Review of Water Network Analysis and Validation of SCALER Hydraulic Simulator

The article intends to present the validation stage of a software to model and simulate hydraulic networks for water distribution, the SCALER, through its application to a real system, with many branches, with a model previously developed and verified using the EPANET software. SCALER was developed in 2020 and 2021 and, until then, had only been applied to networks with a relatively small number of branches. After discussing topics related to hydraulic modeling of distribution networks, techniques and applications, a brief review of the fundamentals of SCALER is carried out, passing on to its application to the case at hand, which is the Vila Joaniza community, in the municipality of Rio de Janeiro. Data from image, scheme and table are used to assist in the description of the local situation and respective distribution network, with the objective of assessing whether the nodal pressures obtained by SCALER are sufficiently similar to those obtained by EPANET, in order to ensure the proper functioning of the software. After this step, and the calculations have been made by the program, an operation screen, the generated graph of the local situation and a table with the comparison of absolute and percentage deviations between the nodal pressures resulting from the SCALER and those obtained with the EPANET are inserted, confirming that the deviation values are quite small, which validates SCALER as a software also applicable to networks with many branches.

Production batch sizing and inventory level control using simulation software

Computer simulation has great application potential in the area of Production Engineering as a tool to support decision making as it allows to simulate the functioning of a real system through logical relationships, in order to observe its behavior under different scenarios. Which could not be practiced in the real system. In line with this aspect, the present work aims to present a report on the application of simulation for the design of production batches and inventory control, highlighting the process necessary for the construction of the generated simulation model, as well as the challenges and opportunities observed. In order to achieve the proposed objective, a literature review was carried out on the topics of interest; the choice and understanding of simulation software and; the survey of data from a large auto parts manufacturer located in the interior of the state of São Paulo. The main results were an increase in production volume from the inclusion and dimensioning of a buffer after the assembly process and a balance between the number of items of each component of the product structure in the supply with the real capacity of manufacturing cell processing. Cabe ressaltar que o modelo de simulação produto da pesquisa deste artigo pode ser aplicado como um sistema de apoio à decisão do gestor para a elaboração do planejamento estratégico e do planejamento operacional com o propósito de melhorar a capacidade de análise e decisão. It is important mentioning that the simulation model in this article can be applied as a support system decision for the preparation of strategic planning and operational planning, with the purpose of improving the analysis capacity for decision-making.

A novel similarity measure for mining missing links in long-path networks

Network information mining is the study of the network topology, which may answer a large number of application-based questions towards the structural evolution and the function of a real system. The question can be related to how the real system evolves or how individuals interact with each other in social networks. Although the evolution of the real system may seem to be found regularly, capturing patterns on the whole process of evolution is not trivial. Link prediction is one of the most important technologies in network information mining, which can help us understand the evolution mechanism of real-life network. Link prediction aims to uncover missing links or quantify the likelihood of the emergence of nonexistent links from known network structures. Currently, widely existing methods of link prediction almost focus on short-path networks that usually have a myriad of close triangular structures. However, these algorithms on highly sparse or long-path networks have poor performance. Here, we propose a new index that is associated with the principles of Structural Equivalence and Shortest Path Length (SESPL) to estimate the likelihood of link existence in long-path networks. Through 548 real networks test, we find that SESPL is more effective and efficient than other similarity-based predictors in long-path networks. Meanwhile, we also exploit the performance of SESPL predictor and of embedding-based approaches via machine learning techniques. The results show that the performance of SESPL can achieve a gain of 44.09% over GraphWave and 7.93% over Node2vec. Finally, according to the matrix of Maximal Information Coefficient (MIC) between all the similarity-based predictors, SESPL is a new independent feature in the space of traditional similarity features.

Development of an Analytic Convection Model for a Heated Multi-Hole Probe for Aircraft Applications

Ice accretion or icing is a well-known phenomenon that entails a risk for the correct functioning of an aircraft. One of the areas more vulnerable to icing is the air data measuring system. This paper studies the icing protection offered by a heating system installed inside a multi-hole probe. The problem is initially solved analytically, creating a tool that can be used in order to predict the heating performance depending on the flying conditions. Later, the performance of the real system is investigated with a heated five-hole probe prototype in a wind tunnel experiment. The measured results are compared with the predictions made by the analytical model. Last, the icing protection provided by the system is estimated with respect to flying altitude and speed. As a result, a prediction tool that can be used in order to make quick icing risk predictions for straight cylindrical probes is delivered. Furthermore, the study provides some understanding about how parameters like altitude and air speed affect the occurrence of ice accretion.

