Formulation Of Problem Research Articles

Maximum power optimization of a direct-drive wind turbine connected to PMSG using multi-objective genetic algorithm

This work aimed to develop and evaluate a maximum power point tracking (MPPT) control system for a wind energy conversion system (WECS) based on a permanent magnet synchronous generator (PMSG). PMSG is commonly used to generate direct-drive and variable-speed wind energy. Initially, the generator and converter on the DC load side are controlled to follow the wind speed reference set by the MPPT algorithm. The paper presents the optimization problem formulation, including the optimization space, constraints, and objectives. The genetic algorithm (GA) is used to extract the maximum power from the WECS in this design improvement. In this study, to control and stabilize the maximum power point (MPP) of the wind turbine, a proportional integral (PI) controller and a GA heuristic approach were utilized. The GA approach was employed to determine the best settings (Kp, Ki) using MATLAB/Simulink with a 12.3 kW PMSG to model and simulate the proposed system. Based on four performance indicators-integrated squared error (ISE), integrated absolute error (IAE), integrated time absolute error (ITAE), and integrated time squared error (ITSE), the GA approach was used to optimize the controller settings. The results of the simulation show that the wind turbine (WT) can effectively track the necessary MPP. The simulation's output also includes generated power, DC bus voltage, electromagnetic torque, and currents.

Offset-Free Koopman Model Predictive Control of Thermal Comfort Regulation for a Variable Refrigerant Flow-Dedicated Outdoor Air System-Combined System

Abstract Variable refrigerant flow (VRF) system has been an appealing solution of air conditioning for residential and commercial buildings, due to its flexibility and cost effectiveness, while lack of ventilation capability is a major drawback. Incorporation of dedicated outdoor air system (DOAS) is a typical practice. However, good coordination between DOAS and VRF is critical for achieving desired thermal comfort is challenging due to the possible complexity of mixed sensible and latent heat exchanges. In this paper, to handle the nonlinear dynamic characteristics of VRF-DOAS system, we propose an offset-free Koopman model predictive control (MPC) strategy for thermal comfort regulation, in which the MPC design is computationally more efficient due to the convex problem formulation and the use of reduced-order Koopman models, and the offset-free MPC structure enhances the robustness to model uncertainties and unmeasured disturbances. A control-oriented model is obtained by hybridizing the first-principle and data-driven modeling approach. The proposed controls strategy is evaluated with a Modelica simulation model of a VRF-DOAS system. A Dymola-Python cosimulation platform is developed via the functional mockup interface (FMI), for which the MPC algorithms are implemented in Python. Simulation results show significantly better performance of the offset-free Koopman MPC in thermal comfort regulation.

Towards Environmentally Sustainable Aviation: A Review on Operational Optimization

In recent years, the rapid growth of air traffic has intensified pressure on the air transport system, leading to congestion problems in airports and airspace. The projected increase in demand exacerbates these issues, necessitating immediate attention. Additionally, there is a growing concern regarding the environmental impact of the aviation sector. To tackle these challenges, the adoption of advanced methods and technologies shows promise in expanding current airspace capacity and improving its management. This paper presents an overview of sustainable aviation, drawing on publications from academia and industry. The emphasis is on optimizing both flight and ground operations. Specifically, the review delves into recent advancements in airline operations, airport operations, flight operations, and disruption management, analyzing their respective research objectives, problem formulations, methodologies, and computational experiments. Furthermore, the review identifies emerging trends, prevailing obstacles, and potential directions for future research.

Concurrent or Retrospective Thinking Aloud in Usability Tests? A Meta-Analytic Review

In usability tests, the users are commonly asked to think aloud to let the evaluator listen in on their thoughts. Two variants of this procedure involve that the users either think aloud while using the tested product (concurrent thinking aloud, CTA) or after using it (retrospective thinking aloud, RTA). This study reviews the studies that compare CTA and RTA to investigate what is gained and lost by using one or the other variant in a usability test. A total of 29 studies, reporting from 42 comparisons of CTA and RTA, matched the inclusion criteria and were included in the meta-analyses. The main differences are that for CTA task time is longer, but total time shorter, whereas for RTA the users verbalize more explanations, problem formulations, and design recommendations. In addition, CTA users probably experience the evaluator’s presence as less disturbing than RTA users do.

