scholarly journals Comparison of Plug Flow and Multi-Node Stratified Tank Modeling Approaches Regarding Computational Efficiency and Accuracy

2020 ◽  
Author(s):  
Fernando Karg Bulnes ◽  
Kyle R. Gluesenkamp ◽  
Joseph Rendall
Keyword(s):  
Experimental Data ◽  
Thermal Stratification ◽  
Mean Squared Error ◽  
Plug Flow ◽  
Computational Effort ◽  
Computational Time ◽  
Water Tank ◽  
Water Heaters ◽  
External Process ◽  
Numerical Computing

Abstract Residential water heaters contain water stratified by temperature-driven density differences. This implies that a water tank can reach a state in which the top and bottom sections have different temperatures, unless mixing happens. A high degree of thermal stratification can improve the efficiency of some water heaters, by saving the amount of energy required for the heat-up process. Studies of stratification became popular in the 1970s and it remains an active research topic today. The research has led to the development of different models and techniques to better predict and define a stratified tanks behavior. By comparing these models and techniques used previously to describe thermal stratification, the phenomenon could be better understood, exploited, and used to increase efficiency and thermal energy capacity in modern water tanks. From the existing models, we found the one-dimensional standard plug-flow and a multi node model to be appropriate for analyzing the processes of the heat up and cool-down in a water tank. These two models are based on energy balances. This work involved comparing the accuracy and computational effort needed to implement these models. To assess accuracy, we compared both types of existing models to experimental data (also collected in this work) which included a heat up process using an external heat pump. This external process included a layering process that has an eddy diffusivity at five times the rate of thermal diffusion. For this project, we implemented the models in MATLAB, the multi-paradigm numerical computing environment. We quantified model accuracy using the root mean squared error between modeled data and experimental data for six measured tank temperatures. Comparing the accuracy and the computational time taken to run the simulation provides a method to contrast the performance of each model and a way to rate it. The multi node model was run using from 6 to 96 spatial nodes; the plug flow model was run using 1 to 0.001 °C temperature bin sizes. Additionally, timesteps were varied from 4 to 236 s. The results quantify the tradeoff between accuracy and computational time, providing guidance for simulations to intelligently select the best model type and simulation parameters. This research can be used to validate the pre-existing models and possibly improve the modern water tank.

scholarly journals Characterization of Wrapped Coil Tank Water Heater During Charging/Discharging

2017 ◽  
Author(s):  
Ahmed Elatar ◽  
Kashif Nawaz ◽  
Bo Shen ◽  
Van Baxter ◽  
Omar Abdelaziz
Keyword(s):  
Water Temperature ◽  
Heat Pump ◽  
Thermal Stratification ◽  
Water Tank ◽  
Water Heater ◽  
Water Heaters ◽  
Discharge Flow Rate ◽  
Circulation Patterns ◽  
The Impact ◽  
Supply Water

Heat pump water heaters (HPWH) are an energy efficient method for water heating compared to conventional electric water heaters. A wrapped coil around the water tank is often used as the condenser for the heat pump for such applications. Thermal stratification, caused by varying heat transfer rate from the condenser to the water depending on the phase of the refrigerant and the wrap configuration, is often observed inside the tank, especially for HPWHs using CO2 as the refrigerant. The current study investigates the impact of the charging/discharging process on thermal stratification. A series of simulations were conducted based on the draw patterns recommended by the DOE method of test for rating water heater performance. We also analyzed the water circulation patterns during charging/discharging process. The thermal stratification was adversely affected because of the circulation even when the Heat Pump (HP) was operational. It was observed that a relatively higher charge/discharge flow rate disrupts the thermal stratification quickly and thus lowers the supply water temperature. Furthermore, the duration of charging/discharging also plays an important role. It was noticed that the back flow has insignificant effect on the supply water temperature if charging/discharging time is relatively small. However, the effect was obvious for larger water draw flow rates that last for longer time.

