Dimensional analysis of partial discharge initiated by a metallic particle adhering to the spacer surface in a gas-insulated system

Partial discharges (PDs) constitute important phenomena in a Gas-Insulated System (GIS) that warrant recognition (and, subsequently, mitigation) as they are obvious symptoms of system degradation. This paper proposes the application of dimensional analysis, based on Buckingham pi theorem, for characterizing PDs provoked by the presence of metallic particles adhering to the spacer surface in a GIS employing SF6 (Sulphur hexafluoride). The ultimate goal of the analysis is to formulate the relationships that express three PD indicator quantities, namely current, charge, and energy, in terms of six independent quantities that collectively influence these indicators. These six quantities (henceforth referred to as the influencing, determining or affecting variables) include the level of applied voltage, the SF6 pressure, the length and position of the particle on the spacer, the duration of voltage application, and the gap between electrodes. To compute the pertinent dimensionless products, we implement three computational methods based on matrix operations. These three methods produce exactly the same dimensionless products, which are subsequently used for constructing the models depicting the relationships between each of the three PD dependent quantities and the common six determining variables. The models derived provide partial quantitative information and facilitate qualitative reasoning about the considered phenomenon.

Validation of evaporation-determined model of arc-cathode coupling in the peak current phase in pulsed GMA welding

A first experimental validation of the EDACC (evaporation-determined arc-cathode coupling) model is performend by comparing the experimental and simulated current in the peak current phase of a pulsed GMAW (gas metal arc welding) process. For this, the EDACC model was extended to limit the cathode surface temperature to a realistic value of <2400K. The information on the plasma for the EDACC model was gathered from literature and extrapolated and extended according to qualitative reasoning. The information on the cathode surface of the EDACC model was derived from a steady-state simulation of the weld pool, using an averaging approach over time for the energy and current. The weld pool surface temperature was compared to pyrometric measurements, that were performed for this work, and the agreement was found to be fair. The observed agreement between the modelled and experimentally determined current was within 10%. As strong assumptions were made for the comparison, the validation cannot be considered as final, but the assumptions are thoroughly analyzed and discussed. However the critical link between surface temperature, plasma temperature and total current transmitted could be reconstructed.

Combining quantitative and qualitative reasoning in concurrent multi-player games

We propose a general framework for modelling and formal reasoning about multi-agent systems and, in particular, multi-stage games where both quantitative and qualitative objectives and constraints are involved. Our models enrich concurrent game models with payoffs and guards on actions associated with each state of the model and propose a quantitative extension of the logic $${\textsf {ATL}}^{*}$$ ATL ∗ that enables the combination of quantitative and qualitative reasoning. We illustrate the framework with some detailed examples. Finally, we consider the model-checking problems arising in our framework and establish some general undecidability and decidability results for them.

A modeler's manifesto: Synthesizing modeling best practices with social science frameworks to support critical approaches to data science

In the face of the "crisis of reproducibility" and the rise of "big data" with its associated issues, modeling needs to be practiced more critically and less automatically. Many modelers are discussing better modeling practices, but to address questions about the transparency, equity, and relevance of modeling, we also need the theoretical grounding of social science and the tools of critical theory. I have therefore synthesized recent work by modelers on better practices for modeling with social science literature (especially feminist science and technology studies) to offer a "modeler’s manifesto": a set of applied practices and framings for critical modeling approaches. Broadly, these practices involve 1) giving greater context to scientific modeling through extended methods sections, appendices, and companion articles, clarifying quantitative and qualitative reasoning and process; 2) greater collaboration in scientific modeling via triangulation with different data sources, gaining feedback from interdisciplinary teams, and viewing uncertainty as openness and invitation for dialogue; and 3) directly engaging with justice and ethics by watching for and mitigating unequal power dynamics in projects, facing the impacts and implications of the work throughout the process rather than only afterwards, and seeking opportunities to collaborate directly with people impacted by the modeling.

The transformation framework The role security in the global education system

This article analyses the role of Global Education System (GES) and proposes the Applied Holistic Mathematical Model for GES (AHMM4GES). The AHMM4GES is based on many years of research on business & educational transformations, Artificial Intelligence (AI), applied mathematics, software modelling, business & organizational engineering, skills & educational systems, financial analysis, security and enterprise architecture. The used research methodology is based on the author’s authentic mixed research method that is supported by a mainly qualitative reasoning module. AHMM4GES’s formalism mimics the human brain, by using empirical processes that are based on heuristics. The AHMM4GES is used to implement a decision-making system (or an expert system) to support a GES and uses a behaviour-driven development environment that can be easily adopted by any organization. The development environment can be used by any team member without any prior computer sciences qualifications. The AHMM4GES is used to estimate the Role of AI based Security in GES’s (RAISGES) context and tries to estimate the roles of the giants in this domain, like the USA, China, and India; and what would be the real role of the European Union and France. The uniqueness and originality of this research is that the AHMM4GES promotes a holistic unbundling process, the alignment of transformation strategies to support GES’ evolution. For a successful integration of AHMM4GES in projects, the manager’s profile, education, skills and role are crucial, where his decisions are supported by the selection, implementation and processing of critical success factors. The main implication is a systemic approach that is the optimal to integrate an RAI4GES.

