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A DATA driven METHOD FOR THE DERIVATION OF EXPLICIT ALGEBRAIC REYNOLDS STRESS MODELS APPLIED TO THE WAKE LOSSES OF LOW-PRESSURE TURBINE CASCADES 69

A DATA DRIVEN METHOD FOR THE DERIVATION OF EXPLICIT ALGEBRAI...

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69th ASME Turbomachinery Technical conference and Exposition (ASME Turbo Expo) (GT)

作者： Deutsch, Johannes Afshar, Nima Fard Henninger, Stefan Jeschke, Peter Rhein Westfal TH Aachen Inst Jet Prop & Turbomachinery Aachen Germany

ISBN: (纸本)9780791888070

This paper introduces and validates a data-driven approach to improve the prediction of linear eddy viscosity models (LEVMs). The general approach is adopted in order to improve the wake mixing of low-pressure turbine (LPT) cascades. The approach is based on the modification of the Boussinesq assumption. It follows the rationale applied in the derivation of explicit algebraic Reynolds stress models (EARSMs) by including additional second-order tensors, as suggested by Pope [1]. The unknown scalar functions that determine the contributions of each second-order tensor to the Reynolds stresses are approximated as polynomials. A metamodel-assisted multi-objective optimization determines the value of each of the polynomial coefficients. The optimization minimizes the difference between the result of the EARSM simulation and reference data provided by a high fidelity large eddy simulation (LES). In this study, tailor made EARSMs are calibrated in order to improve the prediction of the kinetic energy loss distribution in the wake of the T106C LPT cascade with an isentropic Reynolds number of 80 000. We showed that the wake losses predicted by state of the art Reynolds-averaged Navier-Stokes (RANS) turbulence models cannot reproduce the reference LES data. In the following, we investigated the influence of each polynomial coefficient of the EARSM on the flow solutions within a sensitivity study. The models generated by the approach reduced the deviations in turbulent kinetic energy loss between the LES reference solution and the baseline model by approximately 70 %. The turbulent quantities are analyzed to identify the physical correlations between the model inputs and the improvement. The transferability of the models to unseen test cases was assessed using the MTU-T161 LPT cascade with an isentropic Reynolds number of 90 000. A decrease of up to 80% is achieved regarding the deviations between the LES reference and the baseline RANS model. In summary, the suggested approa

关键词： turbulence modeling turbine cascade loss generation

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Evaluating data-driven building stock heat demand forecasting models for energy optimization 17

Evaluating data-driven building stock heat demand forecastin...

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17th conference of International-Building-Performance-simulation-Association (IBPSA)

作者： Jafarinejad, Tohid De Jaeger, Ina Erfani, Arash Saelens, Dirk Katholieke Univ Leuven Bldg Phys & Sustainable Design Sect Dept Civil Engn Leuven Belgium EnergyVille Genk Belgium

ISBN: (纸本)9781775052029

Achieving energy efficiency in building sector is plausible through overly non-convex energy optimization schemes such as demand side management (DSM) at district scale, which itself relies on the district's thermal model. The main challenge is deriving accurate surrogate data-driven models for districts, which can compete with detailed time-intensive physics based models. In this study, common data-driven models namely ARX, ANN and SVM are deployed for modeling various districts under different aggregation criteria. This study is conducted based on the artificial districts that are developed for IBPSA Project 1. Furthermore, the data-driven models are compared based on two Key Performance Indicators (KPI) namely coefficient of determination (R2) and run-time. Finally, it is shown that an SVM model performs the best. Moreover, aggregating based on archetype yields more promising results in terms of accuracy.

关键词： Benchmarking

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Model-driven Behavioral modeling and Verification Methods for Human-Machine Hybrid Intelligent Systems

Model-Driven Behavioral Modeling and Verification Methods fo...

