Real-Time Dynamics Modeling of Cryogenic Ball Bearings With Thermal Coupling

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Pradeep K. Gupta ◽  
Howard G. Gibson
Keyword(s):  
Steady State ◽  
Real Time ◽  
Dynamic Modeling ◽  
Heat Generation ◽  
Step Change ◽  
Operating Conditions ◽  
Thermal Time ◽  
Ball Bearings ◽  
Thermal Coupling ◽  
Steady State Condition

Abstract Real-time dynamic modeling of cryogenic ball bearings, where the rotating inner race accelerates to the operating speed, is based on integration of classical differential equations of motion of bearing elements, when experimentally measured ball/race traction behavior is used to compute the imposed acceleration on the rolling elements. The dynamic performance simulation provides a realistic coupling between traction behavior in the ball-to-race contacts and dynamics of bearing element motion as the bearing goes through the transient speed variation. However, due to vastly different mechanical and thermal time scales, heat generation in the bearing is time-averaged over a relatively large thermal time-step to model temperature fields as a step change, while the bearing motion is simulated in real-time. The emphasis is on dynamic modeling with thermal coupling in a static sense. Under stable conditions, the step change in temperature field converges to operating value as the bearing approaches a dynamic steady-state condition, which demonstrates acceptable significance of the dynamic simulation with coupled thermal interactions. Both all steel and hybrid ball bearings for liquid oxygen (LOX) turbo pump applications are modeled. Bearing performance simulations are closely modeled over experimental time cycles in both transient and steady-state domains. Steady-state solutions are shown to be independent of initial conditions to demonstrate acceptable convergence of time domain integrations. Model predictions of heat transferred to circulating LOX is within the range of variation in experimental data. Parametric evaluation of bearing performance as a function of operating conditions demonstrate that while the ball/race contact stress is higher in a hybrid bearing, contact heat generation is significantly lower in comparison with that in the all steel bearings.

scholarly journals Dynamic Modeling of Single-Shaft Industrial Gas Turbine

1996 ◽  
Author(s):  
R. Bettocchi ◽  
P. R. Spina ◽  
F. Fabbri
Keyword(s):  
Steady State ◽  
Gas Turbine ◽  
Dynamic Modeling ◽  
Operating Conditions ◽  
Steady State Condition ◽  
On Line ◽  
Working Parameters ◽  
Industrial Gas Turbine ◽  
And Control ◽  
Measurement And Control

In the paper the dynamic non-linear model of single shaft industrial gas turbine was developed as the first stage of a methodology aimed at the diagnosis of measurement and control sensors and gas turbine operating conditions. The model was calibrated by means of reference steady-state condition data of a real industrial gas turbine and was used to simulate various machine transients. The model is modular in structure and was carried out in simplified form, but not so as to compromise its accuracy, to reduce the calculation time and thus make it more suitable for on-line simulation. The comparison between values of working parameters obtained by the simulations and measurements during some transients on the gas turbine in operation provided encouraging results.

Thermo-structural analysis of a honeycomb-type volumetric absorber for concentrated solar power applications

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Masoud Behzad ◽  
Benjamin Herrmann ◽  
Williams R. Calderón-Muñoz ◽  
José M. Cardemil ◽  
Rodrigo Barraza
Keyword(s):  
Heat Transfer ◽  
Thermal Stress ◽  
Steady State ◽  
Discrete Model ◽  
Continuum Model ◽  
Transient State ◽  
Operating Conditions ◽  
Steady State Condition ◽  
Content Type ◽  
The Continuum

Purpose Volumetric air receivers experience high thermal stress as a consequence of the intense radiation flux they are exposed to when used for heat and/or power generation. This study aims to propose a proper design that is required for the absorber and its holder to ensure efficient heat transfer between the fluid and solid phases and to avoid system failure due to thermal stress. Design/methodology/approach The design and modeling processes are applied to both the absorber and its holder. A multi-channel explicit geometry design and a discrete model is applied to the absorber to investigate the conjugate heat transfer and thermo-mechanical stress levels present in the steady-state condition. The discrete model is used to calibrate the initial state of the continuum model that is then used to investigate the transient operating states representing cloud-passing events. Findings The steady-state results constitute promising findings for operating the system at the desired airflow temperature of 700°C. In addition, we identified regions with high temperatures and high-stress values. Furthermore, the transient state model is capable of capturing the heat transfer and fluid dynamics phenomena, allowing the boundaries to be checked under normal operating conditions. Originality/value Thermal stress analysis of the absorber and the steady/transient-state thermal analysis of the absorber/holder were conducted. Steady-state heat transfer in the explicit model was used to calibrate the initial steady-state of the continuum model.