Improved Algorithms for Allen's Interval Algebra: a Dynamic Programming Approach

The constraint satisfaction problem (CSP) is an important framework in artificial intelligence used to model e.g. qualitative reasoning problems such as Allen's interval algebra A. There is strong practical incitement to solve CSPs as efficiently as possible, and the classical complexity of temporal CSPs, including A, is well understood. However, the situation is more dire with respect to running time bounds of the form O(f(n)) (where n is the number of variables) where existing results gives a best theoretical upper bound 2^O(n * log n) which leaves a significant gap to the best (conditional) lower bound 2^o(n). In this paper we narrow this gap by presenting two novel algorithms for temporal CSPs based on dynamic programming. The first algorithm solves temporal CSPs limited to constraints of arity three in O(3^n) time, and we use this algorithm to solve A in O((1.5922n)^n) time. The second algorithm tackles A directly and solves it in O((1.0615n)^n), implying a remarkable improvement over existing methods since no previously published algorithm belongs to O((cn)^n) for any c. We also extend the latter algorithm to higher dimensions box algebras where we obtain the first explicit upper bound.

Development of Effective Artificial Neural Network Model using Sequential Sensitivity Analysis and Randomized Training

As the machine learning algorithms evolve, there is a growing need of how to train the algorithm effectively for the large data with available resources in practically less time. The paper presents an idea of developing an effective model that focuses on the implementation of sequential sensitivity analysis and randomized training approach which can be one solution to this growing need. Many researchers focused on the implementation of sensitivity analysis to eliminate the insignificant features ands reduce the complexity in data selection. These sensitivity analysis methods relatively take a large time for validation through modeling and hence found impractical for large data. On the other hand, the randomized training approach was found to be the most popular approach for training the data but there is a very brief explanation available in research articles on how this training method is meaningful in getting higher accuracy. The current work focuses on the use of sequential sensitivity analysis and randomized training in an artificial neural network (ANN) for high dimensionality thermal power plant data. The sequential sensitivity analysis (SSA) technique includes the use of correlation analysis (CA), Analysis of variance (ANOVA), Akaike information criterion (AIC) in a sequential manner to reduce the validation time for all possible feature combinations. Only selected combinations are then tested against different training methods such as downward extrapolation, upward extrapolation, interpolation and randomized training in ANN. The paper also focuses on suggesting the significance of training with randomized training with comparison-based qualitative reasoning. The statistical parameters, mean square error (RMSE), Mean absolute relative difference (MARD) and R Square (R^2)were accessed for validation purposes. The research work mainly useful in the field of Ecommerce, Finance, industry and in facilities where large data is generated.

The business transformation enterprise architecture framework for innovation The role of artificial intelligence in the global business education (RAIGBE)

This article analyses the role of Global Business Education (GBE) and proposes the Applied Holistic Mathematical Model for GBE (AHMM4GBE). The AHMM4GBE is based on a lifetime long research on business transformations, Artificial Intelligence (AI), applied mathematics, software modelling, business engineering, educational systems, financial analysis, security and enterprise architecture. The used research methodology is based on the author’s authentic mixed research method that is supported by a mainly qualitative reasoning module. AHMM4GBE’s formalism mimics the human brain, by using empirical processes that are mainly based on heuristics. The AHMM4GBE is used to implement a decision-making system (or an expert system) to support a GBE and uses a behaviour-driven development environment that can be easily adopted by any organization. The development environment can be used by any team member without any prior computer sciences qualifications. The AHMM4GBE is used to estimate the Role of AI in GEB’s (RAIGBE) context and tries to estimate the roles of the giants in this domain, like USA, China, and India; and what would be the real role of the European Union and France. The uniqueness of this research is that the AHMM4GBE promotes a holistic unbundling process, the alignment of transformation strategies to support GBE’s evolution. For a successful integration of the AHMM4GBE in projects, the manager’s profile and role are crucial, where his decisions are supported by the selection, implementation and processing of critical success factors. A holistic systemic system approach is the optimal choice to integrate an RAI4GBE.

Curating complexity: the role of sentience in parametric design

In De Architectura, Vitruvius makes note of three criteria that define architecture; firmitas (durability), utilitas (function) and venustas (delight). These ideals form the philosophical foundations of virtually all modern architectural theory. With the advent of computational tools, many advocates, commonly armed with staggering statistics, frame these methods as a means of increasing efficiency in collaboration, construction and performance - muting the critical role of a sentient designer in architectural discourse of the digital age. The role of the parti has eroded in favour of computational strategies that constrain utilitas to a measure of quantifiable “fitness”. The research herein unveils and reflects upon the mutating role of the architect in computational design, advocating for the importance of qualitative reasoning in a parametric process. Where the current paradigm is negligent, the project aims to illuminate and reinforce the role of today’s sentient designer nested in a cultural milieu of computation.