Heuristic Methodology Research Articles

Methane Risk Assessment in Underground Mines by Means of a Survey by the Panel of Experts (Sope)

Purpose The purpose of the paper was to develop a method of methane risk assessment in order to fulfil the technical-organizational and legal requirements for occupational risk assessment in mines. Methane hazard and associated risks of the effects of ignition and/or explosion of methane is one of the most severe natural hazards. Methods Heuristic methodology based on the Delphi approach and a group survey by a panel of experts, which was named SOPE, was used to assess the magnitude of methane risk. The adopted tools for assessing the current state of methane risk factors and their possible accident consequences were targeted surveys, with the participation of experts representing, mainly, engineering-technical personnel of mine ventilation service. The objectivity and independence of the judgment of the experts was checked by determining indicators of the degree of the experts’ unanimity, indicators of their competence as well as indicators of the validity of their evaluations. The subject matter of the study of methane hazard were five longwall are- as of the “A-Z” twin-mine (after the merge of two mines: Mine A and Mine Z), three longwalls operated towards plant A and two longwalls operated towards plant Z. For the assessment of each area of the mine, a Methane Risk Assessment Questionnaire consisting of 4 assessment cards, was used. The cards included four areas of the studied risk factors, i.e. factors shaping the methane hazard (17 factors), the activity of the methane ignition initiators (19 factors), detection and prevention of methane risk (16 factors) and possible human and material losses (13 factors). Result The evaluation of 65 factors affecting the causes and consequences of the methane risk in the exploitation area under analysis, was conducted in accordance with the procedure of the adopted method, based on the proposed algorithm. Assessments by experts were used to calculate the indicators of the magnitude of methane hazard for each group of factors separately. Practical implications A practical example of the application of this method is incorporated in chapter four of this paper, which also discusses the results of the conducted research. Originality/value The obtained values of the indicators of methane risk assessment and analysis of their changes showed that the proposed method can be an important element in the design and construction of a modern methane safety system in coal mines. It provides the possibility of controlling this risk and enables the minimization of its consequences in accordance

Multiple scattering effects for polydisperse scatterers in soft media

We explore the effects of polydispersity in 3D heterogeneous media consisting of scattering species (e.g., droplets, particles) in viscous liquids using a multiple scattering formulation to define effective speed and attenuation spectra. We adopt a published formulation [A. L. Gower, M. J. A. Smith, W. J. Parnell, and I. D. Abrahams, in Proceedings of the Royal Society of America (2018), p. 474] that rigorously extends multiple scattering theory to multi-component systems and show that in the long wavelength region it is consistent with a previous heuristic methodology applied to polydisperse scatterers. We investigate cases of a monomodal size distribution of finite width, and multi-modal size distributions with similar species. Further, systems of mixed scatterer species (i.e., different types of scatterer) with different sizes and distributions are considered. We will discuss the implications for inversion of ultrasonic spectra to determine particle size distributions and for the design of materials with targeted properties by varying composition (concentrations of different scatterer species) and scatterer properties.

Centrality based solution approaches for median-type incomplete hub location problems

Hub location problems are of those main issues which are focused on by researchers from different aspects for the last three decades especially along with the growth of transportation networks in the world. However, several methods developed for addressing hub location problems do not perform well for large-scale networks because of their computational complexity. This study presents heuristic methodologies based on characteristic features which affect the design of incomplete hub networks. The main idea of this methodology is predicated upon the analysis of characteristics of hub locations. In this respect, the focus was placed on centrality measures, which are frequently used in social networks. Capacity constraints were not addressed, and single-allocation hub location problems were analyzed in this study focused on p-median problems which are the most common problems in the literature. Such characteristics of hub locations as the allocation across the distribution network distance and demand quantities were assessed based on centrality measures, and simple heuristic methods were developed. These methods evaluate nodes across distribution networks from diverse aspects such as centrality, distance, flow, and specify the level of importance of nodes to the networks. Candidate hub nodes are divided into sub-sets in terms of the level of importance and are inserted into the original model as constraints, and then the model is solved under these constraints, which are produced based on certain specifications. In order to test the performance of the proposed methods, data sets such as CAB, AP, URAND and TR which were frequently used in the literature were employed. It was ascertained that the proposed methodology provided good quality solutions in a short solution time. Moreover, the proposed method enables the detailed analysis of hub locations across the network and reduce the problem size. That being the case, it offers valuable opportunities in terms of both the quality of solutions and the solution time for p-hub median problems.

