Definition Of Constraints Research Articles

ORSO: The Organizational Structure Ontology

ABSTRACT Organizational structure information is deeply embedded in the different functional activities of accounting. This paper presents ORSO (ORganizational Structure Ontology), an ontology for describing organizational structures that can be reasoned with as part of accounting applications, developed following the principles and guidelines of design science research. ORSO allows the representation of key organizational constructs to meet internal and external accounting needs, including financial reporting requirements, analysis of an organization’s governance structure, economic analysis of agent and group performance, the definition and monitoring of controls, and responding to political and social inquiries about agents and other needs. A prototype is presented that demonstrates three possible types of applications of ORSO systems: (1) analysis of organizational structures, (2) accounting analysis through the integrated use of Resource-Event-Agent (REA) transaction data and ORSO specifications, and (3) constraint definition and monitoring. Data Availability: Additional information is available from the authors. JEL Classifications: M4.

Approach Uses Multidisciplinary Constraints for Automatic Well-Path Generation

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215021, “A New Paradigm for Automatic Well-Path Generation Using Multidisciplinary Constraints,” by Eric Cayeux, SPE, Gilles Pelfrene, SPE, and Rodica G. Mihai, SPE, NORCE, et al. The paper has not been peer reviewed. _ Because of the multidisciplinary nature of the well-planning process, many iterations are necessary to generate a well path. This is a time-consuming process that finally leads to planned trajectories that may be suboptimal. Departing from the traditional incremental approach to well-path generation, the method proposed in the complete paper relies on the collection of experienced-based constraints from each discipline to generate possible alternatives to the well path. As a result of this new process, the multidisciplinary team can focus on the relevance of the constraints rather than on the details of the planned trajectory. Constraint-Based Well-Path Design To better capture the decisions during the well-path-planning process and their motivation, a constraint-based design is proposed. Typical constraints that can be included in such an approach are geological, geomechanical, operational, economic, time-related, technical, social, and environmental. The complete paper focuses on geometrical constraints and aspects related to their influence on well-path design. Target and Target-Group Constraints Definition. A target is a complex concept with no standard definition across the industry or within companies themselves. In the proposed approach, the target is defined as a set of geometrical constraints to be met, each referring to a target body. It differs from the standard approach in that it does not discriminate between target bodies to reach (such as points or target axes), which can be called attractors, and those to avoid (such as faults or vertical walls of lease lines), which can be called repellors. The distinction is particularly relevant when the well-path-generation algorithm can process the set of constraints globally, thus providing an ensemble of solutions that inherently meet all constraints.

Optimizing Room Temperature Control: A Comparative Analysis of Deep Reinforcement Learning and Contextual Bayesian Optimization Methods

Building temperature control presents significant modeling challenges due to the complexity of internal systems and varied usage patterns. Consequently, black box modeling has become a prevalent approach in this domain. This technique broadly encompasses deep learning and Bayesian optimization methods, each offering unique mechanisms for deriving optimal control parameters. Deep learning methods iteratively refine control parameters using extensive datasets, whereas Bayesian optimization employs Gaussian process regression and acquisition functions to pinpoint optimal solutions. This paper conducts a comparative analysis of two innovative methods within these branches: the application of Deep Reinforcement Learning (DRL) for integrated control of household temperature and electric vehicle charging, and the Primal-Dual Contextual Bayesian Optimization (PDCBO) method for adaptive thermal control in buildings. The study reveals that the DRL approach, integrated with electric vehicle charging systems, excels in responsiveness and reducing energy consumption. In contrast, the PDCBO method enhances control by allowing for the artificial definition and continuous optimization of constraints on energy usage and comfort during the operation, facilitated by algorithmic design. By synthesizing the strengths of both methods and considering electric vehicle integration and tailored adaptive control constraints, enhanced outcomes are achievable. This paper proposes that specific control strategies be developed for different building types to address diverse real-world requirements effectively.