scholarly journals A Novel Methodology for Hydrocarbon Depth Prediction in Seabed Logging: Gaussian Process-Based Inverse Modeling of Electromagnetic Data

2021 ◽  
Vol 11 (4) ◽  
pp. 1492
Author(s):  
Hanita Daud ◽  
Muhammad Naeim Mohd Aris ◽  
Khairul Arifin Mohd Noh ◽  
Sarat Chandra Dass
Keyword(s):  
Gaussian Process ◽  
Inverse Modeling ◽  
Mean Squared Error ◽  
Computational Effort ◽  
Percentage Error ◽  
Depth Prediction ◽  
Receiver System ◽  
Realistic Representation ◽  
And Performance ◽  
Gp Model

Seabed logging (SBL) is an application of electromagnetic (EM) waves for detecting potential marine hydrocarbon-saturated reservoirs reliant on a source–receiver system. One of the concerns in modeling and inversion of the EM data is associated with the need for realistic representation of complex geo-electrical models. Concurrently, the corresponding algorithms of forward modeling should be robustly efficient with low computational effort for repeated use of the inversion. This work proposes a new inversion methodology which consists of two frameworks, namely Gaussian process (GP), which allows a greater flexibility in modeling a variety of EM responses, and gradient descent (GD) for finding the best minimizer (i.e., hydrocarbon depth). Computer simulation technology (CST), which uses finite element (FE), was exploited to generate prior EM responses for the GP to evaluate EM profiles at “untried” depths. Then, GD was used to minimize the mean squared error (MSE) where GP acts as its forward model. Acquiring EM responses using mesh-based algorithms is a time-consuming task. Thus, this work compared the time taken by the CST and GP in evaluating the EM profiles. For the accuracy and performance, the GP model was compared with EM responses modeled by the FE, and percentage error between the estimate and “untried” computer input was calculated. The results indicate that GP-based inverse modeling can efficiently predict the hydrocarbon depth in the SBL.

Experimental Validation of Forced Response Methods in a Multi-Stage Axial Turbine

2018 ◽  
Author(s):  
Thomas Hauptmann ◽  
Christopher E. Meinzer ◽  
Joerg R. Seume
Keyword(s):  
Experimental Data ◽  
Vibration Amplitude ◽  
Turbine Blades ◽  
Service Condition ◽  
Sensitivity Study ◽  
Forced Response ◽  
Tip Clearance ◽  
Computational Time ◽  
Reference Case ◽  
Axial Turbine

Depending on the in service condition of jet engines, turbine blades may have to be replaced, refurbished, or repaired in the course of an engine overhaul. Thus, significant changes of the turbine blade geometry can be introduced due to regeneration and overhaul processes. Such geometric variances can affect the aerodynamic and aeroelastic behavior of turbine blades. One goal in the development of the regeneration process is to estimate the aerodynamic excitation of turbine blades depending on these geometric variances caused during the regeneration. Therefore, this study presents an experimentally validated comparison of two methods for the prediction of forced response in a multistage axial turbine. Two unidirectional fluid structure interaction (FSI) methods, a time-linearized and a time-accurate with a subsequent linear harmonic analysis, are employed and the results validated against experimental data. The results show that the vibration amplitude of the time-linearized method is in good agreement with the experimental data and, also requires lower computational time than the time-accurate FSI. Based on this result, the time-linearized method is used to perform a sensitivity study of the tip clearance size of the last rotor blade row of the five stage axial turbine. The results show that an increasing tip clearances size causes an up to 1.35 higher vibration amplitude compared to the reference case, due to increased forcing and decreased damping work.

