes a flexibility-oriented operation optimization model using the distributionally robust chance-constrained (DRCC) method. A customized solution method utilizing second-order cone relaxation and sample average approximation (SAA) is also introduced. The results of case studies indicate that the flexibility of AC/DC hybrid distribution networks is enhanced through sharing energy storage among multiple feeders, adaptive reactive power regulation using soft open points (SOPs) and static var compensators (SVCs), and power transfer between feeders via SOPs.

Efficient Near-Infrared Quantum Cutting in Y2O3 co-doped with Ho3+, Yb3+ Phosphor for the Application in Solar Cell

Abstract: An efficient Near-Infrared Quantum Cutting has been demonstrated in Ho3+ and Yb3+ co-activated Y2O3 sample, synthesized by a complex based precursor solution method. The phosphors have been characterized by X-ray diffraction (XRD), Crystal structure photoluminescence (PL) and CIE Chromaticity analysis. The phosphor materials give efficient emission in the green region both through UC and PL, while efficient NIR emission is observed through the QC process. The Photoluminescence emission (PL) spectra of Y2O3 doped 1% Ho3+ x% Yb3+ (x= 0, 5, 10, 20, 30, and 50) samples, The cooperative energy transfers from one Ho3+ to two Yb3+, an intense NIR emission around 549 nm of Yb3+ 2F5/2 - 2F7/2 transition was obtained under 449 nm excitation. Near infrared photons (wavelength range 549 nm) emitted by an Yb3+ ion pair. The Properties of Y2O3 doped with Ho3+ and Yb3+ quantum-cutting phosphors are dependent on various factors such as dopant concentration, crystallinity, homogeneity, particle size. Effective control of the above parameters the quantum-cutting ability of the phosphor material. Small particle size of the quantum-cutting phosphor Y2O3:Ho3+, Yb3+ make it a suitable candidate for its application in solar cells.

Enhancing Novice Developer Efficacy through UX Journey: Integrating User Experience and User Requirement to Develop Developer Skills

User experience and user requirements are two different approaches to software development. User requirements focus on meeting customer expectations and demands for software solutions, while user experience covers all aspects of software interaction with users. To increase the value of the software, the software must have usable and easy-to-use features with an attractive design or work environment that fits the user's behavior. Integrating software requirements and user experience can increase developer productivity by focusing on features that meet user requirements and expectations. This integration can also increase software development efficiency by addressing issues arising during development. This article addresses developers' challenges when addressing user needs and provides practical solutions widely accepted in industry and academia. Combining user experience and user needs into the UX Journey approach can increase developer productivity and confidence in software development. The design of the UX Journey is carried out by evaluating several existing design solution methods such as Design Thinking, IDEO, HPI, and Double Diamond to determine the existing conditions and needs for the problems faced. Then, by mapping the user, context, and domain, the model is obtained. appropriate. The proposed model comprises Discover, Explore, Test, and Listen activities. A trial was carried out on the respondents to test the method, and a feasibility test and an implementation schedule were obtained based on the statistical analysis of the initial user. It took 980-1500 minutes to complete the design solution. Focusing on features that align with user needs and improve problem-solving efficiency throughout development gives developers greater confidence in producing high-quality software.

Robust joint multiple resources allocation algorithm for cooperative underwater acoustic communication networks

AbstractIn this article, a joint relay selection, power control and time allocation problem is studied to maximize the energy efficiency for the cooperative underwater acoustic communication networks. The joint optimization problem is full of challenges due to the strong coupling of multiple resources and the uncertain characteristics of the underwater acoustic communication scenario. To address this issue, the worst‐case method is employed to transform an original uncertain problem into a deterministic problem. Furthermore, we propose the block coordinate descent‐based method to decouple the strongly coupling multi‐resource allocation problem into three relatively independent sub‐problems. The coupling of multiple resources is completely decoupled, thereby greatly reducing the solving difficulty. In addition, given that the sub‐problems with the fractional objective function are still non‐convex and hard to solve, the Dinkelbach‐based method is proposed to transform the fractional objective function into a subtractive form. At last, the relay selection sub‐problem is transformed into a integer programming problem, and the time allocation sub‐problem is transformed into a linear programming problem, whose optimal solutions can be obtained by some well‐established solution methods. The power allocation problem is transformed into a convex optimization problem, which can be solved by the Lagrangian dual method. Finally, in the proposed iteration structure, the three sub‐problems are alternatingly solved until convergence. Simulation results are presented to demonstrate the efficiency and robustness of the proposed algorithm.