Exponential Stability of the Numerical Solution of a Hyperbolic System with Nonlocal Characteristic Velocities

In this paper, we investigate the problem of the exponential stability of a stationary solution for a hyperbolic system with nonlocal characteristic velocities and measurement error. The formulation of the initial boundary value problem of boundary control for the specified hyperbolic system is given. A difference scheme is constructed for the numerical solution of the considered initial boundary value problem. The definition of the exponential stability of the numerical solution in ℓ2-norm with respect to a discrete perturbation of the equilibrium state of the initial boundary value difference problem is given. A discrete Lyapunov function for a numerical solution is constructed, and a theorem on the exponential stability of a stationary solution of the initial boundary value difference problem in ℓ2-norm with respect to a discrete perturbation is proved.

The Effect of Hexagon Fraud Elements on Village Fund Fraud with Religiosity as a Moderating Variable

This research is motivated by the many cases of fraud that occur, especially related to village funds which can harm the community and hinder village progress. There is a possibility of village fund fraud in Way Suluh Krui Village. There is fraud detection using the fraud hexagon theory. Differences in the results of previous research related to the detection of fraud have been observed through the fraud hexagon theory. This study aims to determine the effect of the fraud hexagon element on the possibility of fraud moderated by religiosity. This study uses quantitative research with the formulation of associative problems. The participants in this study were local village government officials totalling 32 samples. This study used primary data with a research instrument using the questionnaire method, namely distributing questionnaires, then the results were collected and analyzed using SEM-PLS analysis with SmartPLS 4 software. The results showed that while conspiracies affected town store, extortion, pressure, opportunity, legitimization, capacity, pomposity, and agreement could not be used by legalism to direct the impact of the extortion hexagon components against the chance of town reserve extortion. Keywords: fraud hexagon, village fund, religiosity

On the use of elliptic PDEs for the parameterisation of planar multipatch domains

AbstractThis paper presents a parameterisation framework based on (inverted) elliptic PDEs for addressing the planar parameterisation problem of finding a valid description of the domain’s interior given no more than a spline-based description of its boundary contours. The framework is geared towards isogeometric analysis (IGA) applications wherein the physical domain is comprised of more than four sides, hence requiring more than one patch. We adopt the concept of harmonic maps and propose several PDE-based problem formulations capable of finding a valid map between a convex parametric multipatch domain and the piecewise-smooth physical domain with an equal number of sides. In line with the isoparametric paradigm of IGA, we treat the parameterisation problem using techniques that are characteristic for the analysis step. As such, this study proposes several IGA-based numerical algorithms for the problem’s governing equations that can be effortlessly integrated into a well-developed IGA software suite. We augment the framework with mechanisms that enable controlling the parametric properties of the outcome. Parametric control is accomplished by, among other techniques, the introduction of a curvilinear coordinate system in the convex parametric domain, for which more general elliptic PDEs are adopted. Depending on the application, parametric control allows for building desired features into the computed map, such as homogeneous cell sizes or boundary layers.

Heuristic-Based Hybrid Algorithm for Value Stream Design with Milk-Run Approach

In this study, a heuristic algorithm has been developed for the Milk-Run related to the vehicle routing problem. It aimed to supply in the right place and at the right time in a short time with the internal logistics system approach. Since the proposed problem formulation is NP-hard, we suggested a heuristic-based hybrid genetic algorithm method to solve the problem. Real life problem is solved with a milk run approach inspired by vehicle routing problems. Firstly the model was developed with mixed integer linear programming then the problem was solved with the proposed hybrid genetic algorithm. The aim reduce the total transportation cost in the network and the number of vehicles required by using an efficient vehicle routing strategy. It explains the change in the existing distribution and collection systems of a logistics service company. The response of variables such as time, weight, volume, and pallet was measured under various scenarios with cost and time savings by applying Milk-Run optimization. The deterministic model and the proposed heuristic algorithm compared the previews and outputs of the paths. Accordingly, 30% and 50% discounts were made on restrictions for six different scenarios.