Shallow groundwater and river baseflow: Interconnection evidences and integrated water management strategies. Case study in the upper Descoberto watershed, Federal District, Brazil

Aquifer discharge in the form of baseflow is intimate related to river replenishment. In this manner, it is reasonable that water management practices consider an integrated approach including surface and groundwater. Effective regulatory measures, however, require the understanding of the mechanisms and the degree of such interconnection. In the Federal District, capital of Brazil, research focused on this theme are scarce, despite the relevance addressed by some authors. In the present study, shallow groundwater of Upper Descoberto Watershed was monitored for four years (2019–2023). The area responds to 60% of local population public water supply and has been facing land use conflicts and water crisis. Data were collected with 2-h resolution and compared to fluviometric stations discharge and water height records. Graphical analyses demonstrate that river baseflow is highly dependent on shallow aquifer discharge. The decrease of the phreatic aquifer water level results, in a short period, in streams flow reduction. This result is contrasting to the former agreement that considered the connection would take more time to be established. Statistical correlation coefficients are as high as 0.920 for the entire monitoring range and 0.998 for the dry season. The results evidence that soils have important reservoir and regulatory functions, even though they might not be relevant for high water demand activities. In this way, water grant process should account for correlated components, such as territory planning, estimation of total extraction by sensitive areas and properly characterization of insignificant uses, alternative and independent water sources evaluation, and definition of environmental constraints. The mitigation practices of hydric problems must include the implementation of artificial recharge devices, use of sustainable farming methods and control of rainwater overland flow. It is desirable the maintenance and enlargement of the current monitoring net so that former patterns that culminated in water crisis can be early identified and mitigated.

Robust wind farm layout optimization

Wake interactions in wind farms cause losses in annual energy production (AEP) on the order of 10%. Wind farm designers optimize the layout of the farm to mitigate wake losses, especially in the dominant site-specific wind directions. As wind turbines and wind farms grow in scale, optimization becomes more complex. Offshore wind farms regularly comprise more than 100 wind turbines and are characterized by complex boundaries due to shipping lanes, neighboring wind farms, and other constraints.Layout optimization methods are broadly split between gradient-based and gradient-free approaches. Gradient-based approaches can converge quickly and perform well for smaller, academic problems but are often sensitive to initial conditions and tuning parameters and require expert knowledge to use. On the other hand, gradient-free approaches can be more robust to problem complexities. We present a robust layout optimization approach based on a random search algorithm. The algorithm is intended for those who are not optimization experts and has few tuning parameters that need specification to achieve satisfactory results. Unlike off-the-shelf methods, which use generally available, non-domain-specific optimization routines that accept as inputs an optimization function and constraint definitions, this approach takes advantage of the relative computational costs of the different evaluations by evaluating cheaper computations first (boundary and minimum distance constraints) and running expensive AEP evaluations only if all other checks pass. Moreover, an outer genetic algorithm allows multiple solutions to evolve in parallel, enabling rapid solution development on high-performance computers. We discuss the relative ease of selecting necessary tuning parameters and demonstrate the efficacy of the genetic random search on a complex layout problem consisting of placing 70 turbines in a nonconvex and unconnected boundary region.

Coupled funnel control for supersonic tailless aerial vehicle on penetrating counter air

Supersonic Tailless Aerial Vehicles (STAVs) will become an essential force in Penetrating Counter Air (PCA), but STAVs do not have the traditional horizontal and vertical tails, making pitch and yaw control difficult. The attack angle and the sideslip angle need to be limited to ensure that the engine inlet and the aerodynamic rudder at the rear of the vehicle can work properly, which is the so-called security constraints. In addition, the tracking error of the aerodynamic angle needs to be limited to achieve effective attitude control or high-accuracy tracking of trajectories, which is the so-called performance constraints. To this end, an attitude control method that meets the needs of PCA has been devised, based on constraint definition, coupled constraints handling, and control law design. Firstly, mathematical descriptions of the security constraints, performance constraints, and control constraints are given. Secondly, two treatment methods, coupled command filter and coupled funnel control are proposed for the aerodynamic angle coupled constraint problem. Finally, based on Nonlinear Dynamic Inverse (NDI) design, the coupled funnel controller is designed and validated by simulation for two typical mission scenarios, high-altitude penetration and low-altitude surprise defence. The proposed control method not only satisfies the security and performance constraints of STAV attitude control but also is highly robust.

Application of AI for modelling and structural analysis of a parametric 2D frame with voice assistant

Structural calculations are essential for civil engineering, but specialized software for their analysis is limited. The lack of availability of efficient tools has generated the need to explore new ways to optimize these calculations. This work addresses the aforementioned problem, proposing the use of Python and automation technologies to offer an innovative and accessible solution to improve efficiency in the field of structural analysis of 2D frames. This proposal seeks to reduce work times by relying on AI, as well as to promote accessibility in this field. To achieve this purpose, the Python library AnaStruct, specifically designed for structural analysis using matrix methods, is used. This tool enables the detailed definition of structural elements, constraints and loads, as well as the visualization of the analysis results. In addition, the Speech Recognition library is implemented for interaction through voice reception, which speeds up the data entry process and structural analysis commands. Through surveys conducted, it is observed that the program achieved an average reduction of the analysis time between 73.33% and 94.29%, compared to traditional methods. Where 100% of the respondents unanimously confirmed that it improves efficiency, and 78.6% expressed their willingness to recommend it for future projects.

