Dynamic Models of Thermal Systems Using an Energy-Based Modeling Approach

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Federica Grossi ◽  
Roberto Zanasi
Keyword(s):  
Heat Transfer ◽  
Simple Structure ◽  
Dynamic Models ◽  
Control Design ◽  
Thermal Systems ◽  
Conservation Of Energy ◽  
New Approach ◽  
Proposed Model ◽  
Real Time Simulations ◽  
Internal Convection

The aim of this work is to give a new approach to obtain compact dynamic thermal models suitable for a variety of systems where the heat transfer can be caused by conduction, internal convection (not at the boundary), and evaporation/condensation of water. The structural properties of the proposed dynamic model are presented and discussed in this paper. These properties guarantee conservation of energy and mass within the system, thus giving a good confidence in the correctness of the model. This paper shows that the proposed model has a simple structure, can be easily implemented in simulink, and provides simulation times much shorter compared with those usually obtained using CFD programs. The proposed model proves to be suitable for real-time simulations and for control design purposes.

Intelligent recognition of semantic relationships based on antonymy

2020 ◽  
Vol 16 (3) ◽  
pp. 263-290
Author(s):  
Hui Guan ◽  
Chengzhen Jia ◽  
Hongji Yang
Keyword(s):  
Semantic Similarity ◽  
New Approach ◽  
Word Similarity ◽  
Semantic Relationships ◽  
Proposed Model ◽  
Path Distance ◽  
The Hierarchical Structure ◽  
Thinking Process ◽  
Similarity Measuring ◽  
Intelligent Recognition

Since computing semantic similarity tends to simulate the thinking process of humans, semantic dissimilarity must play a part in this process. In this paper, we present a new approach for semantic similarity measuring by taking consideration of dissimilarity into the process of computation. Specifically, the proposed measures explore the potential antonymy in the hierarchical structure of WordNet to represent the dissimilarity between concepts and then combine the dissimilarity with the results of existing methods to achieve semantic similarity results. The relation between parameters and the correlation value is discussed in detail. The proposed model is then applied to different text granularity levels to validate the correctness on similarity measurement. Experimental results show that the proposed approach not only achieves high correlation value against human ratings but also has effective improvement to existing path-distance based methods on the word similarity level, in the meanwhile effectively correct existing sentence similarity method in some cases in Microsoft Research Paraphrase Corpus and SemEval-2014 date set.

Towards real-time fire data synthesis using numerical simulations

2021 ◽  
pp. 073490412199344
Author(s):  
Wolfram Jahn ◽  
Frane Sazunic ◽  
Carlos Sing-Long
Keyword(s):  
Real Time ◽  
Computational Fluid Dynamic ◽  
Dynamic Models ◽  
Fluid Dynamic ◽  
Near Field ◽  
Computing Time ◽  
Temperature Correction ◽  
Dynamic Simulations ◽  
Conservation Of Energy ◽  
Fire Scenarios

Synthesising data from fire scenarios using fire simulations requires iterative running of these simulations. For real-time synthesising, faster-than-real-time simulations are thus necessary. In this article, different model types are assessed according to their complexity to determine the trade-off between the accuracy of the output and the required computing time. A threshold grid size for real-time computational fluid dynamic simulations is identified, and the implications of simplifying existing field fire models by turning off sub-models are assessed. In addition, a temperature correction for two zone models based on the conservation of energy of the hot layer is introduced, to account for spatial variations of temperature in the near field of the fire. The main conclusions are that real-time fire simulations with spatial resolution are possible and that it is not necessary to solve all fine-scale physics to reproduce temperature measurements accurately. There remains, however, a gap in performance between computational fluid dynamic models and zone models that must be explored to achieve faster-than-real-time fire simulations.

scholarly journals Predicting the Energy Consumption of a Robot in an Exploration Task Using Optimized Neural Networks

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 920
Author(s):  
Liesle Caballero ◽  
Álvaro Perafan ◽  
Martha Rinaldy ◽  
Winston Percybrooks
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Mobile Robot ◽  
Energy Budget ◽  
Dynamic Models ◽  
Pearson Correlation ◽  
Experimental Conditions ◽  
Grid Map ◽  
Proposed Model ◽  
Exploration Task

