Dynamic Optimization of Spur Gears

2007 ◽  
Author(s):  
M. Faggioni ◽  
F. Pellicano ◽  
A. Andrisano ◽  
G. Bertacchi
Keyword(s):  
Dynamic Model ◽  
Computational Cost ◽  
Optimization Method ◽  
Operating Conditions ◽  
Lumped Mass ◽  
Mass System ◽  
Profile Modification ◽  
Wide Range ◽  
Random Simplex ◽  
Using Data

This paper presents a global optimization method able to find gear profile modifications that minimize vibrations. A non linear dynamic model is used to study the vibrational behavior; the dynamic model is validated using data available in literature. The optimization method takes into account the influence of torque levels both on the static and the dynamic response. Therefore, two different objective functions are considered; the first one is based on static analysis and the second one is based on the dynamic behavior of a lumped mass system. The procedure can find the optimal profile modification that reduce the vibrations over a wide range of operating conditions. In order to reduce the computational cost, a Random-Simplex optimization algorithm is developed; the optimum reliability is also estimated using a Monte Carlo simulation. The approach shows good performances both for the computational efficiency and the reliability of results.

Dynamic Model of a Sac-Type Pneumatically Driven Artificial Ventricle

1977 ◽  
Vol 99 (1) ◽  
pp. 14-19 ◽  
Author(s):  
D. B. Geselowitz ◽  
G. E. Miller ◽  
W. M. Phillips
Keyword(s):  
Dynamic Model ◽  
Circulatory System ◽  
Operating Conditions ◽  
Time Varying ◽  
Outlet Port ◽  
Mock Circulatory System ◽  
Linear Resistance ◽  
Wide Range ◽  
Artificial Ventricle ◽  
Nonlinear Resistance

Inlet and outlet pressures and flows were obtained over a wide range of operating conditions for a pneumatically driven sac-type artificial ventricle connected to a mechanical mock circulatory system. The load presented to the ventricle by the mock circulatory system was found to be characterized by a linear resistance and capacitance. A dynamic model for the ventricle which accounted for instantaneous pressures and flows was developed. The outlet port is characterized by an inertance and square law resistance; the inlet port is characterized by a nonlinear resistance dependent on the type of valve. The input to the model is the time varying sac pressure. The model predicts the fill-limited and ejection-limited modes of the artificial ventricle.

Extraction of modal parameters for identification of time-varying systems using data-driven stochastic subspace identification

2017 ◽  
Vol 24 (20) ◽  
pp. 4781-4796 ◽  
Author(s):  
Wenchao Li ◽  
Viet-Hung Vu ◽  
Zhaoheng Liu ◽  
Marc Thomas ◽  
Bruce Hazel
Keyword(s):  
Data Driven ◽  
Modal Parameters ◽  
Subspace Identification ◽  
Time Varying ◽  
Lumped Mass ◽  
State Matrix ◽  
Mass System ◽  
Stochastic Subspace Identification ◽  
Time Varying Systems ◽  
Using Data

This paper presents a method for the extraction of modal parameters for identification of time-varying systems using Data-Driven Stochastic Subspace Identification (SSI-DATA). In practical applications of SSI-DATA, both the modal parameters and computational ones are mixed together in the identified results. In order to differentiate the structural ones from computational ones, a new method based on the eigen-decomposition of the state matrix constructed in SSI-DATA is proposed. The efficiency of the proposed method is demonstrated through numerical simulation of a lumped-mass system and experimental test of a moving robot for extracting excited natural frequencies of the system.

Nonlinear Dynamic Model of a Two-Stage Pressure Relief Valve for Designers

2001 ◽  
Vol 124 (1) ◽  
pp. 62-66 ◽  
Author(s):  
Pei-Sun Zung ◽  
Ming-Hwei Perng
Keyword(s):  
Dynamic Model ◽  
Nonlinear Dynamic ◽  
Dynamic Models ◽  
Operating Conditions ◽  
Model Parameters ◽  
Nonlinear Dynamic Model ◽  
Relief Valve ◽  
Two Stage ◽  
Pressure Relief ◽  
Wide Range

This paper presents a handy nonlinear dynamic model for the design of a two stage pilot pressure relief servo-valve. Previous surveys indicate that the performance of existing control valves has been limited by the lack of an accurate dynamic model. However, most of the existing dynamic models of pressure relief valves are developed for the selection of a suitable valve for a hydraulic system, and assume model parameters which are not directly controllable during the manufacturing process. As a result, such models are less useful for a manufacturer eager to improve the performance of a pressure valve. In contrast, model parameters in the present approach have been limited to dimensions measurable from the blue prints of the valve such that a specific design can be evaluated by simulation before actually manufacturing the valve. Moreover, the resultant model shows excellent agreement with experiments in a wide range of operating conditions.