A study on aerodynamics of Ultra-efficient cars

Ultra-efficient cars (i.e. Formula One racing cars) are loaded with many different aerodynamic components. They interact to produce highly nonlinear flows, which have a very complex effect on the airflow around the racing car. Clearing up fluid phenomena makes it possible to optimize aerodynamic components effectively. This paper reviews the aerodynamic performance of currently used shapes, as well as the definition of the design constraints for the vehicle. The designs are inspired by formula one cars, especially by Honda F1 Team, but they are adjusted according to the limit conditions of CFD simulation software Ansys CFX, and parameters are scaled accordingly based on the space requirements of this test. A level of velocity at 40 km/h is tested, giving ideas of the full model performance. Results are then compared and discussed to obtain a comprehensive and valid conclusion about the potential improvement in the aerodynamics of road cars, which can be extracted from those ultra-efficient ones.

Compressed air energy storage with T100 microturbines: Dynamic analysis and operational constraints

The aim of this paper is the dynamic analysis of a small-size second-generation Compressed Air Energy Storage (CAES) system. It consists of a recuperated T100 micro gas turbine, an intercooled two-stage reciprocating compressor and an artificial tank for air storage. The possibility of including an innovative air expander before the injection into the turbine is also investigated. Starting from background on design and management optimization, this work proposes dynamic simulations and definition of operational constraints, not considered in previous publications. These represent significant results to extend the system range (producing efficiency and cost benefits), avoiding risks and failures in prototypes as well as in commercial applications. Following a section with calculations motivating the activity from an economic point of view, the interaction of the T100 integrated with the CAES system is analysed through a validated dynamic model. Close attention is paid to the discharging of the air storage vessel because the increment of mass flow at the turbine expander can lead to surge margin decrease and thermal stresses, especially during dynamic operations. Consequently, maximum limits for the air injection are obtained and different operational strategies are considered to ensure safe operation during the system dynamics, enlarging the application range or proposing modifications in the control system.

Modified Active Disturbance Rejection Predictive Control: A fixed-order state–space formulation for SISO systems

This paper presents a novel control strategy that provides active disturbance rejection predictive control on constrained systems with no nominal identified model. The proposed loop relaxes the modelling requirement to a fixed discrete-time state–space realisation of a first-order plus integrator plant despite the nature of the controlled process. A third-order discrete Extended State Observer (ESO) estimates the model mismatch and assumed plant states. Moreover, the constraints handling is tackled by incorporating the compensation term related to the total perturbation in the definition of the optimisation problem constraints. The proposal merges in a new way state–space Model Predictive Control (MPC) and Active Disturbance Rejection Control (ADRC) into an architecture suitable for the servo-regulatory operation of linear and non-linear systems, as shown through validation examples.

Fully integrated construction planning

The full and efficient integration of the various aspects and actors involved in construction planning is still lacking in practice, despite having been the subject of research for decades, and the potential of advanced modeling technologies. This study investigates whether the integration of different aspects of construction planning could be applied in practice through a straightforward and structured process, consisting of a series of steps, that supports the clear definition of goals, relevant parameters, and constraints, based on readily available data. The process is based on a modular approach that will allow integrated project information models to be reconfigured at the time they are required. It is implemented through a platform for integrated construction planning that can be easily applied in practice by the project team and does not require the development of a single dedicated software program. This ensures its flexibility and allows its expansion to include additional aspects.

