A Research on Waste-Gated Turbine Performance Under Unsteady Flow Condition

2016 ◽  
Author(s):  
Q. Deng ◽  
R. D. Burke ◽  
Q. Zhang ◽  
Ludek Pohorelsky
Keyword(s):  
Mass Flow ◽  
Thermal Inertia ◽  
Cold Start ◽  
Dynamic Responses ◽  
Model Parameters ◽  
Transfer Model ◽  
Frequency Range ◽  
Mechanism Model ◽  
Housing Temperature ◽  
Unsteady Flow Condition

Turbochargers are key components of engine air-paths that must be carefully considered during the development process. The combination of fluid, mechanical and thermal phenomenon make the turbocharger a highly dynamic and non-linear modelling challenge. The aim of this study is to quantify the dynamic response of the turbocharger system across a frequency spectrum from 0.003Hz to 500Hz, i.e. for exhaust gas pulsation in steady state, load steps and cold start drive cycles, to validate the assumption of quasi-steady assumptions for particular modelling problems. A waste-gated turbine was modelled using the dual orifice approach, a lumped capacitance heat transfer model and novel, physics-based pneumatic actuator mechanism model. Each sub-model has been validated individually against experimental measurements. The turbine inlet pressure and temperature and the waste-gate actuator pressure were perturbed across the full frequency range both individually and simultaneously in separate numerical investigations. The dynamic responses of turbine housing temperature, turbocharger rotor speed, waste-gate opening, mass flow and gas temperatures/pressures were all investigated. The mass flow parameter exhibits significant dynamic behaviour above 100Hz, illustrating that the quasi-steady assumption is invalid in this frequency range. The waste-gate actuator system showed quasi-steady behaviour below 10Hz, while the mechanical inertia of the turbine attenuated fluctuations in shaft speed for frequencies between 0.1–10Hz. The thermal inertia of the turbocharger housing meant that housing temperature variations were supressed at frequencies above 0.01Hz. The results have been used to illustrate the importance of model parameters for three transient simulation scenarios (cold start, load step and pulsating exhaust flow).

A Research on Waste-Gated Turbine Performance Under Unsteady Flow Condition

2017 ◽  
Vol 139 (6) ◽  
Author(s):  
Q. Deng ◽  
R. D. Burke ◽  
Q. Zhang ◽  
Ludek Pohorelsky
Keyword(s):  
Mass Flow ◽  
Nonlinear Modeling ◽  
Thermal Inertia ◽  
Cold Start ◽  
Dynamic Responses ◽  
Model Parameters ◽  
Transfer Model ◽  
Frequency Range ◽  
Mechanism Model ◽  
Housing Temperature

Turbochargers are key components of engine air-paths that must be carefully considered during the development process. The combination of fluid, mechanical, and thermal phenomenon make the turbocharger a highly dynamic and nonlinear modeling challenge. The aim of this study is to quantify the dynamic response of the turbocharger system across a frequency spectrum from 0.003 Hz to 500 Hz, i.e., for exhaust gas pulsation in steady state, load steps, and cold start drive cycles, to validate the assumption of quasi-steady assumptions for particular modeling problems. A waste-gated turbine was modeled using the dual orifice approach, a lumped capacitance heat transfer model, and novel, physics-based pneumatic actuator mechanism model. Each submodel has been validated individually against the experimental measurements. The turbine inlet pressure and temperature and the waste-gate actuator pressure were perturbed across the full frequency range both individually and simultaneously in separate numerical investigations. The dynamic responses of turbine housing temperature, turbocharger rotor speed, waste-gate opening, mass flow, and gas temperatures/pressures were all investigated. The mass flow parameter exhibits significant dynamic behavior above 100 Hz, illustrating that the quasi-steady assumption is invalid in this frequency range. The waste-gate actuator system showed quasi-steady behavior below 10 Hz, while the mechanical inertia of the turbine attenuated fluctuations in shaft speed for frequencies between 0.1 and 10 Hz. The thermal inertia of the turbocharger housing meant that housing temperature variations were supressed at frequencies above 0.01 Hz. The results have been used to illustrate the importance of model parameters for three transient simulation scenarios (cold start, load step, and pulsating exhaust flow).