A Modified Stochastic Subspace Identification Method for Estimating Natural Frequencies

2016 ◽  
Author(s):  
Kaoshan Dai ◽  
Ying Wang ◽  
Yichao Huang ◽  
W. D. Zhu ◽  
Y. F. Xu
Keyword(s):  
Natural Frequencies ◽  
Health Assessment ◽  
Operating Conditions ◽  
Subspace Identification ◽  
Lumped Mass ◽  
Mass System ◽  
Stochastic Subspace Identification ◽  
Identification Method ◽  
Periodic Rotation ◽  
Subspace Identification Method

A system identification method for estimating natural frequencies is proposed. This method developed based on the stochastic subspace identification method can identify modal parameters of structures in operating conditions with harmonic components in excitation. It benefits wind turbine tower structural health assessment because classical operational modal analysis methods can fail as periodic rotation excitation from a turbine introduces strong harmonic disturbance to tower structure response data. The effectiveness, accuracy and robustness of the proposed method were numerically investigated and verified through a lumped-mass system model.

scholarly journals Understanding Dephosphorization in Basic Oxygen Furnaces (BOFs) Using Data Driven Modeling Techniques

Metals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 955 ◽  
Author(s):  
Sandip Barui ◽  
Sankha Mukherjee ◽  
Amiy Srivastava ◽  
Kinnor Chattopadhyay
Keyword(s):  
Statistical Methods ◽  
Data Science ◽  
Basic Oxygen Furnace ◽  
Study Data ◽  
Operating Conditions ◽  
Lower Grade ◽  
Basic Oxygen ◽  
Wide Range ◽  
Using Data ◽  
Data Driven Modeling

Owing to the continuous deterioration in the quality of iron ore and scrap, there is an increasing focus on improving the Basic Oxygen Furnace (BOF) process to utilize lower grade input materials. The present paper discusses dephosphorization in BOF steelmaking from a data science perspective, which thus enables steelmakers to produce medium and low phosphorus steel grades. In the present study, data from two steel mills (Plant I and Plant II) were collected and various statistical methods were employed to analyze the data. While most operators in steel plants use spreadsheet-based techniques and linear regression to analyze data, this paper discusses on the suitability of selecting various statistical methods, and benchmarking tests to analyze such dephosphorization data sets. The data contains a wide range of operating conditions, both low and high phosphorus input loads, different slag basicity’s, different slag chemistries, and different end point temperatures, etc. The predicted phosphorus partition from various statistical models is compared against plant data and verified against previously published research.

scholarly journals A Data-Driven-Based Industrial Refrigeration Optimization Method Considering Demand Forecasting

Processes ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 617 ◽  
Author(s):  
Josep Cirera ◽  
Jesus A. Carino ◽  
Daniel Zurita ◽  
Juan A. Ortega
Keyword(s):  
Demand Forecasting ◽  
Optimization Method ◽  
Remaining Useful Life ◽  
Operating Conditions ◽  
Data Driven ◽  
Refrigeration System ◽  
Operation Condition ◽  
Self Organizing Maps ◽  
Using Data ◽  
Industrial Refrigeration

One of the main concerns of industry is energy efficiency, in which the paradigm of Industry 4.0 opens new possibilities by facing optimization approaches using data-driven methodologies. In this regard, increasing the efficiency of industrial refrigeration systems is an important challenge, since this type of process consume a huge amount of electricity that can be reduced with an optimal compressor configuration. In this paper, a novel data-driven methodology is presented, which employs self-organizing maps (SOM) and multi-layer perceptron (MLP) to deal with the (PLR) issue of refrigeration systems. The proposed methodology takes into account the variables that influence the system performance to develop a discrete model of the operating conditions. The aforementioned model is used to find the best PLR of the compressors for each operating condition of the system. Furthermore, to overcome the limitations of the historical performance, various scenarios are artificially created to find near-optimal PLR setpoints in each operation condition. Finally, the proposed method employs a forecasting strategy to manage the compressor switching situations. Thus, undesirable starts and stops of the machine are avoided, preserving its remaining useful life and being more efficient. An experimental validation in a real industrial system is performed in order to validate the suitability and the performance of the methodology. The proposed methodology improves refrigeration system efficiency up to 8%, depending on the operating conditions. The results obtained validates the feasibility of applying data-driven techniques for the optimal control of refrigeration system compressors to increase its efficiency.

Dynamic Model of a Novel Alternating Flow (AF) Hydraulic Pump

2017 ◽  
Author(s):  
Mengtang M. Li ◽  
Ryan Foss ◽  
Kim A. Stelson ◽  
James D. Van de Ven ◽  
Eric J. Barth
Keyword(s):  
Dynamic Model ◽  
High Efficiency ◽  
Check Valve ◽  
Viscous Friction ◽  
Operating Conditions ◽  
Hydraulic Systems ◽  
Displacement Control ◽  
Hydraulic Pump ◽  
Wide Range ◽  
Variable Displacement