Planning third generation minigrids: Multi-objective optimization and brownfield investment approaches in modelling village-scale on-grid and off-grid energy systems

Access to reliable and sustainable electricity is still precluded for a large share of global population living in rural areas of developing countries, especially in sub-Saharan Africa. Hybrid microgrids are considered a suitable solution for providing affordable and reliable access to electricity to isolated communities. Properly planning and sizing such systems is although an aspect that can greatly influence the sustainability of the intervention, and the arrival to the market of the third generation minigrids poses new challenges to the process. Three main challenges are identified as pivotal for the proper sizing of new generation microgrids: arrival of the main grid, inappropriateness of Net Present Cost as only objective function in the strategy selection process, and necessity to operate on already existing minigrids. Such aspects are addressed in this work by proposing a methodological advancement to an existing open-source microgrid sizing model: a grid outage model alongside the definition of new constraints and variables for the optimization problem with grid-connected microgrids, a multi-objective optimization option, and a brown-field optimization option. The new version of the model is tested on real life case studies in rural Rwanda (greenfield) and Mozambique (brownfield), proving the profitability of grid-connected and grid-extension solutions for sufficiently low connection distances. Sensitivity analyses are performed to assess variations in system size, cost and CO2 emissions with respect to microgrid and grid connection parameters.

Earnings Management Behavior of Firms with Financial Constraints: Focusing on Firms that Issue Redeemable Convertible Preferred Stocks

Purpose: T his study aim s to e xplore t he e ffect of f inancial c onstraints o n earnings m anagement by f ocusing on firms that issue redeemable convertible preferred stocks (RCPS). RCPS are considered a financing option primarily used by firms that have investment opportunities but face difficulties in raising funds with a low cost of capital. Therefore, the issuance of RCPS can be an effective indicator to identify firms with financial constraints. Design/methodology/approach: This study employs a sample of 12,406 firm-year observations of listed companies in the Korean stock market from 2011 to 2018. The study conducts multiple regression analyses to investigate the level of earnings management of RCPS-issuing firms with respect to that of non-issuing firms. In this analysis, the earnings management is proxied by discretionary accruals and real operational activities. Findings: This study shows that RCPS-issuing firms have a higher level of discretionary accruals than non-issuing firms. Meanwhile, there is no significant difference in the level of real activities management between RCPS-issuing and non-issuing firms. These findings imply that firms with financial constraints engage in aggressive earnings management through discretionary accruals rather than real operational activities. Research limitations/implications: This study provides compelling evidence that financially constrained firms strategically use discretionary accruals to signal positive prospects for external capital suppliers, allowing them to raise the capital necessary for investment. It is also confirmed that financially constrained firms do not depend on real activities management, which sacrifices cash flows and firm value in the long run. Originality/value: T his is t he f irst s tudy t o test t he l ink between f inancial c onstraints a nd e arnings m anagement by analyzing RCPS-issuing firms that conform to the definition of financial constraints. This approach can alleviate the risk of errors in the classification of firms and the endogeneity problems accompanied by estimating financially constrained firms with firm characteristics, such as dividend payout ratio, cash flows, size, age, or a combined index of these variables.

Validation of SST-SCM correlation-based transition model by the simulation of wall-bounded flows

A modified correlation-based transition model coupled with SST turbulence model(k−ω−γ−R˜eθt) is proposed in this work. For better verification of intermittency, the constraint definition strictly based on local variables is cited to ensure physical solution. In order to obtain more details of laminar and transition boundary layer for separation-induced transition, a local correction method based on streamline curvature modification (SCM) has been developed to extend model ability in predicting adverse-pressure-gradient flows. The mean strain rate involved with mean rotation rate and shear rate is modified according to wall-bounded condition with rotation and non-rotation features to preserve the anisotropic characteristics encountered in large range flows. Furthermore, separation-induced intermittency is corrected by considering the effect of average strain rate to prevent outliers in local intermittency whenever the laminar boundary layer separates. Considering that results of test cases simulation with different empirical correlations vary huge from each other, all cases are matched with its suitable empirical correlations to ensure the stability and accuracy calculated by proposed model. Transitional flat-plate cases are calculated to validate the basic ability for near-wall flow simulation.Massive separated flow over two-dimensional circular cylinder has been studied to verify the predicted accuracy for non-equilibrium flows. Flow over multi-element airfoil 30P30N and the simulation of vortex system over three-dimensional Low Pressure Turbine(LPT) cascade T106A are given to examine the predictions of Reynolds shear stress profiles and pressure distribution with flow disturbance; reasonable results show a good match between experimental data and calculation by proposed model.