An Accelerated Testing Approach for Lubricant Oil Consumption Reduction on an EMD 710 Diesel Engine

2010 ◽  
Author(s):  
Kent Froelund ◽  
Steve Fritz ◽  
John Hedrick ◽  
Jaime Garcia ◽  
Neil Blythe
Keyword(s):  
Steady State ◽  
Diesel Engine ◽  
Real Time ◽  
Measurement Technique ◽  
Consumption Rate ◽  
Operating Conditions ◽  
Lubricating Oil ◽  
Oil Consumption ◽  
Ultra Low Sulfur Diesel ◽  
Lubricant Oil

Real-Time Da Vinci Lubricant Oil Consumption (DALOC™) measurements were made on a 2,942 kW (4,000 hp) EMD 16-710G3 locomotive diesel engine, as part of a program to evaluate prototype cylinder kits that hold the potential to reduce lubricating oil consumption and hence reduce exhaust particulate matter emissions towards meeting EPA Tier 0+ locomotive emissions certification. The DALOC technique uses sulfur dioxide (SO2) measured in the exhaust gas stream as a tracer for oil consumption. The engine was operated on an ultra-low sulfur diesel fuel (3 ppm by weight) and commercially available SAE grade 20W40 mineral-based lubricating oil (4,865 ppm by weight). Knowing the SO2 concentration in the exhaust, the air and fuel flow rates, and the lubricating oil consumption rate can be calculated in real-time, i.e. on a second-to-second basis. Use of this measurement technique on the locomotive engine application has proven to be a cost- and time-reducing tool for mapping steady-state lubricating oil consumption rate. Numerous prior publications describe the evolution of this technique over time as well as the prior art in the area of lubricant impact on emissions [1–12]. As part of this project, the lubricant oil consumption of 4 different cylinder kits were accurately quantified at 4 steady-state operating conditions typical of North American freight locomotive operation within less than 40 hours of actual engine running. Applying this measurement technique, a reduction of lubricant oil consumption of 75%+ in comparison to the baseline cylinder kits were documented.

Real-Time Digital Simulation and Analysis of Sliding Mode and P&O MPPT Algorithms for a PV System

2015 ◽  
Vol 16 (4) ◽  
pp. 313-322 ◽  
Author(s):  
Venkata Ratnam Kolluru ◽  
Kamalakanta Mahapatra ◽  
Bidyadhar Subudhi
Keyword(s):  
Steady State ◽  
Real Time ◽  
Sliding Mode ◽  
Boost Converter ◽  
Maximum Power ◽  
Sliding Mode Controller ◽  
Step Size ◽  
Pv System ◽  
Steady State Condition ◽  
Power Extraction

Abstract This paper presents an integral Sliding Mode Controller (SMC) of a DC-DC boost converter integrated with a photovoltaic (PV) system for maximum power extraction. In view of improving the steady-state performance of the maximum power point tracking (MPPT), an integral of the error term is included in the sliding surface. The output of PV panels is connected to a DC-DC boost converter to regulate and enhance the voltage up to a desired level. By using SMC with integral term, the steady-state condition is obtained at less than 0.1 sec. With the proposed ISMC MPPT the maximum power extracted is more than 10% than the traditional Perturb & Observe (P&O) MPPT at standard test conditions (STC). The results obtained using the SMC are compared with that of the fixed step size P&O MPPT controller. The performances of the proposed sliding mode controller and the P&O controller are validated through experimentations using a Real-Time Digital Simulator (RTDS)-Opal RT.

Multiobjective Dynamic Optimization of an Industrial Steam Reformer with Genetic Algorithms

2007 ◽  
Vol 5 (1) ◽  
Author(s):  
Ali Alizadeh ◽  
Navid Mostoufi ◽  
Farhang Jalali-Farahani
Keyword(s):  
Steady State ◽  
Dynamic Optimization ◽  
Synthesis Gas ◽  
Transition Period ◽  
Dynamic Condition ◽  
Homogeneous Model ◽  
Operating Conditions ◽  
Reactor Performance ◽  
Steady State Condition ◽  
Steam Reformer