Slab assignment to non-identical reheat furnaces running in parallel mode

This article analyses a slab assignment problem for non-identical reheat furnaces in the steelmaking industry. We tackle the problem of assigning slabs to different types of reheat furnaces, a walking beam and a pusher type furnace. Furthermore, we need to determine the feed-in as well as the residence time for each slab. The aim is to (i) reduce the energy consumption, (ii) increase the production rate and (iii) the heating quality of the slabs which depends on the assigned furnace and to what extent the slabs are overheated. Moreover, the subsequent production stage (Hot Rolling Mill), needs to be synchronized with the furnaces which is essential for a smooth production. We specify the problem as a mixed integer optimization formulation that is solved with iterative parameter adjustment. Rapid convergence leads to a novel two-phase solution method that yields furnace schedules that are optimal for the adjusted parameter values in reasonable time. The results show that our proposed method performs better than an industry benchmark by increasing the production rate and increasing the reheating quality. Furthermore, the new generic problem formulation allows using standard software and can be applied to identical or non-identical furnaces highlighting its broad applicability across steel-making companies.

Development of a New Thermal-Hydraulic Module for FRENETIC, a Code for the Multiphysics Analysis of Liquid Metal–Cooled Reactors

This paper describes the development of a new thermal-hydraulic (TH) module for the Fast REactor NEutronics/Thermal-hydraulICs (FRENETIC) multiphysics code for the full-core simulation of liquid metal–cooled fast reactors, developed at Politecnico di Torino. The code performs steady-state and transient neutronic (NE) and TH coupled calculations while maintaining a relatively low computational cost thanks to the adoption of simplified physical models. The NE module implements the nodal formulation of the multigroup neutron diffusion equations with delayed neutron precursors whereas the TH module treats the reactor hexagonal assemblies as separate channels, which are individually modeled as one-dimensional in the axial direction, accounting for the thermal coupling in the horizontal direction. The new TH module is more robust and portable while providing improved performance with respect to the previous implementation—also thanks to the adopted OpenMP parallelization. Some physical aspects that were previously neglected, such as the thermal inertia of nonfuel rods, have also been included in the model. The development was carried out in accordance with current best practices for code design, implementation, and testing, thus rendering the code easier to be maintained and possibly to be extended in the future. The code usability has also been improved by means of a set of Python classes purposely developed to simplify the input generation and postprocessing phases. This can potentially widen the usage of FRENETIC within the fast reactor community for the simulation of full-core coupled NE-TH transients and/or as a platform to test new solution methods. The paper also includes the application of this new FRENETIC version to a representative configuration of the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED) core design. First, the nominal operating conditions of the ALFRED reactor were simulated, proving that the new upgrade of the code is faster and more robust with respect to the previous one. Then, two accidental transients where NE-TH feedback effects are relevant—an unprotected loss of flow and a total instantaneous blockage of a single fuel assembly—were considered.

Dynamic job allocation method of multiple agricultural machinery cooperation based on improved ant colony algorithm

Contemporary large-scale and systematic agricultural operations demand the collaborative efforts of multiple agricultural machines with distinct functionalities. However, the failure of a single agricultural machine during collaborative operations jeopardizes the entire undertaking. To address this challenge, this paper proposes a multi-machine collaborative dynamic job allocation method based on the improved ant colony algorithm. Initially, the improved ant colony algorithm is employed to determine the optimal solution for harvester scheduling. This solution is then fed into the data conversion algorithm to acquire the necessary unloading point information for transport vehicle scheduling. Subsequently, the improved ant colony algorithm is once again utilized to optimize the transport vehicle scheduling. In cases of agricultural machinery failure or changes in the operating environment, two distinct methods are employed based on the situation. The first involves double-layer rescheduling of both harvester and transport vehicles, while the second employs single-layer rescheduling exclusively for the transport vehicles, yielding the respective rescheduling results. The outcomes demonstrate that the proposed solution method effectively identifies the current optimal scheduling plan for both the harvester and transport vehicle in the event of malfunctions. Moreover, under the premise that the unproductive waiting time of the harvester is reduced to zero, and the number of transport vehicles is minimized, it achieves the minimization of operating time cost and transportation cost. This method exhibits significant potential for seamless integration into the practical application of unmanned farms, providing a foundation for addressing scheduling and management challenges in multi-agricultural machinery collaborative operations within complex farmland operating environments.