This paper deals with the problem of determining a useful energy budget for a mobile robot in a given environment without having to carry out experimental measures for every possible exploration task. The proposed solution uses machine learning models trained on a subset of possible exploration tasks but able to make predictions on untested scenarios. Additionally, the proposed model does not use any kinematic or dynamic models of the robot, which are not always available. The method is based on a neural network with hyperparameter optimization to improve performance. Tabu List optimization strategy is used to determine the hyperparameter values (number of layers and number of neurons per layer) that minimize the percentage relative absolute error (%RAE) while maximize the Pearson correlation coefficient (R) between predicted data and actual data measured under a number of experimental conditions. Once the optimized artificial neural network is trained, it can be used to predict the performance of an exploration algorithm on arbitrary variations of a grid map scenario. Based on such prediction, it is possible to know the energy needed for the robot to complete the exploration task. A total of 128 tests were carried out using a robot executing two exploration algorithms in a grid map with the objective of locating a target whose location is not known a priori by the robot. The experimental energy consumption was measured and compared with the prediction of our model. A success rate of 96.093% was obtained, measured as the percentage of tests where the energy budget suggested by the model was enough to actually carry out the task when compared to the actual energy consumed in the test, suggesting that the proposed model could be useful for energy budgeting in actual mobile robot applications.

scholarly journals A New Approach to Inform Restoration and Management Decisions for Sustainable Apiculture

2021 ◽  
Vol 13 (11) ◽  
pp. 6109
Author(s):  
Joanne Lee Picknoll ◽  
Pieter Poot ◽  
Michael Renton
Keyword(s):  
Floral Resources ◽  
Pollination Services ◽  
New Approach ◽  
Honey Production ◽  
Proposed Model ◽  
Colony Loss ◽  
Supply Potential ◽  
Australian Case ◽  
Stocking Rates

Habitat loss has reduced the available resources for apiarists and is a key driver of poor colony health, colony loss, and reduced honey yields. The biggest challenge for apiarists in the future will be meeting increasing demands for pollination services, honey, and other bee products with limited resources. Targeted landscape restoration focusing on high-value or high-yielding forage could ensure adequate floral resources are available to sustain the growing industry. Tools are currently needed to evaluate the likely productivity of potential sites for restoration and inform decisions about plant selections and arrangements and hive stocking rates, movements, and placements. We propose a new approach for designing sites for apiculture, centred on a model of honey production that predicts how changes to plant and hive decisions affect the resource supply, potential for bees to collect resources, consumption of resources by the colonies, and subsequently, amount of honey that may be produced. The proposed model is discussed with reference to existing models, and data input requirements are discussed with reference to an Australian case study area. We conclude that no existing model exactly meets the requirements of our proposed approach, but components of several existing models could be combined to achieve these needs.

Highly Subcooled Flow Boiling: A Model for Estimating Heat Transfer Behind Sliding Bubbles in a Narrow Channel

2012 ◽  
Author(s):  
Arif B. Ozer ◽  
Donald K. Hollingsworth ◽  
Larry. C. Witte
Keyword(s):  
Heat Transfer ◽  
Flow Field ◽  
Heat Generation ◽  
Wall Temperature ◽  
Flow Boiling ◽  
Narrow Channel ◽  
Heated Wall ◽  
Uniform Heat ◽  
Proposed Model ◽  
Sliding Bubbles

A quenching/diffusion analytical model has been developed for predicting the wall temperature and wall heat flux behind bubbles sliding in a confined narrow channel. The model is based on the concept of a well-mixed liquid region that enhances the heat transfer near the heated wall behind the bubble. Heat transfer in the liquid is treated as a one-dimensional transient conduction process until the flow field recovers back to its undisturbed level prior to bubble passage. The model is compared to experimental heat transfer results obtained in a high-aspect-ratio (1.2×23mm) rectangular, horizontal channel with one wide wall forming a uniform-heat-generation boundary and the other designed for optical access to the flow field. The working fluid was Novec™ 649. A thermochromic liquid crystal coating was applied to the outside of the uniform-heat-generation boundary, so that wall temperature variations could be obtained and heat transfer coefficients and Nusselt numbers could be obtained. The experiments were focused on high inlet subcooling, typically 15–50°C. The model is able to capture the elevated heat transfer rates measured in the channel without the need to consider nucleate boiling from the surface or microlayer evaporation from the sliding bubbles. Surface temperatures and wall heat fluxes were estimated for 17 different experimental conditions using the proposed model. Results agreed with the measured values within ±15% accuracy. The insight gathered from comparing the results of the proposed model to experimental results provides the basis for a better understanding of the physics of subcooled bubbly flow in narrow channels.