An industrial steam reformer of a methanol plant was modeled at a dynamic condition in which a one dimensional homogeneous model was coupled with a verified kinetics from the literature. A close agreement was observed between the results of the model and industrial data from a real plant at steady state conditions. The open loop response of the system to switching between two operating conditions was investigated and shown that the produced synthesis gas during the transition period would be unsuitable for the downstream methanol converter. The genetic algorithm was then employed to perform a multi-objective dynamic optimization on the reactor performance in case of switching the feed and operating conditions. Maximization of methane conversion and minimization of a stoichiometric parameter, were considered as the two objectives' functions that were optimized for a fixed feed rate of methane to the existing unit. The results of the dynamic optimization for the specified reformer configuration were achieved after switching the operating condition. Results of the optimization showed that the produced synthesis gas would stay in its acceptable limits in terms of quality of the feed of the methanol converter and also, the final conversion of the reformer would be improved compared to the steady state condition. This procedure could be applied to the advanced process control of the methanol plant.

Thermal Management of Electronic Chips in a Channel Using Input Power to Control Flow Velocity

2009 ◽  
Vol 131 (1) ◽  
Author(s):  
Esam M. Alawadhi
Keyword(s):  
Steady State ◽  
Pressure Drop ◽  
Thermal Management ◽  
Heat Generation ◽  
Electronic Device ◽  
Thermal Characteristics ◽  
Input Power ◽  
Control Flow ◽  
Steady State Condition ◽  
Average Temperature

In this research, thermal management of an electronic device using the input power is investigated numerically using the finite element method. The considered geometry consists of a horizontal channel with three volumetrically heated chips mounted on the bottom wall of the channel. The magnitude of the channel’s inlet velocity is varied with the variation of heat generation in the chips. The thermal characteristics of the system are presented, and compared with thermal characteristics of a system at a steady state condition. The effect of the Reynolds number and the oscillating period of the heat generation on the chips’ average temperature and Nusselt number is presented. The pressure drop in the channel is also calculated. The results indicated that the transient operating condition causes temperature to be higher than steady state by more than 45%, and difference between the transient and steady operations is reduced if the frequency is high. However, flow frequency has nearly no effect on the pressure drop in the channel.

scholarly journals Dynamic Modeling of HVDC for Power System Stability Assessment: A Review, Issues, and Recommendations

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4829
Author(s):  
Tarek Abedin ◽  
M. Shahadat Hossain Lipu ◽  
Mahammad A. Hannan ◽  
Pin Jern Ker ◽  
Safwan A. Rahman ◽  
...  
Keyword(s):  
Steady State ◽  
Dynamic Modeling ◽  
Direct Current ◽  
Current Source ◽  
Computational Cost ◽  
Operating Conditions ◽  
System Stability ◽  
Voltage Source ◽  
Voltage Source Converter ◽  
Stability Assessment

High-voltage direct current (HVDC) has received considerable attention due to several advantageous features such as minimum transmission losses, enhanced stability, and control operation. An appropriate model of HVDC is necessary to assess the operating conditions as well as to analyze the transient and steady-state stabilities integrated with the AC networks. Nevertheless, the construction of an HVDC model is challenging due to the high computational cost, which needs huge ranges of modeling experience. Therefore, advanced dynamic modeling of HVDC is necessary to improve stability with minimum power loss. This paper presents a comprehensive review of the various dynamic modeling of the HVDC transmission system. In line with this matter, an in-depth investigation of various HVDC mathematical models is carried out including average-value modeling (AVM), voltage source converter (VSC), and line-commutated converter (LCC). Moreover, numerous stability assessment models of HVDC are outlined with regard to stability improvement models, current-source system stability, HVDC link stability, and steady-state rotor angle stability. In addition, the various control schemes of LCC-HVDC systems and modular multilevel converter- multi-terminal direct current (MMC-MTDC) are highlighted. This paper also identifies the key issues, the problems of the existing HVDC models as well as providing some selective suggestions for future improvement. All the highlighted insights in this review will hopefully lead to increased efforts toward the enhancement of the modeling for the HVDC system.