Enhanced Traffic Light Guidance for Safe and Energy-Efficient Driving: A Study on Multiple Traffic Light Advisor (MTLA) and 5G Integration

This paper presents Multiple Traffic Light Advisor (MTLA), a novel Green Light Optimal Speed Advisory (GLOSA) system that leverages 5G communication technology. GLOSA systems are emerging as a key component in intelligent transportation systems, thanks to the development of effective communication technologies. At its core, MTLA serves as a guidance system for drivers, providing real-time instructions to adjust vehicle speed to optimize the utilization of current and future states of traffic lights along their route.The work addresses several limitations in the current state-of-the-art approaches, including the use of an overly simplified velocity profile, the omission of potential grip and jerk in problem formulation, and the absence of a detailed description of the algorithm’s implementation aspects. Initially, we comprehensively present an optimization-free implementation of the overall control architecture based on an unconventional speed profile. Subsequently, MTLA is improved within a non-linear Model Predictive Control (MPC) framework which uses the latter nonoptimal solution as an initial guess and considers potential grip and jerk in the problem formulation. The developed systems are numerically tested and compared within a high-fidelity simulation environment using the IPG CarMaker simulator. The results demonstrate promising performance in terms of energy savings, with a significant reduction of 37% in energy usage, as well as improved overall comfort with respect to the case where no guidance is given to the driver. These findings suggest a high potential for future developments in this domain.

Analysis of sports policy in Papua in the formation of the Papuan contingent at the XX National Sports Week (PON)

Analyzing sports policy in Papua in the formation of the XX PON contingent is something that must be done because the achievements of Papua Province at the national level at the national sports week (PON) event, which is held every 4 years, will be increasingly competitive. This study aims to analyze sports policy in Papua in the formation of the Papua contingent at the XX national sports week (PON). Using qualitative methods with data collection techniques interviews, observation and documentation. With the policy analysis methodology used in problem solving: problem formulation, forecasting, recommendations, monitoring, and evaluation. The participants were the Indonesian National Sports Committee (KONI) Papua, the Papua Sports and Youth Office (DISORDA), the Papua Provincial Sports Branch Management, coaches and athletes totaling 22 people. The results of this analysis found that the policies taken by Papua Province in the formation of the XX PON contingent related to the recruitment of Papuan domiciled athletes, recruitment of athletes domiciled outside Papua (contract athletes) and training centers inside and outside Papua aim to determine the medal acquisition target, improve achievement and become a good host. The results of the study concluded that the province of Papua has a policy, namely the Papua Governor Regulation Number 29 of 2020 concerning the Description of Duties and Functions of the Papua Provincial Sports and Youth Office and in the stage of drafting a Special Regional Regulation (PERDASUS) of Sports and the use of athlete mutation regulations in the framework of PON contained in KONI Decree Number 56 of 2010 as an attitude of primordialism to achieve the successful achievement target of the host of the XX Papua PON. Through this research can provide positive input for the Papua provincial government to realize the Sports PERDASUS so that the selection of potential athletes in Papua is managed with a planned, systematic, measurable and sustainable sports coaching pattern. Keywords: Sports Policy, Papua Contingent, PON XX