Modelling and Parameter Identification for a Flexible Rotor With Periodic Impacts

The ability of a multibody dynamics model to accurately predict the behavior of a real system depends heavily on the correct choice of model parameters. The identification of unknown system parameters, which cannot be directly computed or measured is usually time consuming and costly. If experimental measurement data of the real system is available, the parameters in the mathematical model can be determined by minimizing the error between the model response and the measurement data. The latter task can be solved by means of optimization. While many optimization methods are available, optimization with a genetic algorithm is a promising approach for searching optimal solutions for complex engineering problems, as reported in a paper of one of the authors. So far, however, there is no general approach how to apply genetic optimization algorithms for complex multibody system dynamics models in order to obtain unknown parameters automatically — which is however of great importance when dealing with real flexible multibody systems. In the present paper we present a methodology to determine several unknown system parameters applied to a flexible rotor system which is excited with periodic impacts. Experiments were performed on the physical system to obtain measurement data which is used to identify the impact force as well as the support stiffnesses of the rotor system using genetic optimization.

An Open-Source ROS-Gazebo Toolbox for Simulating Robots With Compliant Actuators

To enable the design of planning and control strategies in simulated environments before their direct application to the real robot, exploiting the Sim2Real practice, powerful and realistic dynamic simulation tools have been proposed, e.g., the ROS-Gazebo framework. However, the majority of such simulators do not account for some of the properties of recently developed advanced systems, e.g., dynamic elastic behaviors shown by all those robots that purposely incorporate compliant elements into their actuators, the so-called Articulated Soft Robots ASRs. This paper presents an open-source ROS-Gazebo toolbox for simulating ASRs equipped with the aforementioned types of compliant actuators. To achieve this result, the toolbox consists of two ROS-Gazebo modules: a plugin that implements the custom compliant characteristics of a given actuator and simulates the internal motor dynamics, and a Robotic Operation System (ROS) manager node used to organize and simplify the overall toolbox usage. The toolbox can implement different compliant joint structures to perform realistic and representative simulations of ASRs, also when they interact with the environment. The simulated ASRs can be also used to retrieve information about the physical behavior of the real system from its simulation, and to develop control policies that can be transferred back to the real world, leveraging the Sim2Real practice. To assess the versatility of the proposed plugin, we report simulations of different compliant actuators. Then, to show the reliability of the simulated results, we present experiments executed on two ASRs and compare the performance of the real hardware with the simulations. Finally, to validate the toolbox effectiveness for Sim2Real control design, we learn a control policy in simulation, then feed it to the real system in feed-forward comparing the results.

Numerical simulation applied to milk cooling

A model is a representation of a real system that can be analysed and yield predictions under different operating conditions. The aim of this study was to model a milk cooling tank that cools milk to 4 °C to preserve its quality after milking at the farm. The model was developed and simulated using the software Ansys for finite element analysis. The results from the simulations were compared to experimental data. The model simulated milk cooling in the tank with an error lower than 2%, which is considered acceptable for numerical simulations. In other words, the model satisfactorily represents the real system. Thus, alternatives can be directly tested in the computational model to improve and optimise the milk cooling process and to better use the system without actually implementing them in the real system.

A Tool for the Analysis and Characterization of School Mathematical Models

This paper shows a tool for the analysis of written productions that allows for the characterization of the mathematical models that students develop when solving modeling tasks. For this purpose, different conceptualizations of mathematical models in education are discussed, paying special attention to the evidence that characterizes a school model. The discussion leads to the consideration of three components, which constitute the main categories of the proposed tool: the real system to be modeled, its mathematization and the representations used to express both. These categories and the corresponding analysis procedure are explained and illustrated through two working examples, which expose the value of the tool in establishing the foci of analysis when investigating school models, and thus, suggest modeling skills. The connection of this tool with other approaches to educational research on mathematical modeling is also discussed.