Spatial data analysis approach for network-wide consolidation of bus stop locations

Existing studies indicate that ideal spacing between bus stops improves the quality of service, travel time, and other transit service parameters. In this study, a network-wide heuristic methodology is proposed to optimize the number of stops in an existing bus network by eliminating redundant stops along each bus route in the network through an iterative process. It is postulated that ideal stop spacing can substantially lower the operating costs as it can reduce fleet size requirements without affecting the performance of the transit system. The proposed methodology attempts to eliminate undesired stops based on two vital inputs: (1) stop spacing, and (2) passenger boarding, which represent accessibility and travel time/delay. Potentially undesirable stops are eliminated recursively while their corresponding passenger boarding is redistributed across the adjacent stops. The process is repeated until ideal stop locations are identified. Stop location consolidation is evaluated using two performance indicators, i.e., in-vehicle travel time and access distance, which are considered for evaluating the performance of the modified bus network and comparing the total ridership with the existing network to justify the improvements. In other words, the ideal stop spacing is determined based on projected demand (ridership) loss and assessment of the performance indicators. The application of the proposed methodology is demonstrated using the bus network of the City of Regina in Saskatchewan, Canada. The findings of this research are expected to serve as a decision support tool for transit planners by offering additional flexibility to adopt appropriate bus stop spacing for an existing network.

Electric vehicle charging stations’ location in urban transportation networks: A heuristic methodology

Electric vehicle charging stations’ location in urban transportation networks: A heuristic methodology

Novel method for the parameterization of a reliable equivalent circuit model for the precise simulation of a battery cell's electric behavior

This article presents a novel approach to extract the equivalent circuit model parameter from a pulse test. The presented results corroborate that this novel heuristic methodology can very accurately fit the voltage response of the battery, while drastically reducing the dependence of the parametrization on set boundary conditions and initial guess values. The method's robustness is verified by fitting the voltage response of a mock battery model with pre-defined parameters. It could be shown that the suggested method is able to precisely extract the set parameters from the simulated voltage. Furthermore, the model values obtained from the test of a lithium ion battery cell correlate with physical parameter and other investigation methods like the calculation of the distribution of relaxation times (DRT). As a result, an accurate equivalent circuit model of the cell was created. The restriction as to universal validity of the empirical equivalent circuit model was significantly reduced by limiting the voltage of the RC element with highest time constant. Finally, a robust battery cell model with only a minor root-mean-square error of 1.30% was obtained. ResultA new method for the precise parameterization of an equivalent circuit model from pulse tests is presented. The robustness of such equivalent circuit models is increased by limiting the voltage of the RC element with the highest time constant. Overall, a precise, reliable model of a lithium-ion battery cell is created.

Development of the Landslide Susceptibility Map of Attica Region, Greece, Based on the Method of Rock Engineering System

The triggering of slope failures can cause a significant impact on human settlements and infrastructure in cities, coasts, islands and mountains. Therefore, a reliable evaluation of the landslide hazard would help mitigate the effects of such landslides and decrease the relevant risk. The goal of this paper is to develop, for the first time on a regional scale (1:100,000), a landslide susceptibility map for the entire area of the Attica region in Greece. In order to achieve this, a database of slope failures triggered in the Attica Region from 1961 to 2020 was developed and a semi-quantitative heuristic methodology called Rock Engineering System (RES) was applied through an interaction matrix, where ten parameters, selected as controlling factors for the landslide occurrence, were statistically correlated with the spatial distribution of slope failures. The generated model was validated by using historical landslide data, field-verified slope failures and a methodology developed by the Oregon Department of Geology and Mineral Industries, showing a satisfactory correlation between the expected and existing landslide susceptibility level. Having compiled the landslide susceptibility map, studies focusing on landslide risk assessment can be realized in the Attica Region.

Solving a novel designed second order nonlinear Lane–Emden delay differential model using the heuristic techniques

The aim of the present study is to present a new model based on the nonlinear singular second order delay differential equation of Lane–Emden type and numerically solved by using the heuristic technique. Four different examples are presented based on the designed model and numerically solved by using artificial neural networks optimized by the global search, local search methods and their hybrid combinations, respectively, named as genetic algorithm (GA), sequential quadratic programming (SQP) and GA-SQP. The numerical results of the designed model are compared for the proposed heuristic technique with the exact/explicit results that demonstrate the performance and correctness. Moreover, statistical investigations/assessments are presented for the accuracy and performance of the designed model implemented with heuristic methodology.