A Novel Method to Estimate Parameters of the Wall-Wetting Fuel Model in MPFI Engines for Cold Start and Warm Up Conditions

2004 ◽  
Author(s):  
M. Shahbakhti ◽  
M. Ghafuri ◽  
A. R. Aslani ◽  
A. Sahraeian ◽  
S. A. Jazayeri ◽  
...  
Keyword(s):  
Fuel Injection ◽  
Cold Start ◽  
Spark Ignition Engine ◽  
Intake Manifold ◽  
Exhaust Emission ◽  
Model Parameters ◽  
Transfer Model ◽  
Fuel Film ◽  
Warm Up ◽  
Fuel Ratio

In order to fulfill the LEV/ULEV exhaust emission standards, it is necessary to have a precise control of air fuel ratio under transient conditions especially during cold start and warm up periods. The objective in this study was to estimate parameters of a fuel delivery model and use them to provide a correct fuel injection compensation strategy. In this study, fuel transfer characteristics of intake port of a typical fuel-injected spark ignition engine have been determined for engine warm-up conditions following cold starts at temperature down to −15°C and extending to fully-warmed-up conditions, using a method based upon perturbing fuel injection rate and recording AFR (Air Fuel Ratio) response. Since there was no cold chamber available to perform tests in cold start conditions, a new method was utilized to simulate cold start conditions. This method can be used on any PFI engine with closed valve injection strategy. Following the estimation of fuel transfer model parameters, the variation of fuel film deposit factor (X), fuel film evaporation time constant (τf) and transport delay to oxygen sensor (ΔT) parameters over a range of temperatures, engine speeds and intake manifold pressures have been evaluated, providing a good insight to define transient fuel compensation requirements for cold start and warm up conditions.

Transient Behavior of Glow Plugs in Direct-Injection Natural Gas Engines

2012 ◽  
Vol 134 (9) ◽  
Author(s):  
Stewart Xu Cheng ◽  
James S. Wallace
Keyword(s):  
Heat Transfer ◽  
Natural Gas ◽  
Direct Injection ◽  
High Surface ◽  
Cold Start ◽  
Transfer Model ◽  
Ignition Process ◽  
Computational Domain ◽  
Glow Plug ◽  
Natural Gas Engines

Glow plugs are a possible ignition source for direct injected natural gas engines. This ignition assistance application is much different than the cold start assist function for which most glow plugs have been designed. In the cold start application, the glow plug is simply heating the air in the cylinder. In the cycle-by-cycle ignition assist application, the glow plug needs to achieve high surface temperatures at specific times in the engine cycle to provide a localized source of ignition. Whereas a simple lumped heat capacitance model is a satisfactory representation of the glow plug for the air heating situation, a much more complex situation exists for hot surface ignition. Simple measurements and theoretical analysis show that the thickness of the heat penetration layer is small within the time scale of the ignition preparation period (1–2 ms). The experiments and analysis were used to develop a discretized representation of the glow plug domain. A simplified heat transfer model, incorporating both convection and radiation losses, was developed for the discretized representation to compute heat transfer to and from the surrounding gas. A scheme for coupling the glow plug model to the surrounding gas computational domain in the KIVA-3V engine simulation code was also developed. The glow plug model successfully simulates the natural gas ignition process for a direct-injection natural gas engine. As well, it can provide detailed information on the local glow plug surface temperature distribution, which can aid in the design of more reliable glow plugs.

scholarly journals Investigations Concerning the Residence Time Distribution of Twin-Screw-Extrusion Processes as Indicator for Inherent Mixing

Pharmaceutics ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 207 ◽  
Author(s):  
Jens Wesholowski ◽  
Andreas Berghaus ◽  
Markus Thommes
Keyword(s):  
Residence Time ◽  
Mass Flow ◽  
Time Distribution ◽  
Residence Time Distribution ◽  
Dispersion Model ◽  
Model Parameters ◽  
Twin Screw Extrusion ◽  
Characteristic Model ◽  
Screw Extrusion ◽  
Twin Screw

Over recent years Twin-Screw-Extrusion (TSE) has been established as a platform technology for pharmaceutical manufacturing. Compared to other continuous operation, one of the major benefits of this method is the combination of several unit operations within one apparatus. Several of these are linked to the Residence Time Distribution (RTD), which is typically expressed by the residence time density function. One relevant aspect for pharmaceutical processes is the mixing capacity, which is represented by the width of this distribution. In the frame of this study the influence of the mass flow, the temperature and the screw-barrel clearance were investigated for a constant barrel load (specific feed load, SFL). While the total mass flow as well as the external screw diameter affected the mixing performance, the barrel temperature had no influence for the investigated range. The determined results were additionally evaluated with respect to a fit to the Twin-Dispersion-Model (TDM). This model is based on the superimposition of two mixing functions. The correlations between varied process parameters and the obtained characteristic model parameters proved this general physical view on extrusion.