Deep learning procedure for knock, performance and emission prediction at steady-state condition of a gasoline engine

2020 ◽  
Vol 234 (14) ◽  
pp. 3347-3361
Author(s):  
Seunghyup Shin ◽  
Sangyul Lee ◽  
Minjae Kim ◽  
Jihwan Park ◽  
Kyoungdoug Min
Keyword(s):  
Deep Learning ◽  
Steady State ◽  
Gasoline Engine ◽  
Pressure Rise ◽  
Learning Model ◽  
Operating Conditions ◽  
Cylinder Pressure ◽  
Steady State Condition ◽  
Brake Mean Effective Pressure ◽  
Deep Learning Model

Recently, deep learning has played an important role in the rise of artificial intelligence, and its accuracy has gained recognition in various research fields. Although engine phenomena are very complicated, they can be predicted with high accuracy using deep learning because they are based on the fundamentals of physics and chemistry. In this research, models were built with deep neural networks for gasoline engine prediction. The model consists of two sub-models. The first predicts the knock occurrence, and the second predicts performance, combustion, and emissions. This includes maximum cylinder pressure, crank angle at maximum cylinder pressure, maximum pressure rise rate, and brake mean effective pressure, brake-specific fuel consumption, brake-specific nitrogen oxides, and brake-specific carbon oxide, which are representative results of the engine (for normal combustion cases without knock). Model input parameters were selected considering engine operating conditions, and physically measurable sensor values. For test cases, the accuracy of the first model for knock classification is 99.0%, and the coefficient of determination (R2) values for the second model are all above 0.99. Test times of both models were approximately 2 ms. The robustness of all the models was verified using K-fold cross-validation. A sensitivity study of accuracy, according to the amount of training utilized, was also conducted to determine how many data points are required to effectively train the deep learning model. Accordingly, a deep learning approach was applied to predict the steady-state conditions of a gasoline engine. Achieved model accuracies and robustness proved deep learning to be an effective modeling approach, and test time was recognized to be able to apply for the real-time prediction. The sensitivity analysis can be applied for the preliminary study to define the number of experimental points for the deep learning model.

Anomaly detection for heavy power generation gas turbine considering the effect of output power variation

2019 ◽  
Vol 234 (6) ◽  
pp. 795-803
Author(s):  
Zhong Wang ◽  
Yujiong Gu ◽  
Xudong Han ◽  
Junjie Zhu ◽  
Jiaohui Xu
Keyword(s):  
Power Generation ◽  
Steady State ◽  
Anomaly Detection ◽  
Gas Turbine ◽  
Output Power ◽  
Operating Conditions ◽  
Operating Parameters ◽  
Unsteady State ◽  
Steady State Condition ◽  
Positive Rate

In the frequency modulation process of the heavy power generation gas turbine, the variation of output power will cause the fluctuation of the operating parameters. In order to detect the anomaly of the true performance deterioration accurately, a novel statistical anomaly detection model was developed. First, the mathematical description of the operating parameters under three different operating conditions—unsteady-state, steady-state and normal, steady-state and anomaly—was presented according to the characteristics of parameters and output power. Second, the new characteristic test statistic P-ratio based on the T-statistic was proposed for the anomaly detection under the steady-state condition. Then, the on-line steady-state detection algorithm based on the Gaussian mixture model was built for the unsteady-state identification. Finally, the efficacy of the model was examined on the synthetic deterioration data, which superimposes the anomaly simulation signal data on the real healthy data from a real power generation gas turbine. The testing result is shown to be satisfactory with respect to the false positive rate and the true positive rate. Future research is required to further improve the accuracy of the proposed model.

Development and Experimental Validation of a Control-Oriented Diesel Engine Fuel Consumption and Brake Torque Predictive Model for Hybrid Powertrain Control Applications

2010 ◽  
Author(s):  
Fabio Chiara ◽  
Junmin Wang ◽  
Chinmaya B. Patil ◽  
Ming-Feng Hsieh ◽  
Fengjun Yan
Keyword(s):  
Steady State ◽  
Diesel Engine ◽  
Real Time ◽  
Fuel Consumption ◽  
Experimental Validation ◽  
Operating Conditions ◽  
Engine Fuel ◽  
Real Time Control ◽  
Brake Torque ◽  
Highly Nonlinear

This paper describes the development and experimental validation of a control-oriented, real-time-capable, Diesel engine instantaneous fuel consumption and brake torque model under warmed-up conditions. Such a model, with the capability of reliably and computationally-efficiently estimating the aforementioned variables at steady-state and transient engine operating conditions, can be utilized in the context of real-time control and optimization of hybrid powertrains. The only two inputs of the model are the torque request and the engine speed. While Diesel engine dynamics are highly nonlinear and very complex, by considering the Diesel engine and its control system (engine control unit (ECU)) together as an entity, it becomes possible to predict the engine instantaneous fuel consumption and torque based on only the two inputs. A synergy between different modeling methodologies including physically-based grey-box and data-driven black-box approaches were integrated in the Diesel engine model. The fueling and torque predictions have been validated by means of FTP72 test cycle experimental data from a medium-duty Diesel engine at steady-state and transient operations.

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