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2024 International conference on Advanced Control Systems and Automation Technologies, ACSAT 2024

作者： Dong, Yuanfa Zeng, Yuxin Zhang, Wenli Zhou, Bin China Three Gorges University College of Mechanical & Power Engineering Yichang China

ISBN: (纸本)9798331541668

The design phase endows the product with innate quality, especially the quality of front-end design, which directly determines the final interactive characteristics and user experience of the product. In order to reduce human-machine behavior conflicts, it is necessary to model and validate human-machine hybrid intelligent systems at the behavioral level in the early stages of design. In response to the difficulties in characterizing multimodal interactions and supporting simulation based behavior optimization design caused by 'human in the loop', firstly, the SysML state machine diagram was extended based on the characteristics of human-computer interaction behavior, and a meta behavior and formal representation model for human-machine hybrid intelligent systems was established. Subsequently, a semantic mapping rule from the human-computer interaction behavior model to the PRISM probabilistic time automaton was proposed, and the requirement specification of the human-machine hybrid intelligent system was validated using probabilistic time computation tree logic. A model driven behavior modeling and validation method for human-machine hybrid intelligent systems was proposed. Finally, the feasibility of the method was verified by taking the design of a human-machine hybrid intelligent system for handling human-machine collaborative assembly anomalies as an example. © 2024 IEEE.

关键词： Intelligent systems

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A Holistic Approach for Rapid Unconventional Reservoir optimization

A Holistic Approach for Rapid Unconventional Reservoir Optim...

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2024 SPE/AAPG/SEG Unconventional Resources Technology conference, URTC 2024

作者： Zheng, Wei Banerjee, Raj Carvajal, Rodolfo Koley, Manas SLB United States

Developing unconventional plays in North America has been challenged with the need for speed and accuracy. Different approaches have been implemented in the field ranging from empirical, analytical methods to numerical simulation and machine learning. However, none of these separate approaches offers a robust and yet balanced solution for rapid and accurate reservoir optimization for unconventional plays. Therefore, a holistic approach is developed in this paper, which combines benefits of analytical, numerical and data science methodologies to systematically study unconventional reservoirs and provide timely optimization solutions. This workflow starts with asset screening using public data, to fit the unconventional reservoir challenge, a published data-driven machine learning (ML) completion optimization approach is used for the preliminary well design. After the initial scope is defined, sector modeling using numerical simulation powered by high-fidelity fracture, reservoir and geomechanics simulators is performed for production history match. Since most of the unconventional plays are depleted, 3D finite-element reservoir geomechanics coupling is used for robust understanding of the induced influences. This is critical for operations planning such as parent-child well and refracture design as the depletion complicates production profile. Due to the high computational nature, this step is applied at the sector level. With high-well-count pad development, local grid refinement methodology can be applied for an overall efficiency balance. In this study, an established ML based rate-transient analysis approach is applied to achieve rapid asset forecast for area of interest. Public Permian Basin data were used for initial well assessment. A synthetic data set was used to build the parent-child well model at pad level. Sensitivity study for infill well spacing design was conducted at sector level with consideration of depletion effects for production optimization. Us

关键词： Machine learning

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2nd International and 14th National conference on Industrial Problems on Machines and Mechanisms, IPRoMM 2022

2nd International and 14th National Conference on Industrial...

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2nd International and 14th National conference on Industrial Problems on Machines and Mechanisms, IPRoMM 2022