Evaluation of Cathode Air Flow Transients in a SOFC/GT Hybrid System Using Hardware in the Loop Simulation

2014 ◽  
Author(s):  
Nana Zhou ◽  
Chen Yang ◽  
David Tucker
Keyword(s):  
Fuel Cell ◽  
Gas Turbine ◽  
Hybrid System ◽  
Mass Flow ◽  
Cell System ◽  
Department Of Energy ◽  
Dynamic Responses ◽  
Partial Recovery ◽  
Fuel Cell System ◽  
Air Mass

Thermal management in the fuel cell component of a direct fired solid oxide fuel cell gas turbine (SOFC/GT) hybrid power system, especially during an imposed load transient, can be improved by effective management and control of the cathode air mass flow. The response of gas turbine hardware system and the fuel cell stack to the cathode air mass flow transient was evaluated using a hardware-based simulation facility designed and built by the U.S. Department of Energy, National Energy Technology Laboratory (NETL). The disturbances of the cathode air mass flow were accomplished by diverting air around the fuel cell system through the manipulation of a hot-air bypass valve in open loop experiments. The dynamic responses of the SOFC/GT hybrid system were studied in this paper. The evaluation included distributed temperatures, current densities, heat generation and losses along the fuel cell over the course of the transient along with localized temperature gradients. The reduction of cathode air mass flow resulted in a sharp decrease and partial recovery of the thermal effluent from the fuel cell system in the first 10 seconds. In contrast, the turbine rotational speed did not exhibit a similar trend. The collection of distributed fuel cell and turbine trends obtained will be used in the development of controls to mitigate failure and extend life during operational transients.

scholarly journals Quantifying location error to define uncertainty in volcanic mass flow hazard simulations

2021 ◽  
Vol 21 (8) ◽  
pp. 2447-2460
Author(s):  
Stuart R. Mead ◽  
Jonathan Procter ◽  
Gabor Kereszturi
Keyword(s):  
Mass Flow ◽  
Performance Metrics ◽  
Numerical Models ◽  
Model Performance ◽  
Flow Simulation ◽  
Model Complexity ◽  
Model Parameters ◽  
Spatial Covariance ◽  
Trade Offs ◽  
Pixel Pair

Abstract. The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty in correct values of model parameters), a lack of model uncertainty quantification, and limited approaches to incorporate this uncertainty into hazard maps. When quantified, mass flow simulation errors are typically evaluated on a pixel-pair basis, using the difference between simulated and observed (“actual”) map-cell values to evaluate the performance of a model. However, these comparisons conflate location and quantification errors, neglecting possible spatial autocorrelation of evaluated errors. As a result, model performance assessments typically yield moderate accuracy values. In this paper, similarly moderate accuracy values were found in a performance assessment of three depth-averaged numerical models using the 2012 debris avalanche from the Upper Te Maari crater, Tongariro Volcano, as a benchmark. To provide a fairer assessment of performance and evaluate spatial covariance of errors, we use a fuzzy set approach to indicate the proximity of similarly valued map cells. This “fuzzification” of simulated results yields improvements in targeted performance metrics relative to a length scale parameter at the expense of decreases in opposing metrics (e.g. fewer false negatives result in more false positives) and a reduction in resolution. The use of this approach to generate hazard zones incorporating the identified uncertainty and associated trade-offs is demonstrated and indicates a potential use for informed stakeholders by reducing the complexity of uncertainty estimation and supporting decision-making from simulated data.

scholarly journals A transfer learning framework based on motor imagery rehabilitation for stroke

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fangzhou Xu ◽  
Yunjing Miao ◽  
Yanan Sun ◽  
Dongju Guo ◽  
Jiali Xu ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Motor Imagery ◽  
Stroke Rehabilitation ◽  
Transfer Functions ◽  
Model Parameters ◽  
Transfer Model ◽  
Learning Networks ◽  
Training Time ◽  
Fine Tune ◽  
Bci System

AbstractDeep learning networks have been successfully applied to transfer functions so that the models can be adapted from the source domain to different target domains. This study uses multiple convolutional neural networks to decode the electroencephalogram (EEG) of stroke patients to design effective motor imagery (MI) brain-computer interface (BCI) system. This study has introduced ‘fine-tune’ to transfer model parameters and reduced training time. The performance of the proposed framework is evaluated by the abilities of the models for two-class MI recognition. The results show that the best framework is the combination of the EEGNet and ‘fine-tune’ transferred model. The average classification accuracy of the proposed model for 11 subjects is 66.36%, and the algorithm complexity is much lower than other models.These good performance indicate that the EEGNet model has great potential for MI stroke rehabilitation based on BCI system. It also successfully demonstrated the efficiency of transfer learning for improving the performance of EEG-based stroke rehabilitation for the BCI system.