Constraint definition at a crack tip for the strip yield model

Constraint definition at a crack tip for the strip yield model

Gaps and Challenges in the Implementation of the International, Sub-regional and National Mechanisms for Cooperation and Referral of Trafficking in Persons (TIP) Victims: The Case of Ghana

Trafficking in Persons (TIP) is globally widespread. On the African continent, however, it is prevalent in West and Central Africa. Human traffickers often take advantage of the lax security conditions to conduct and perpetuate human trafficking. In recent times, there have been attempts to end TIP by implementing international, sub-regional and national mechanisms for cooperation and referral of TIP victims. These efforts are, however, fraught with challenges. This paper examines the institutional challenges of implementing international, sub-regional and national mechanisms for cooperation and referral of Trafficking in Persons (TIP) victims. Drawing on the concept of institutional collaboration, we explore the gaps and challenges in the implementation of these mechanisms. This study found that the major challenges and gaps faced by institutions working to implement mechanisms for cooperation include disparities in definition of terminologies, financial and logistical constraints, underutilisation of online reporting systems, inadequate partner collaborations, a gap in the development of operational guidelines and the drafting of training manuals, operational challenges and high staff turnover. Despite these challenges, we conclude that there has been significant improvement in coordination activities in Ghana among the various institutional actors, led by the Human Trafficking Secretariat. The relevance of this study lies in the fact that it allows for a critical mapping and appreciation of the challenges developing countries face in tackling TIP, which then gives meaning to Global Northern-prescribed international ranking systems (the tier system) which are otherwise meaningless within the Global Southern context.

A Tool-Assisted Approach for User-Friendly Definition of FB Constraints

Model-based software engineering is a promising approach for controlling complex automation systems. Automation engineers, unfortunately, do not routinely model the expected behavior, especially if they are not trained in software engineering. They rather focus only on the implementation. In this paper, we analyze potential causes for the low adoption of service sequences within IEC 61499, which define behavioral constraints for building blocks of control applications. We propose a methodology for mining constraints of software components, which are then classified by an engineer. Furthermore, we suggest extending the language to allow for forbidden and mandatory scenarios. Our approach facilitates the constraint definition for legacy software, where the effort of manual specification is extremely high. Tool support for all described extensions and modeling techniques is provided as part of the open source IDE Eclipse 4diac to facilitate applying the approach in practice.

Constraint Definition for Gripper Selection and Grasp Planning for Robotic Assembly Using Product Manufacturing Information from STEP AP242Ed2 Files

This article uses the Product Manufacturing Information (PMI) from STEP AP242 neutral files for gripper selection and grasp planning in a robotic assembly operation. The PMI, along with the part geometry and dimensions, are used in identifying various handling features of the parts and selecting an appropriate gripper. The required PMI, like material, volume, surface finish, threading and coating information, are added to the STEP AP242 files. The PMI is semantically included in the STEP files following the Model Based Definition (MBD) methodology. Two methods are described to add the PMI to the STEP files, one using a custom string and another using the standard entities defined in ISO 10303 AP242: 2020 standard. The entire process is demonstrated in a use case.

Open Named Entity Modeling From Embedding Distribution

In this paper, we report our discovery on named entity distribution in a general word embedding space, which helps an open definition on multilingual named entity definition rather than previous closed and constraint definition on named entities through a named entity dictionary, which is usually derived from human labor and replies on schedule update. Our initial visualization of monolingual word embeddings indicates named entities tend to gather together despite of named entity types and language difference, which enable us to model all named entities using a specific geometric structure inside embedding space, namely, the named entity hypersphere. For monolingual cases, the proposed named entity model gives an open description of diverse named entity types and different languages. For cross-lingual cases, mapping the proposed named entity model provides a novel way to build a named entity dataset for resource-poor languages. At last, the proposed named entity model may be shown as a handy clue to enhance state-of-the-art named entity recognition systems generally.

Command filter based adaptive DSC of uncertain stochastic nonlinear systems with input delay and state constraints

In this paper, a command filter based dynamic surface control (DSC) is developed for stochastic nonlinear systems with input delay, stochastic unmodeled dynamics and full state constraints. An error compensation system is designed to constrain the filtering error caused by the first-order filter in the traditional dynamic surface design. On this basis, the stability proof of DSC for stochastic nonlinear systems based on command filter is proposed. The definition of state constraints in probability is presented, and the problem of stochastic full state constraints is solved by constructing a group of coordinate transformations with nonlinear mappings. The Pade approximation is adopted to deal with input delay. The stochastic unmodeled dynamics is considered, which is processed by utilizing the property of stochastic input-to-state stability (SISS) and changing supply function. All the signals of the system are proved to be semi-globally uniformly ultimately bounded (SGUUB) in probability, and the full state constraints are not violated. The two simulation examples also verify the effectiveness of the proposed adaptive DSC scheme.