ISBN: (纸本)9789819942695

The proceedings contain 67 papers. The special focus in this conference is on Industrial Problems on Machines and Mechanisms. The topics include: Design and Development of a Three-Link Rigid-Flexible Manipulator;comparative Study on Hydraulic Pressure Pulsation Characteristics in Simple and Regenerative Hydraulic System;localization of a Drone for Landing Using Image-Based Visual Servoing with Image Moments;System Identification of Hydrostatic Transmission (HST) System Using Bond Graph Methodology;surface Electromyography-Controlled Mechanical Hand: A Design Approach;Semi-Automated Setup for the Manufacture of Dual-Probe Heat Pulse (DPHP) Soil-Moisture Sensor;a Study of Passive Control in a Bridge Configured Winding Induction Motor with an Oval-Shaped Stator;control Framework for Position Control of Three-Segment Tendon-driven Continuum Robot;position Control of Pneumatic Piston Using Continuous Integral Sliding Mode Control;rail Analyzer: 3D Model-Based Railway simulation Software for Wheel-Rail Interaction;Dynamic Analysis of a Low-Speed, High-Torque Hydro-Motor Drive System to Maintain a Constant Drive Speed Using ANN-Based Fuzzy PI Controller;hand–Object Interaction modeling for Precision Grasp by Multi-fingered Hands;profile Estimation of Multi-segmented Cable-driven Continuum Robots Using optimization Method;shape Reconstruction of a Pneumatic Continuum Manipulator Under the Effect of Hysteresis During Trajectory Tracking;Fabrication of Hard WC + Cu + La2O3 Coating on Ti–6Al–4V Alloy Using Reverse EDM Process;simulation of Temperature Profile in Wire Arc Additive Manufacturing;Effect of Polarity Variation in Maglev EDM Using Nitrogen-Rich Powder-Mixed Dielectric;microstructural and Mechanical Characterization of Friction Stir-Assisted Lap Joining of Mg Alloy;Prediction of Exit Burr Formation in Orthogonal Micromachining via FE modeling;virtual Validation and optimization of Electric Two-Wheeler for Ride Comfort Analysis.

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Combining Data-driven and Physics-based Process Models for Hybrid Model Predictive Control of Building Energy Systems 30

Combining Data-driven and Physics-based Process Models for H...

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30th Mediterranean conference on Control and Automation (MED)

作者： Stoffel, Phillip Loeffler, Charlotte Eser, Steffen Kuempel, Alexander Mueller, Dirk Rhein Westfal TH Aachen EON Energy Res Ctr Inst Energy Efficient Bldg & Indoor Climate D-52074 Aachen Germany

ISBN: (纸本)9781665406734

Model predictive control is well suited to control building energy systems efficiently. However, it still lacks commercial relevance due to the high modeling effort. This article presents a methodology to reduce the modeling effort by combining data-driven and physics-based process models in a hybrid MPC scheme. Data-driven models like artificial neural networks are generally nonconvex and nonlinear. Thus, using such models results in a nonlinear, nonconvex optimization problem. We present a workflow to efficiently solve the resulting optimization problem with gradient-based solvers using the algorithmic differentiation tool CasADi. The developed workflow is applied to an exemplary building energy system to implement an economic, hybrid model predictive controller. simulation results confirm the high potential of the proposed methodology by realizing a cost-effective operation of the controlled system.

关键词： Economics Automation simulation Buildings Artificial neural networks Predictive models Control systems

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Generating Vehicle Behavior in Urban Traffic: A Static Path driven Behavior Model 7

Generating Vehicle Behavior in Urban Traffic: A Static Path ...

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7th IFAC conference on Engine and Powertrain Control, simulation and modeling (E-COSM)

作者： Xiong, Jie Chen, Chen Piao, Yingxi Li, Honglin Li, Shengbo Eben Cheng, Bo Tsinghua Univ Beijing Peoples R China Beijing Univ Technol Beijing Peoples R China DONGFENG Motor Corp Res Dev Inst Wuhan Peoples R China

Autonomous driving simulation is crucial for testing autonomous driving functions and iterating algorithms. However, most current studies focus solely on normal traffic behaviors, such as car-following or lane-changing, while neglecting abnormal traffic behaviors that are very important for autonomous vehicle training and testing, such as random deviations from the road centerline, random desired speeds, etc. This paper introduces an innovative method that integrates car-following and lane-changing behaviors into a unified framework by designing a path value evaluation function for static path optimization and performing optimal path-following obstacle avoidance. This method allows for random deviations from the road centerline and random desired speeds. By utilizing the highD dataset for model calibration, the simulated traffic flow closely mirrors real-world conditions. simulation experiments indicate that this model can simulate complex and diverse vehicle driving behaviors, particularly in scenarios involving deviations from the road centerline and abnormal speeds, with the average following distance reaching 95.2% of the standard value. Copyright (c) 2024 The Authors.

关键词： modeling and simulation of transportation systems Autonomous Vehicles autonomous driving simulation Intelligent transportation systems,car following behavior lane changing behavior

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Manifold optimization for Data driven Reduced-Order modeling∗ 59

Manifold Optimization for Data Driven Reduced-Order Modeling...