scholarly journals Summertime canopy albedo is sensitive to forest thinning

2013 ◽  
Vol 10 (9) ◽  
pp. 15373-15414 ◽  
Author(s):  
J. Otto ◽  
D. Berveiller ◽  
F.-M. Bréon ◽  
N. Delpierre ◽  
G. Geppert ◽  
...  
Keyword(s):  
Forest Management ◽  
Tree Species ◽  
Structural Changes ◽  
Near Infrared ◽  
Canopy Structure ◽  
Model Parameters ◽  
Transfer Model ◽  
Forest Thinning ◽  
Crown Volume ◽  
The Difference

Abstract. Despite an emerging body of literature linking canopy albedo to forest management, understanding of the process is still fragmented. We combined a stand-level forest gap model with a canopy radiation transfer model and satellite-derived model parameters to quantify the effects of forest thinning, that is removing trees at a certain time during the forest rotation, on summertime canopy albedo. The effects of different forest species (pine, beech, oak) and four thinning strategies (light to intense thinning regimes) were examined. During stand establishment, summertime canopy albedo is driven by tree species. In the later stages of stand development, the effect of tree species on summertime canopy albedo decreases in favour of an increasing influence of forest thinning on summertime canopy albedo. These trends continue until the end of the rotation where thinning explains up to 50% of the variance in near-infrared canopy albedo and up to 70% of the variance in visible canopy albedo. More intense thinning lowers the summertime shortwave albedo in the canopy by as much as 0.02 compared to unthinned forest. The structural changes associated with forest thinning can be described by the change in LAI in combination with crown volume. However, forests with identical canopy structure can have different summertime albedo values due to their location: the further north a forest is situated, the more the solar zenith angle increases and thus the higher is the summertime canopy albedo, independent of the wavelength. Despite the increase of absolute summertime canopy albedo values with latitude, the difference in canopy albedo between managed and unmanaged forest decreases with increasing latitude. Forest management thus strongly altered summertime forest albedo.

scholarly journals Quantifying location error to define uncertainty in volcanic mass flow hazard simulations

2021 ◽  
Author(s):  
Stuart R. Mead ◽  
Jonathan Procter ◽  
Gabor Kereszturi
Keyword(s):  
Mass Flow ◽  
Performance Metrics ◽  
Numerical Models ◽  
Model Performance ◽  
Flow Simulation ◽  
Model Complexity ◽  
Model Parameters ◽  
Spatial Covariance ◽  
Trade Offs ◽  
Pixel Pair

Abstract. The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty in correct values of model parameters), a lack of model uncertainty quantification, and limited approaches to incorporate this uncertainty into hazard maps. When quantified, mass flow simulation errors are typically evaluated on a pixel-pair basis, using the difference between simulated and observed (actual) map-cell values to evaluate the performance of a model. However, these comparisons conflate location and quantification errors, neglecting possible spatial autocorrelation of evaluated errors. As a result, model performance assessments typically yield moderate accuracy values. In this paper, similarly moderate accuracy values were found in a performance assessment of three depth-averaged numerical models using the 2012 debris avalanche from the Upper Te Maari crater, Tongariro Volcano as a benchmark. To provide a fairer assessment of performance and evaluate spatial covariance of errors, we use a fuzzy set approach to indicate the proximity of similarly valued map cells. This fuzzification of simulated results yields improvements in targeted performance metrics relative to a length scale parameter, at the expense of decreases in opposing metrics (e.g. less false negatives results in more false positives) and a reduction in resolution. The use of this approach to generate hazard zones incorporating the identified uncertainty and associated trade-offs is demonstrated, and indicates a potential use for informed stakeholders by reducing the complexity of uncertainty estimation and supporting decision making from simulated data.

scholarly journals Learning to Learn Morphological Inflection for Resource-Poor Languages

2020 ◽  
Vol 34 (05) ◽  
pp. 8058-8065
Author(s):  
Katharina Kann ◽  
Samuel R. Bowman ◽  
Kyunghyun Cho
Keyword(s):  
Fine Tuning ◽  
Target Language ◽  
Model Parameters ◽  
Transfer Model ◽  
Absolute Accuracy ◽  
Learning To Learn ◽  
Suggested Approach ◽  
High Resource ◽  
Resource Poor ◽  
Cross Lingual

We propose to cast the task of morphological inflection—mapping a lemma to an indicated inflected form—for resource-poor languages as a meta-learning problem. Treating each language as a separate task, we use data from high-resource source languages to learn a set of model parameters that can serve as a strong initialization point for fine-tuning on a resource-poor target language. Experiments with two model architectures on 29 target languages from 3 families show that our suggested approach outperforms all baselines. In particular, it obtains a 31.7% higher absolute accuracy than a previously proposed cross-lingual transfer model and outperforms the previous state of the art by 1.7% absolute accuracy on average over languages.

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