Friction-induced vibration: Model development and comparison with large-scale experimental tests

2013 ◽  
Vol 332 (21) ◽  
pp. 5302-5321 ◽  
Author(s):  
T. Butlin ◽  
J. Woodhouse
Keyword(s):  
Large Scale ◽  
Model Development ◽  
Experimental Tests ◽  
Vibration Model ◽  
Friction Induced Vibration

scholarly journals Machine learning-based feature importance approach for sensitivity analysis of steel frames

2021 ◽  
Author(s):  
Hyeyoung Koh ◽  
Hannah Beth Blum
Keyword(s):  
Machine Learning ◽  
Sensitivity Analysis ◽  
Feature Selection ◽  
Large Scale ◽  
Failure Modes ◽  
Model Development ◽  
Predictive Performance ◽  
Computational Effort ◽  
Structural Systems ◽  
Feature Importance

This study presents a machine learning-based approach for sensitivity analysis to examine how parameters affect a given structural response while accounting for uncertainty. Reliability-based sensitivity analysis involves repeated evaluations of the performance function incorporating uncertainties to estimate the influence of a model parameter, which can lead to prohibitive computational costs. This challenge is exacerbated for large-scale engineering problems which often carry a large quantity of uncertain parameters. The proposed approach is based on feature selection algorithms that rank feature importance and remove redundant predictors during model development which improve model generality and training performance by focusing only on the significant features. The approach allows performing sensitivity analysis of structural systems by providing feature rankings with reduced computational effort. The proposed approach is demonstrated with two designs of a two-bay, two-story planar steel frame with different failure modes: inelastic instability of a single member and progressive yielding. The feature variables in the data are uncertainties including material yield strength, Young’s modulus, frame sway imperfection, and residual stress. The Monte Carlo sampling method is utilized to generate random realizations of the frames from published distributions of the feature parameters, and the response variable is the frame ultimate strength obtained from finite element analyses. Decision trees are trained to identify important features. Feature rankings are derived by four feature selection techniques including impurity-based, permutation, SHAP, and Spearman's correlation. Predictive performance of the model including the important features are discussed using the evaluation metric for imbalanced datasets, Matthews correlation coefficient. Finally, the results are compared with those from reliability-based sensitivity analysis on the same example frames to show the validity of the feature selection approach. As the proposed machine learning-based approach produces the same results as the reliability-based sensitivity analysis with improved computational efficiency and accuracy, it could be extended to other structural systems.

scholarly journals M. cerebralis establishment and spread: A graphical synthesis

2021 ◽  
Author(s):  
Pouria Ramazi ◽  
Samuel Matthias Fischer ◽  
Julie Alexander ◽  
Clayton James ◽  
Andrew J. Paul ◽  
...  
Keyword(s):  
Large Scale ◽  
Graphical Model ◽  
Empirical Studies ◽  
Model Development ◽  
Ecological Impacts ◽  
Surveillance Program ◽  
Whirling Disease ◽  
Spread Model ◽  
Considerable Impact ◽  
Economic Constraints

M. cerebralis is the parasite causing whirling disease, which has dramatic ecological impacts due to its potential to cause high mortality in salmonids. The large-scale efforts, necessary to underpin an effective surveillance program, have practical and economic constraints. There is, hence, a clear need for models that can predict the parasite spread. Model development, however, often heavily depends on knowing influential variables and governing mechanisms. We have developed a graphical model for the establishment and spread of M. cerebralis by synthesizing experts’ opinion and empirical studies. First, we conducted a series of workshops with experts to identify variables believed to impact the establishment and spread of the parasite M. cerebralis and visualized their interactions via a directed acyclic graph. Then we refined the graph by incorporating empirical findings from the literature. The final graph’s nodes correspond to variables whose considerable impact on M. cerebralis establishment and spread is either supported by empirical data or confirmed by experts, and the graph’s directed edges represent direct causality or strong correlation. This graphical model facilitates communication and education of whirling disease and provides an empirically driven framework for constructing future models, especially Bayesian networks.

scholarly journals Automated Compartment Model Development Based on Data from Flow-Following Sensor Devices

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1651
Author(s):  
Jonas Bisgaard ◽  
Tannaz Tajsoleiman ◽  
Monica Muldbak ◽  
Thomas Rydal ◽  
Tue Rasmussen ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Development ◽  
Axial Flow ◽  
Compartment Model ◽  
Mixing Times ◽  
Flow Rates ◽  
Stirred Vessel ◽  
Compartment Models ◽  
Flow Models ◽  
Sensor Devices