Projection Forecasting Policy of Buton Asphalted Mining Management in Indonesia

Asphalt, which is the result of lubricating coal minerals (non-renewable), requires effective management from the government which is realized through rational policies. Efficient policy planning is needed to overcome policy problems without causing major consequences. This research aims to develop selected policy alternatives through selecting alternative policies for managing Buton asphalt mines in Buton Regency. The focus of this research is public policy analysis, namely methods for identifying problems, determining goals, evaluating alternative options, selecting alternatives, and measuring policy performance. This research, only focusing on the best alternative for management policies for the Buton asphalt mine in Kab. Buton. This research aims to analyze and identify: selected policy alternatives to be recommended in the management of asphalt mines in Kab. Buton. The approach used is mixed method. In problem formulation, using descriptive qualitative, to project policy alternatives using public policy analysis techniques through three stages (I), problem formulation techniques (hierarchy), developing into the Projection Forecasting method (extrapolative), ending with alternative selection based on Franklin's criteria. Alternative method looks at the consequences of each policy are equivalent to scoring based on technical, economic, financial and administrative feasibility. The research results show that there are three alternatives developed based on projection forecasting (extrapolative) assessments, namely: structuring institutional authority in asphalt mining management (2.36), strengthening Buton asphalt policy as a leading sector in Buton Regency (2.82), consistency policy in the preparation of Buton asphalt mine management policies (3.18). The selection of consistent alternatives for developing Buton asphalt mine management policies is the most prominent and has a fairly high probability of success and can be carried out. Where policy consistency through social mapping and domestic policy obligations increasing a larger portion for optimal domestic use (distribution to regions for use of State roads) can encourage the use of Buton asphalt nationally. If this condition continues, economic growth can continue. Alternative consistency in preparing Buton asphalt mine management policies in making Buton asphalt mine management policies is the best alternative choice for Buton asphalt mine management policies in Buton Regency.

WELL-POSEDNESS OF A NONLINEAR INTERFACE PROBLEM DESCRIBED BY HEMIVARIATIONAL INEQUALITIES VIA BOUNDARY INTEGRAL OPERATORS

AbstractThis paper is devoted to the well-posedness of a novel nonlinear interface problem on an unbounded domain with nonmonotone set-valued transmission conditions. This interface problem involves a nonlinear monotone partial differential equation in the interior domain and the Laplacian in the exterior domain. Such a scalar interface problem models nonmonotone frictional contact of elastic infinite media. The variational formulation of the interface problem leads to a hemivariational inequality (HVI), which however lives on the unbounded domain, and thus cannot be analyzed in a reflexive Banach space setting. Boundary integral methods lead to another HVI that is amenable to functional analytic methods using standard Sobolev spaces on the interior domain and Sobolev spaces of fractional order on the coupling boundary. Broadening the scope of the paper, we consider extended real-valued HVIs augmented by convex extended real-valued functions. Under a smallness hypothesis, we provide existence and uniqueness results and, moreover, establish a stability result for extended real-valued HVIs with respect to the extended real-valued function as a parameter. Based on the latter general stability result, we provide various stability results for the interface problem, as well as the stability of a related bilateral obstacle interface problem with respect to the obstacles.

A Unified Thermo-Fluid–Solid Formulation for FSI and Phase Change Problems Based on the Particle Finite Element Method

The modeling of industrial processes that involve phase change (e.g., casting, welding or additive manufacturing) is challenging due to their multiscale and multiphysics nature. The coupling of the fluid and solid mechanics is difficult due to the unknown and evolving fluid–solid interface. To deal with the difficulty of the coupling, a unified approach has been developed where fluid and solid regions are represented in the same computational domain and solved by a single solver. The interaction of fluid and solid regions is therefore automatically captured and the material can locally undergo phase transition. This allows to capture the flow in the melt and the thermal stresses in the solid. The solid material model is currently limited to linear elasticity, but it opens the path to more complex material models with plasticity modeling, which already exist in the literature. The proposed method is based on the Particle Finite Element Method (PFEM), which has been shown to accurately handle both fluid and solid mechanics. In this work, we present the key aspects of this novel unified formulation and the treatment of the fluid–solid interface in the PFEM context. The methodology is presented and verified using a set of tests. A laser spot welding example test case demonstrates the potential of combining the unified formulation with the interface treatment and the phase change capabilities and is used for the validation of the present technique.