High power density and good controllability are the most appealing characteristics that make hydraulic systems the best choice for many applications. Current state of the art hydraulic variable displacement pumps show high efficiency at high displacement while they have poor efficiencies at low displacement. This paper proposes a novel alternating flow (AF) variable displacement hydraulic pump to 1) eliminate metering losses by acting as a high-bandwidth pump for displacement control, 2) achieve high efficiency across a wide range of operating conditions and displacements, and 3) allow multiple units to be easily common-shaft mounted for a compact multi-actuator displacement control system from a single prime-mover. A dynamic model using first principles describes the cylinder pressure, flows between pairs of cylinders, and net inlet and outlet flows as a function of the pump’s phase shift angle. The model captures hydraulic check valve dynamics, the effective bulk modulus, leakage flows, and viscous friction. Piston kinematics and dynamics are discussed and energy loss models are presented and used to guide the design for a first prototype of the AF hydraulic pump. The paper presents simulation results from the model that offer an initial evaluation of this novel pump concept and potential applications.

scholarly journals Extending the Capabilities of the Mooring Analysis Program: A Survey of Dynamic Mooring Line Theories for Integration Into FAST

2014 ◽  
Author(s):  
Marco Masciola ◽  
Jason Jonkman ◽  
Amy Robertson
Keyword(s):  
Wind Turbine ◽  
Computational Cost ◽  
Offshore Wind ◽  
Mooring Line ◽  
Offshore Wind Turbine ◽  
Analysis Program ◽  
Lumped Mass ◽  
Element Analysis ◽  
Mass System ◽  
Fast Wind

Techniques to model dynamic mooring lines take various forms. The most widely used models include a heuristic representation of the physics (such as a lumped-mass system), a finite-element analysis discretization of the lines (discretized in space), or a finite-difference model (which is discretized in both space and time). In this paper, the authors explore the features of the various models, weigh the advantages of each, and propose a plan for implementing one dynamic mooring line model into the open-source Mooring Analysis Program (MAP). MAP is currently used as a module for the FAST offshore wind turbine computer-aided engineering (CAE) tool to model mooring systems quasi-statically, although dynamic mooring capabilities are desired. Based on the exploration in this paper, the lumped-mass representation is selected for implementation in MAP based on its simplicity, low computational cost, and ability to provide physics similar to those captured by higher-order models. To begin, the underlying theories defining the three classes of dynamic mooring line models are identified and explored. This leads to insight into the capabilities of each representation. These capabilities are weighed against the current needs of the FAST wind turbine CAE tool, to which MAP will be coupled. Based on the assessment, a plan for integrating the dynamic mooring line theory into the current MAP structure is developed. Common problems arising from the determination of the model static equilibrium and known issues with numerical stability are addressed. Because MAP is a module that FAST can call, a plan consistent with the FAST modularization framework principles is described. Adding dynamic mooring line capabilities extends the features in MAP and also allows uncoupled analysis to be performed through MAP’s native Python bindings.

Performance Simulation of a Hybrid Micro Gas Turbine Fuel Cell System Based on Existing Components

2011 ◽  
Author(s):  
D. P. Bakalis ◽  
A. G. Stamatis
Keyword(s):  
Fuel Cell ◽  
Gas Turbine ◽  
System Performance ◽  
Cell System ◽  
Operating Conditions ◽  
Optimum Operating ◽  
Utilization Factor ◽  
Micro Gas Turbine ◽  
Wide Range ◽  
Using Data

The objective of this work is the development of a simulation model for a hybrid Solid Oxide Fuel Cell (SOFC)/Micro Gas Turbine (MGT) system, flexible and robust enough, capable to predict the system performance under various operating conditions. The hybrid system consists of a high temperature SOFC, based on a tubular configuration developed by Siemens Power Generation Inc, and a recuperated small gas turbine (GT) validated using data for the Capstone C30. The design and off-design performance of the system is examined by means of performance maps. Moreover, operating parameters such as fuel utilization factor, steam to carbon ratio and current density are varied over a wide range and the influence on system performance is studied. The optimum operating conditions are discussed with regard to overall system performance under part load operation. The results show that high electrical efficiencies can be achieved making these systems appropriate for distributed generation applications.

Multipoint Design Optimization of a Transonic Compressor Blade by Using an Adjoint Method

2013 ◽  
Vol 136 (5) ◽  
Author(s):  
Jiaqi Luo ◽  
Chao Zhou ◽  
Feng Liu
Keyword(s):  
Design Optimization ◽  
Adjoint Method ◽  
Pressure Ratio ◽  
Single Point ◽  
Optimization Method ◽  
Computational Effort ◽  
Operating Conditions ◽  
Design Parameters ◽  
Transonic Compressor ◽  
Wide Range

This paper presents the application of a viscous adjoint method to the multipoint design optimization of a rotor blade through blade profiling. The adjoint method requires about twice the computational effort of the flow solution to obtain the complete gradient information at each operating condition, regardless of the number of design parameters. NASA Rotor 67 is redesigned through blade profiling. A single point design optimization is first performed to verify the effectiveness and feasibility of the optimization method. Then in order to improve the performance for a wide range of operating conditions, the blade is redesigned at three operating conditions: near peak efficiency, near stall, and near choke. Entropy production through the blade row combined with the constraints of mass flow rate and total pressure ratio is used as the objective function. The design results are presented in detail and the effects of blade profiling on performance improvement and shock/tip-leakage interaction are examined.

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