Due to the heterogeneous nature of large-scale fermentation processes they cannot be modelled as ideally mixed reactors, and therefore flow models are necessary to accurately represent the processes. Computational fluid dynamics (CFD) is used more and more to derive flow fields for the modelling of bioprocesses, but the computational demands associated with simulation of multiphase systems with biokinetics still limits their wide applicability. Hence, a demand for simpler flow models persists. In this study, an approach to develop data-based flow models in the form of compartment models is presented, which utilizes axial-flow rates obtained from flow-following sensor devices in combination with a proposed procedure for automatic zoning of volume. The approach requires little experimental effort and eliminates the necessity for computational determination of inter-compartmental flow rates and manual zoning. The concept has been demonstrated in a 580 L stirred vessel, of which models have been developed for two types of impellers with varying agitation intensities. The sensor device measurements were corroborated by CFD simulations, and the performance of the developed compartment models was evaluated by comparing predicted mixing times with experimentally determined mixing times. The data-based compartment models predicted the mixing times for all examined conditions with relative errors in the range of 3–27%. The deviations were ascribed to limitations in the flow-following behavior of the sensor devices, whose sizes were relatively large compared to the examined system. The approach provides a versatile and automated flow modelling platform which can be applied to large-scale bioreactors.

Enterprise Modeling: Practices and Perspectives

1995 ◽  
Author(s):  
Lars C. Christensen ◽  
Brage W. Johansen ◽  
Nils Midjo ◽  
Jan Onarheim ◽  
Tor G. Syvertsen ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Development ◽  
Enterprise Modeling ◽  
Organizational Restructuring ◽  
Coordination Environment ◽  
Process Improvements ◽  
Modeling Technology ◽  
Process Plant ◽  
Enterprise Model ◽  
Oil Company

Abstract This paper presents an overview of various approaches to enterprise modeling, illustrated by present and future applications of enterprise modeling technology. A taxonomy derived from different objectives of enterprise modeling is proposed. Preliminary experiences from a large-scale enterprise modeling and organizational restructuring project are reported. The project was conducted at a natural gas process plant operated by the Norwegian oil company Statoil. We argue that the potential of enterprise modeling in business process improvements only can be utilized when the methodology is brought to the heads and hands of the inhabitants of the enterprise. Finally, a coordination environment denoted “the control room metaphor” is presented as a futuristic view of enterprise model development and application.

Mechanical Design of Antichiral-Reentrant Hybrid Intravascular Stent

2018 ◽  
Vol 10 (10) ◽  
pp. 1850105 ◽  
Author(s):  
Xiao Li Ruan ◽  
Jie Jie Li ◽  
Xiao Ke Song ◽  
Hong Jian Zhou ◽  
Wei Xing Yuan ◽  
...  
Keyword(s):  
Large Scale ◽  
Mechanical Design ◽  
Experimental Tests ◽  
Building Blocks ◽  
Industrial Applications ◽  
Mechanical Effect ◽  
Parametric Models ◽  
Element Analysis ◽  
Specific Strength ◽  
Intravascular Stents

Chiral and reentrant metastructures with auxetic deformation abilities can serve as the building blocks in many industrial applications because of their light weight, high specific strength, energy absorption properties. In this paper, we report an innovative tubular-like structure by a combined mechanical effect of antichiral and reentrant. 2D antichiral-reentrant hybrid structures consisting of circular nodes and tangentially-connected ligaments are predesigned and fabricated using laser cutting technology with high-resolution. The elastic properties and auxeticity of the plane structure are analyzed and compared based on finite element analysis (FEA) and experimental results. For the first time, the antichiral-reentrant hybrid intravascular stents with the auxetic feature are proposed and parametric models are devised with good geometrical structure demonstrated. A series of large-scale stents are manufactured with stereolithography apparatus (SLA) additive manufacturing technique, and their mechanical behaviors are investigated in both experimental tests and FEA. As the selected antichiral-reentrant hybrid stents with tailored expansion ability are subjected to radial loading by the dilation of the balloon, stents undergo identifiable deformation mechanism due to the beam-like ligaments and circular node elements in the varied geometrical design, resulting in the distinct stress outcomes in plaque. It is also demonstrated that the antichiral-reentrant hybrid stents with tunable auxeticity possess robust mechanical properties through implantation inside the obstructed lesion.

scholarly journals Demand Response Model Development for Smart Households Using Time of Use Tariffs and Optimal Control—The Isle of Wight Energy Autonomous Community Case Study

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 541 ◽  
Author(s):  
Sourav Khanna ◽  
Victor Becerra ◽  
Adib Allahham ◽  
Damian Giaouris ◽  
Jamie M. Foster ◽  
...  
Keyword(s):  
Demand Response ◽  
Large Scale ◽  
Energy Transport ◽  
Model Development ◽  
Software Tool ◽  
Load Flow ◽  
Smart Devices ◽  
Smart Meters ◽  
Isle Of Wight