Extended intelligent Su-Field analysis based on fuzzy inference

Su-Field analysis, as one of TRIZ analytical tool for solving inventive problems, can be used to improve the performance of the technical system effectively. Generally, choosing an appropriate inventive standard is critical to solving inventive problems efficiently and accurately. However, these standards are summarized and categorized based on the enormous amount of patents in different domains, and they are built in the high level of abstraction, independently of the specific application field, making their use require much more technical knowledge than other TRIZ tools. In order to facilitate the use of inventive standards, especially for capturing the uncertainty or imprecision depicted in the standards, a rule-based heuristic methodology is proposed in this paper. Firstly, Su-Field analysis ontology and fuzzy analysis ontology are built to represent the precise and fuzzy knowledge in the process of solving inventive problems respectively. Then, SWRL (Semantic Web Rule Language) inference and fuzzy inference are performed for generating heuristic concept solution. Finally, a prototype is developed and the resolution of the case of the “Auguste Piccard’s Stratostat” in prototype is elaborated in detail.

Extended Model Predictive Controller to Develop Energy Management Systems in Renewable Source-Based Smart Microgrids with Hydrogen as Backup. Theoretical Foundation and Case Study

This article presents a methodological foundation to design and experimentally test a Model Predictive Controller (MPC) to be applied in renewable source-based microgrids with hydrogen as backup. The Model Predictive Controller has been developed with the aim to guarantee the best energy distribution while the microgrid operation is optimized considering both technical and economic parameters. As a differentiating element, this proposal provides a solution to the problem of energy management in real systems, addressing technological challenges such as charge management in topologies with direct battery connection, or loss of performance associated with equipment degradation or the required dynamics in the operation of hydrogen systems. That is, the proposed Model Predictive Controller achieves the optimization of microgrid operation both in the short and in the long-term basis. For this purpose, a generalized multi-objective function has been defined that considers the energy demand, operating costs, system performance as well as the suffered and accumulated degradation by microgrid elements throughout their lifespan. The generality in the definition of the model and cost function, allows multi-objective optimization problems to be raised depending on the application, topology or design criteria to be considered. For this purpose, a heuristic methodology based on artificial intelligence techniques is presented for the tuning of the controller parameters. The Model Predictive Controller has been validated by simulation and experimental tests in a case study, where the performance of the microgrid under energy excess and deficit situations has been tested, considering the constrains defined by the degradation of the systems that make up the microgrid. The designed controller always made it possible to guarantee both the power balance and the optimal energy distribution between systems according to the predefined priority and accumulated degradation, while guaranteeing the maximum operating voltage of the system with a margin of error less than 1%. The simulation and experimental results for the case study showed the validity of the controller and the design methodology used.

O Peer, Where Art Thou? Uncovering Remote Peering Interconnections at IXPs

Internet eXchange Points (IXPs) are Internet hubs that mainly provide the switching infrastructure to interconnect networks and exchange traffic. While the initial goal of IXPs was to bring together networks residing in the same city or country, and thus keep local traffic local, this model is gradually shifting. Many networks connect to IXPs without having physical presence at their switching infrastructure. This practice, called Remote Peering, is changing the Internet topology and economy, and has become the subject of a contentious debate within the network operators' community. However, despite the increasing attention it attracts, the understanding of the characteristics and impact of remote peering is limited. In this work, we introduce and validate a heuristic methodology for discovering remote peers at IXPs. We (i) identify critical remote peering inference challenges, (ii) infer remote peers with high accuracy (>97%) and coverage (94%) per IXP, and (iii) characterize different aspects of the remote peering ecosystem by applying our methodology to 30 large IXPs. We observe that remote peering is a significantly common practice in all the studied IXPs; for the largest IXPs, remote peers account for 40% of their member base. We also show that today, IXP growth is mainly driven by remote peering, which contributes two times more than local peering.