Stability of Beam Bridges Under Bridge-Vehicle Interaction

In this paper, we provide an accurate and reliable formulation for simulating the interactions of both train/bridge subsystems and suitable for high-speed railway lines as well as for existing lines worldwide that are being renewed or modernized. We model the train as a series of suspended masses, taking into account the energy dissipation and the suspension system for each train vehicle. On the other hand, the bridge supporting the rails with irregular elevations will be modeled as an Euler-Bernoulli beam. The mathematical formulation of the interaction problem between the two subsystems requires the writing of two sets of equations, which interact with each other through contact forces. Using a one-dimensional finite element formulation, a series of equations are constructed by Modeling the beam structure. In addition, the suspended mass equations are first discretized using Newmark's finite difference formulas, which then reduce the degrees of freedom (DOF) of the vehicle to those of the bridge element. This solves the coupling problem between the two subsystems. The derived component is known as the vehicle/bridge interaction (VBI) element. On the other hand, an iterative procedure will be used subsequently to solve the non-linearity problem of the resulting system of differential equations. MATLAB programs provide results that identify the critical parameters influencing the bridge's dynamic stability.

Learning Lyapunov terminal costs from data for complexity reduction in nonlinear model predictive control

AbstractA classic way to design a nonlinear model predictive control (NMPC) scheme with guaranteed stability is to incorporate a terminal cost and a terminal constraint into the problem formulation. While a long prediction horizon is often desirable to obtain a large domain of attraction and good closed‐loop performance, the related computational burden can hinder its real‐time deployment. In this article, we propose an NMPC scheme with prediction horizon and no terminal constraint to drastically decrease the numerical complexity without significantly impacting closed‐loop stability and performance. This is attained by constructing a suitable terminal cost from data that estimates the cost‐to‐go of a given NMPC scheme with long prediction horizon. We demonstrate the advantages of the proposed control scheme in two benchmark control problems.

Constructing shared understanding of complex interdisciplinary problems: Epistemic games in interdisciplinary teamwork

ABSTRACT Background Constructing shared understanding of complex interdisciplinary problems is one of the most challenging aspects of interdisciplinary teamwork. How this process unfolds is under-researched, making it esoteric and difficult to scaffold. This paper aims to provide an articulated and nuanced account of what is involved in student teams’ construction of shared understanding of complex interdisciplinary problems. Methods The study combines the theoretical lens of epistemic games with an ecological analytical perspective. Drawing on the analysis of ethnographic cases, it explores how four graduate student teams construct shared understanding of complex problems during interdisciplinary projects. Findings Construction of shared understanding is a multifaceted and dynamic process that extends over the entire problem-solving activity. It relies on epistemic moves that explicate and juxtapose different perspectives and connect abstract ideas with knowledge grounded in students’ experiences and contexts. The pursuits students engage in, when creating shared understanding, reveal epistemic differences related to formulation of the interdisciplinary problem and what constitutes trustworthy knowledge. Contribution The paper contributes to the literature on the nature of students’ construction of shared understanding of complex interdisciplinary problems revealing critical recurrent moves. It also extends earlier conceptualizations of epistemic games as primarily discourse games and demonstrates that they are profoundly multimodal and distributed.

Variational quantum circuit learning-enabled robust optimization for AI data center energy control and decarbonization

As the demand for artificial intelligence (AI) models and applications continues to grow, data centers that handle AI workloads are experiencing a rise in energy consumption and associated carbon footprint. This work proposes a variational quantum computing-based robust optimization (VQC-RO) framework for control and energy management in large-scale data centers to address the computational challenges and overcome limitations of conventional model-based and model-free strategies. The VQC-RO framework integrates variational quantum circuits (VQCs) with classical optimization to enable efficient and uncertainty-aware control of energy systems in AI data centers. Quantum algorithms executed on noisy intermediate-scale quantum (NISQ) devices are used for value function estimation trained with Q-learning, leading to the formulation of a robust optimization problem with uncertain coefficients. The quantum computing-based robust control strategy is designed to address uncertainties associated with weather conditions and renewable energy generation while optimizing energy consumption in AI data centers. This work also outlines the computational experiments conducted at various AI data center locations in the United States to analyze the reduction in power consumption and carbon emission levels associated with the proposed quantum computing-based robust control framework. This work contributes a novel approach to energy-efficient and sustainable data center operation, promising to reduce carbon emissions and energy consumption in large-scale data centers handling AI workloads by 9.8 % and 12.5 %, respectively.