Residential variable energy price schemes can be made more effective with the use of a demand response (DR) strategy along with smart appliances. Using DR, the electricity bill of participating customers/households can be minimised, while pursuing other aims such as demand-shifting and maximising consumption of locally generated renewable-electricity. In this article, a two-stage optimization method is used to implement a price-based implicit DR scheme. The model considers a range of novel smart devices/technologies/schemes, connected to smart-meters and a local DR-Controller. A case study with various decarbonisation scenarios is used to analyse the effects of deploying the proposed DR-scheme in households located in the west area of the Isle of Wight (Southern United Kingdom). There are approximately 15,000 households, of which 3000 are not connected to the gas-network. Using a distribution network model along with a load flow software-tool, the secondary voltages and apparent-power through transformers at the relevant substations are computed. The results show that in summer, participating households could export up to 6.4 MW of power, which is 10% of installed large-scale photovoltaics (PV) capacity on the island. Average carbon dioxide equivalent (CO2e) reductions of 7.1 ktons/annum and a reduction in combined energy/transport fuel-bills of 60%/annum could be achieved by participating households.

scholarly journals Low-Cost IoT Remote Sensor Mesh for Large-Scale Orchard Monitorization

2020 ◽  
Vol 9 (3) ◽  
pp. 44
Author(s):  
Leonor Varandas ◽  
João Faria ◽  
Pedro Gaspar ◽  
Martim Aguiar
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Low Cost ◽  
Experimental Tests ◽  
Remote Measurement ◽  
Land Protection ◽  
Remote Monitoring System ◽  
Solar Powered ◽  
The Individual ◽  
System Nodes

Population growth and climate change lead agricultural cultures to face environmental degradation and rising of resistant diseases and pests. These conditions result in reduced product quality and increasing risk of harmful toxicity to human health. Thus, the prediction of the occurrence of diseases and pests and the consequent avoidance of the erroneous use of phytosanitary products will contribute to improving food quality and safety and environmental land protection. This study presents the design and construction of a low-cost IoT sensor mesh that enables the remote measurement of parameters of large-scale orchards. The developed remote monitoring system transmits all monitored data to a central node via LoRaWAN technology. To make the system nodes fully autonomous, the individual nodes were designed to be solar-powered and to require low energy consumption. To improve the user experience, a web interface and a mobile application were developed, which allow the monitored information to be viewed in real-time. Several experimental tests were performed in an olive orchard under different environmental conditions. The results indicate an adequate precision and reliability of the system and show that the system is fully adequate to be placed in remote orchards located at a considerable distance from networks, being able to provide real-time parameters monitoring of both tree and the surrounding environment.

Compressible Flow Simulations on a Massively Parallel Computer

1991 ◽  
Vol 02 (01) ◽  
pp. 430-436
Author(s):  
ELAINE S. ORAN ◽  
JAY P. BORIS
Keyword(s):  
Compressible Flow ◽  
Chemical Reactions ◽  
Large Scale ◽  
Model Development ◽  
Time Dependent ◽  
Parallel Computer ◽  
Massively Parallel ◽  
Parallel Solution ◽  
Flow Simulations ◽  
Connection Machine

This paper describes model development and computations of multidimensional, highly compressible, time-dependent reacting on a Connection Machine (CM). We briefly discuss computational timings compared to a Cray YMP speed, optimal use of the hardware and software available, treatment of boundary conditions, and parallel solution of terms representing chemical reactions. In addition, we show the practical use of the system for large-scale reacting and nonreacting flows.

scholarly journals Stability Analysis of a Linear Friction-Induced Vibration Model and Its Prevention Using Active Force Control

2014 ◽  
Vol 6 ◽  
pp. 251594 ◽  
Author(s):  
S. M. Hashemi-Dehkordi ◽  
A. R. Abu-Bakar ◽  
M. Mailah
Keyword(s):  
Force Control ◽  
Pid Controller ◽  
Active Force ◽  
Active Force Control ◽  
Vibration Model ◽  
Control Scheme ◽  
Linear Friction ◽  
Critical Slope ◽  
Negative Damping ◽  
Friction Induced Vibration

This paper presents friction-induced vibration (FIV) caused by combined mode-coupling and negative damping effects in a simple FIV model. In doing so, a new four-degree-of-freedom linear model which consists of a slider and a block is proposed and then simulated using MATLAB/Simulink. Stability or instability of the FIV model is defined by the convergence or divergence of time domain responses of the slider and the block. Having found critical slope of friction-velocity characteristics that generate instabilities in the model, a conventional closed loop proportional-integral-derivative (PID) controller is first introduced into the main model in order to attenuate the vibration level and subsequently to suppress it. Later, the model is integrated with the active force control (AFC) element to effectively reject the disturbance and reduce the vibrations. It is found that the integrated PID-AFC scheme is effective in reducing vibration compared to the pure PID controller alone. Thus, the proposed control scheme can be one of the potential solutions to suppress vibration in a friction-induced vibration system.

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