Optimal Design of Isolated Mini-Grids with Deterministic Methods: Matching Predictive Operating Strategies with Low Computational Requirements

The lack of electricity access is increasingly concentrated in rural areas of developing countries, in which mini-grids are often a suitable solution; however, given the high risks, it is crucial to minimize costs. This paper aims at analyzing existing methodologies for the optimal design of mini-grids combined with different operating strategies. Typical system operations, like the load-following (LFS) and cycle charging (CCS) strategies, are compared with the more demanding predictive strategies based on Mixed-Integer Linear Programming (MILP). The problem is formulated and solved with Particle Swarm Optimization (PSO), so to simulate traditional and predictive operating strategies. Two reformulations based on the proposed Search Space Update are also detailed and compared with the so-called one-shot MILP model, which is able to con-jointly optimize both the design and the operation of the system, in order to reduce computational requirements with the predictive strategy. The results, tailored with data from a rural mini-grid in Kenya, highlight that heuristic methodologies can perform better than the traditional MILP approach, both in terms of optimality and computational time, especially when advanced operating strategies are considered. Conventional operating strategies (LFS or CCS) appear to be sub-optimal, but require very little computational requirements, which makes them suitable for preliminary designs.

Spontaneous Transformation and Recovery From Problematic Eating: A Heuristic Inquiry

Health care professionals agree that there are countless individuals with problematic eating habits that detract from health and well-being but do not directly meet the criteria for diagnosis of disorder. Previous research identifies that problematic eating patterns are notoriously challenging to address and that positive changes in behavior are difficult to maintain. This qualitative study contributes to the literature identifying potential mechanisms for transformative and lasting change for individuals exhibiting problematic eating patterns. Utilizing heuristic methodology, the lived experience of spontaneous transformation as a mechanism of change in the development of, and recovery from, problematic eating habits was illuminated and explored by the primary researcher, SS, and six female coresearchers. The data for this study were obtained through in-depth, informal conversational interviews. Heuristic analysis of the data revealed six core themes relevant to the experience of the phenomenon of spontaneous transformation and the recovery from problematic eating habits: (a) early messaging in environment of origin, (b) moments of suffering as gateways to change, (c) perceived loss of control, (d) implicit awareness resulting in transformation, (e) physical expressions of expansion and constriction, (f) and the necessity for a new definition of recovery. The findings of this study point toward the experience of spontaneous transformation as a mechanism for enhanced self-awareness and potential for generating transformational change in patterns of problematic eating.

Integrating storage and spatial variability into shallow groundwater balances: moving towards water security in hard rock coastal areas

Abstract In terrains with limited soil cover and groundwater storage, groundwater resource management is governed by the spatial nature of storage, recharge and distributed local extraction. Local soils act as important groundwater reservoirs for residents who have no other feasible water supply. A novel heuristic methodology is presented which accounts for the spatial distribution of storage and extraction, using existing topographical and geological databases in addition to well data to construct an applied conceptual groundwater model with assumed stratigraphy. The method uses a geographic information systems (GIS) environment and allows for modelling climate and land-use scenarios. Several scenarios were examined, demonstrating that average reservoir volumes meet demand but at the local levels depletion of reservoirs occurs. Groundwater abstraction in excess of 50% of the approximate freshwater storage was observed in the model, particularly near the coast. Soil-filled valleys may act as local hydraulic barriers by maintaining a higher pressure head as they are less susceptible to large-level fluctuations than the hard rock and may aid in preventing contamination from saline water provided no direct hydraulic connection is present. The method demonstrates the importance of a spatial approach in managing groundwater resources and could be used as a tool in increasing water security.

A Heuristic Methodology for Optimal Deployment of Radar Systems in a Constrained Area of Operation

In emerging network-centric warfare scenarios, the location of sensors in the sensor-grid plays a dominant role in determining the effectiveness of air defence against enemy air threats. Maximising the coverage area of sensors in the sensor-grid, considering operational performance parameters, terrain features and deployability is a challenging task for military operational planners and commanders. Such optimisation problems may not be amenable to classical operations research techniques, or may require enormous computational time to arrive at the results as the decision space grows non-linearly for large areas of operation. In this paper, a novel methodology that uses a heuristic technique (genetic algorithms) to compute the optimal or near-optimal deployment locations for a given set of sensors in a constrained area of operation is proposed. The proposed methodology is illustrated with a number of case studies and a decision support tool is developed as an aid to the military commanders.

Is teaching work? A heuristic study of the views of teachers.

Teachers can be at risk of exposure to psychosocial hazards. Improving workplace safety for teachers, within a 'systems thinking' context, should begin with understanding the work. While much is known about what teachers do, little is known about how teachers conceptualize 'work'. Knowing how teachers conceptualize 'work' provides a reference point for exploring attitudes towards work health and safety. The paper presents a review of the literature, an overview of heuristic methodology describing and interpreting the lived experience of teachers as workers, and analysis of teachers' accounts of work. The heuristic approach allowed the author to compare their lived experiences and perceptions as a teacher with the lived experience of teachers in the NSW school system. Teaching is work that is both rewarding and hazardous. It is argued that teachers draw on battle motifs, perceive a need for safety within a workplace context, and have an ability to conduct personal risk assessments. Findings from the study provided direction for the second phase of the project that is aimed at exploring the ways in which teachers conceptualize psychosocial work- related hazards and the extent to which they are visible in teaching practice and policy.