Numerical Reconstruction of Time-Dependent Boundary Conditions to 2D Heat Equation on Disjoint Rectangles at Integral Observations

In this paper, two-dimensional (2D) heat equations on disjoint rectangles are considered. The solutions are connected by interface Robin’s-type internal conditions. The problem has external Dirichlet boundary conditions that, in the forward (direct) formulation, are given functions. In the inverse problem formulation, the Dirichlet conditions are unknown functions, and the aim is to be reconstructed upon integral observations. Well-posedness both for direct and inverse problems is established. Using the given 2D integrals of the unknown solution on each of the domains and the specific interface boundary conditions, we reduce the 2D inverse problem to a forward heat 1D one. The resulting 1D problem is solved using the explicit Saul’yev finite difference method. Numerical test examples are discussed to illustrate the efficiency of the approach.

Constrained optimal grouping of cloud application components

Cloud applications are built from a set of components often deployed as containers, which can be deployed individually on separate Virtual Machines (VMs) or grouped on a smaller set of VMs. Additionally, the application owner may have inhibition constraints regarding the co-location of components. Finding the best way to deploy an application means finding the best groups of components and the best VMs, and it is not trivial because of the complexity coming from the number of possible options. The problem can be mapped onto may known combinatorial problems as binpacking and knapsack formulations. However, these approaches often assume homogeneus resources and fail to incorporate the inhibition constraints. The main contribution of this paper are firstly a novel formulation of the grouping problem as constrained Coalition Structure Generation (CSG) problem, including the specification of the value function which fulfills the criteria of a Characteristic Function Game (CFG). The CSG problem aims to determine stable and disjoint groups of players collaborating to optimize the joint outcome of the game, and a CFG is a common representation of a CSG, where each group is assigned a value and where the value of the game is the sum of the groups’ contributions. Secondly, the Integer-Partition (IP) CSG algorithm has been modified and extended to handle constraints. The proposed approach is evaluated with the extended IP algorithm, and a novel exhaustive search algorithm establishing the optimum grouping for comparison. The evaluation shows that our approach with the modified algorithm evaluates on average significantly less combinations than the CSG state-of-the-art algorithm. The proposed approach is promising for optimized constrained Cloud application management as the modified IP algorithm can optimally solve constrained grouping problems of attainable sizes.

Basic properties of ferromagnetic vector hysteresis play models and their validation by finite element method

Purpose Magnetic hysteresis holds significant technical and physical importance in the design of electromagnetic components. Despite extensive research in this area, modeling magnetic hysteresis remains a challenging task that is yet to be fully resolved. The purpose of this paper is to study vector hysteresis play models for anisotropic ferromagnetic materials in a physical, thermodynamical approach. Design/methodology/approach In this work, hysteresis play models are implemented to interpret magnetic properties, drawing upon classical rate-independent plasticity principles derived from continuum mechanics theory. By conducting qualitative and quantitative verification and validation, various aspects of ferromagnetic vector hysteresis were thoroughly examined. By directly incorporating the hysteresis play models into the primal formulations using fixed point method, the proposed model is validated with measurements in a finite element (FE) environments. Findings The proposed vector hysteresis play model is verified with fundamental properties of hysteresis effects. Numerical analysis is performed in an FE environment. Measured data from a rotational single sheet tester (RSST) are validated to the simulated results. Originality/value The results of this work demonstrates that the essential properties of the hysteresis effects by electrical steel sheets can be represented by the proposed vector hysteresis play models. By incorporation of hysteresis play models into the weak formulations of the magnetostatic problem in the h-based magnetic scalar potential form, magnetic properties of electrical steel sheets can be locally analyzed and represented.