Heat Transfer in Liquid Helium II by Internal Convection

1948 ◽  
Vol 74 (9) ◽  
pp. 1148-1156 ◽  
Author(s):  
F. London ◽  
P. R. Zilsel
Keyword(s):  
Heat Transfer ◽  
Liquid Helium ◽  
Helium Ii ◽  
Internal Convection

scholarly journals Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Aisong Qin ◽  
Qinghua Zhang ◽  
Qin Hu ◽  
Guoxi Sun ◽  
Jun He ◽  
...  
Keyword(s):  
Health Management ◽  
Rotating Machinery ◽  
Remaining Useful Life ◽  
Programming Algorithm ◽  
Wiener Model ◽  
New Approach ◽  
Degradation Modeling ◽  
Proposed Model ◽  
Useful Life ◽  
Degradation Indicator

Remaining useful life (RUL) prediction can provide early warnings of failure and has become a key component in the prognostics and health management of systems. Among the existing methods for RUL prediction, the Wiener-process-based method has attracted great attention owing to its favorable properties and flexibility in degradation modeling. However, shortcomings exist in methods of this type; for example, the degradation indicator and the first predicting time (FPT) are selected subjectively, which reduces the prediction accuracy. Toward this end, this paper proposes a new approach for predicting the RUL of rotating machinery based on an optimal degradation indictor. First, a genetic programming algorithm is proposed to construct an optimal degradation indicator using the concept of FPT. Then, a Wiener model based on the obtained optimal degradation indicator is proposed, in which the sensitivities of the dimensionless parameters are utilized to determine the FPT. Finally, the expectation of the predicted RUL is calculated based on the proposed model, and the estimated mean degradation path is explicitly derived. To demonstrate the validity of this model, several experiments on RUL prediction are conducted on rotating machinery. The experimental results indicate that the method can effectively improve the accuracy of RUL prediction.

Understanding the electrical behavior of the action potential in terms of elementary electrical sources

2015 ◽  
Vol 39 (1) ◽  
pp. 15-26 ◽  
Author(s):  
Javier Rodriguez-Falces
Keyword(s):  
Action Potential ◽  
Action Potentials ◽  
Present Report ◽  
Electrical Potential ◽  
Ionic Currents ◽  
New Approach ◽  
Electrical Potentials ◽  
Proposed Model ◽  
Ionic Mechanisms ◽  
Human Electrophysiology

A concept of major importance in human electrophysiology studies is the process by which activation of an excitable cell results in a rapid rise and fall of the electrical membrane potential, the so-called action potential. Hodgkin and Huxley proposed a model to explain the ionic mechanisms underlying the formation of action potentials. However, this model is unsuitably complex for teaching purposes. In addition, the Hodgkin and Huxley approach describes the shape of the action potential only in terms of ionic currents, i.e., it is unable to explain the electrical significance of the action potential or describe the electrical field arising from this source using basic concepts of electromagnetic theory. The goal of the present report was to propose a new model to describe the electrical behaviour of the action potential in terms of elementary electrical sources (in particular, dipoles). The efficacy of this model was tested through a closed-book written exam. The proposed model increased the ability of students to appreciate the distributed character of the action potential and also to recognize that this source spreads out along the fiber as function of space. In addition, the new approach allowed students to realize that the amplitude and sign of the extracellular electrical potential arising from the action potential are determined by the spatial derivative of this intracellular source. The proposed model, which incorporates intuitive graphical representations, has improved students' understanding of the electrical potentials generated by bioelectrical sources and has heightened their interest in bioelectricity.

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