Mathematical model and heuristics for maximizing reliability of parallel systems with alternatives and budget constraints

Reliability is defined as the ability to perform a given function over a period of time in a particular environment. Designing problem of the system structure appears in many industries, and various reliability optimization issues arise. Especially in military defence area, it is very important to achieve maximum reliability under a given budget. In this study, maximum reliability optimization problem in parallel system, each component has several alternatives, and limited budget reliability optimization problem is considered. Objective function of the problem is expressed as a nonlinear function because it is a reliability of a parallel system. Therefore, it is generally known as difficult to obtain a global optimal solution. In this paper, we propose a heuristic methodology that solves the problem by using Combinatorial Bender's Cut. The results of experiments proved that the proposed algorithm showed good performance in terms of value of the obtained reliability and consumed CPU time. Keywords : parallel system, reliability, nonlinear programming, heuristic DOI: 10.7176/IEL/10-2-07 Publication date: April 30 th 2020

A Qualitative Heuristic Inquiry into the Development of Therapeutic Presence as a Student Music Therapist

This first-person study investigates the role of cognitive and embodied forms of knowledge in relation to the development of therapeutic presence as a student music therapist. In this paper, I will provide an introduction to the topic reviewing its relevance to the practice of music therapy, and I will argue that the development of therapeutic presence is a fundamental part of becoming a music therapist. Although there are seminal articles in the music therapy literature that discuss the topic of therapeutic presence, I have not found any articles relating it to the development of being a student music therapist. Using heuristic methodology, I will describe the personal process of developing therapeutic presence as a student music therapist. To gain a broader perspective on the research topic, and to provide validation and transparency in relation to my personal heuristic process, three successive theoretical and experiential workshops were carried out with six student music therapists. Data, in the form of questionnaires, reflections and group musical improvisations were analysed systematically to validate my experience of the research topic, and also to discover and evaluate themes and practical methods. The research has culminated in the synthesis of data gathered during the study in relation to the main research question while also reviewing its relevance to music therapy practice and implications for further study.

Gateways for Transformation

Big life transitions, typically resulting from loss, can cause physical, emotional, and behavioral problems. Using a heuristic methodology, this article answers the question: Given polyvagal theory, how can yoga and depth psychology combine to support clients to make transitions more easily? Polyvagal theory hypothesizes that the vagus nerve, the longest cranial nerve, impacts impact many parts of the body related to physical and mental health. Breathing helps the vagus nerve function properly along with self-regulation, homeostasis, and the social engagement system. Yoga and depth psychology recognize the continuous cycles of life that exist in nature, the constancy of change, the aspects of the person that are unchanging, and the ability of both client and therapist to witness it all. To demonstrate the utility of combining yoga and depth psychology to heal the pain of transitions, a therapeutic program was developed and depicted graphically.

Application of the neutrosophic system to tax havens with a criminal approach

The investigation questions transparency (legitimacy) on the one hand and tax evasion (illegality) at tax haven on the other, so this paper the highlights importance of tax havens, either to the detriment of economies suffering from significant capital flight or to the benefit of jurisdictions declared as paradises, whose economy had been favored by the inflow of capital and investment Foreign. Tax havens are mechanisms of defense of wealthy taxpayers who seek to escape with their wealth from state taxes with progressive tax systems for the financing of social protection, education, and security of their population. Much of the study had to be based on the analysis of the information collected to clarify its importance with the support of neutrosophic numbers for the determination of fuzzy sets for a better understanding of the phenomenon under study inserted in tax havens. Besides, the heuristic evaluation methodology was used, as a form of financial investment with neutrosophic representation, since it allowed the search for qualitative results that helped to emphasize investment problems in those States, territories or jurisdictions that do not have taxation, profits, or apply it at very low rates, with serious limitations in the exchange of information (bank secrecy) and a marked absence of transparency. As the main conclusion, it was argued that governments should continue their transparency campaigns to prevent the continued use of money of public origin as a consequence of illegal acts, without affecting the sovereignty of each country.