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59th Annual Allerton conference on Communication, Control, and Computing, Allerton 2023

作者： Newton, Rachel Du, Zhe Balzano, Laura Seiler, Peter University of Michigan Department of Electrical Engineering and Computer Science United States

ISBN: (纸本)9798350328141

The focus of this paper is on data-driven reduced-order modeling. We assume a high fidelity, discrete-time model is available for simulation. The simulator allows state and output trajectories to be collected for any specified initial condition and input signal. An optimal reduced-order model (ROM) requires: (i) the selection of a lower dimensional subspace for the state of the ROM, and (ii) an optimal reduced-order state-space model (evolving on the lower dimensional subspace). A common heuristic is to: (i) select the lower-order subspace using proper orthogonal decomposition (POD), and (ii) use least-squares to fit the reduced-order state-space model on the POD subspace. We demonstrate the potential deficiencies of this heuristic via two simple examples. In order to address these deficiencies, we propose a novel method to optimize the choice of subspace using the Grassmann manifold. Finally, we show that our proposed manifold optimization empirically outperforms the POD heuristic on the two motivating examples and a planar wind farm model. © 2023 IEEE.

关键词： optimization

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A Visual simulation Platform for Automatic Field-of-View Adjustment Algorithm optimization of a Tendon-driven Continuum Laparoscope 2nd

A Visual Simulation Platform for Automatic Field-of-View Ad...

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2nd International conference on the Frontiers of Robotics and Software Engineering, FRSE 2024

作者： Wang, Baichuan Li, Weiqi Zhang, Jing Pan, Zhijie Wang, Xiyu Ye, Yongyin Wang, Jiangnan Li, Mengtang School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-Sen University Shenzhen518107 China Guangdong Provincial Key Laboratory of Fire Science and Technology Guangzhou510006 China

ISBN: (纸本)9789819630127

Laparoscopic surgery, a prevalent form of minimally invasive surgery (MIS), has found widespread application in clinical practice. However, the conventional approach to laparoscopic surgery necessitates assistant surgeons to manually manipulate the camera. In order to improve efficiency, numerous laparoscopic robots have been developed. Yet, these laparoscopic robots are constrained by the Remote Center of Motion (RCM), which limits their degrees of freedom (DoF) and complicates control and modeling during field of view (FOV) adjustments. This paper proposes a novel tendon-driven continuum laparoscope that circumvents the RCM constraint. Additionally, a visualization simulation platform based on Webots is established to design an automatic FOV adjustment tracking algorithms suitable for this laparoscope. The automatic tracking algorithm considers the position, size, and eye-hand coordination of the target instrument. simulation results indicate that after stable tracking of the target, the average tracking error is less than 10 pixels, and the size of the object recognized by the camera is within the set range, consistent with hand-eye coordination. Therefore, the visualization simulation platform proposed in this paper will contribute to optimizing automatic laparoscopic FOV adjustment tracking algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Laparoscopy

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Dynamic modeling and analysis of a vibration-driven robot driven by a conical dielectric elastomer actuator 63

Dynamic modeling and analysis of a vibration-driven robot dr...

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63rd International conference on Vibroengineering

作者： Wang, Xiaojian Li, Hongguang State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China

This article aims to establish a theoretical model of a vibration-driven robot driven by a conical dielectric elastomer actuator and analyze its characteristics, in order to make up for the lack of theoretical model construction and parameter evolution analysis for this type of robot. This article introduces a vibration-driven robot driven by a conical dielectric elastomer actuator, and then establishes its dynamic model based on its electromechanical coupling and viscoelastic characteristics. Subsequently, simulation research is conducted using this model. Overall, this article derived a dynamic equation that can be applied to this type of robot, analyzed its motion characteristics, studied the effects of different parameters on it, and discussed the influence of viscoelasticity on vibration-driven robots. The proposed dynamic model and evolution law of vibration robots can provide theoretical guidance for subsequent control and optimization. Copyright © 2023 Xiaojian Wang, et al.

关键词： Dynamic models

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