Integrated Redesign of Large-Scale Structures by Large Admissible Perturbations

2003 ◽  
Vol 125 (4) ◽  
pp. 234-241 ◽  
Author(s):  
Vincent Y. Blouin ◽  
Michael M. Bernitsas ◽  
Denby Morrison
Keyword(s):  
Degrees Of Freedom ◽  
Large Scale ◽  
Direct Method ◽  
Computational Effort ◽  
Forced Response ◽  
Response Amplitude ◽  
Computational Time ◽  
Performance Constraints ◽  
Large Admissible Perturbations ◽  
Design Selection

In structural redesign (inverse design), selection of the number and type of performance constraints is a major challenge. This issue is directly related to the computational effort and, most importantly, to the success of the optimization solver in finding a solution. These issues are the focus of this paper, which provides and discusses techniques that can help designers formulate a well-posed integrated complex redesign problem. LargE Admissible Perturbations (LEAP) is a general methodology, which solves redesign problems of complex structures with, among others, free vibration, static deformation, and forced response amplitude constraints. The existing algorithm, referred to as the Incremental Method is improved in this paper for problems with static and forced response amplitude constraints. This new algorithm, referred to as the Direct Method, offers comparable level of accuracy for less computational time and provides robustness in solving large-scale redesign problems in the presence of damping, nonstructural mass, and fluid-structure interaction effects. Common redesign problems include several natural frequency constraints and forced response amplitude constraints at various frequencies of excitation. Several locations on the structure and degrees of freedom can be constrained simultaneously. The designer must exercise judgment and physical intuition to limit the number of constraints and consequently the computational time. Strategies and guidelines are discussed. Such techniques are presented and applied to a 2,694 degree of freedom offshore tower.

scholarly journals Simulation of olive pits pyrolysis in a rotary kiln plant

2011 ◽  
Vol 15 (1) ◽  
pp. 145-158 ◽  
Author(s):  
Enzo Benanti ◽  
Cesare Freda ◽  
Vincenzo Lorefice ◽  
Giacobbe Braccio ◽  
Vinod Sharma
Keyword(s):  
Experimental Data ◽  
Temperature Profile ◽  
Rotary Kiln ◽  
Southern Italy ◽  
Flow Reactor ◽  
Plug Flow ◽  
Sensitivity Analyses ◽  
Pyrolysis Process ◽  
Simulation Results ◽  
Main Component

This work deals with the simulation of an olive pits fed rotary kiln pyrolysis plant installed in Southern Italy. The pyrolysis process was simulated by commercial software CHEMCAD. The main component of the plant, the pyrolyzer, was modelled by a Plug Flow Reactor in accordance to the kinetic laws. Products distribution and the temperature profile was calculated along reactor's axis. Simulation results have been found to fit well the experimental data of pyrolysis. Moreover, sensitivity analyses were executed to investigate the effect of biomass moisture on the pyrolysis process.

scholarly journals Heat Transfer Analysis of Passive Residual Heat Removal Heat Exchanger under Natural Convection Condition in Tank

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Qiming Men ◽  
Xuesheng Wang ◽  
Xiang Zhou ◽  
Xiangyu Meng
Keyword(s):  
Heat Transfer ◽  
Heat Exchanger ◽  
Thermal Stratification ◽  
Heat Removal ◽  
Heat Transfer Analysis ◽  
Average Error ◽  
Water Tank ◽  
Shaped Tube ◽  
Heat Transfer Calculation ◽  
Residual Heat

Aiming at the heat transfer calculation of the Passive Residual Heat Removal Heat Exchanger (PRHR HX), experiments on the heat transfer of C-shaped tube immerged in a water tank were performed. Comparisons of different correlation in literatures with the experimental data were carried out. It can be concluded that the Dittus-Boelter correlation provides a best-estimate fit with the experimental results. The average error is about 0.35%. For the tube outside, the McAdams correlations for both horizontal and vertical regions are best-estimated. The average errors are about 0.55% for horizontal region and about 3.28% for vertical region. The tank mixing characteristics were also investigated in present work. It can be concluded that the tank fluid rose gradually which leads to a thermal stratification phenomenon.

Numerical Investigation of Thermal Separators Within the Evacuated Tubes of a Water-in-Glass Solar Water Heater

2018 ◽  
Vol 140 (6) ◽  
Author(s):  
Asif Soopee ◽  
Abdel Anwar Hossen Khoodaruth ◽  
Anshu Prakash Murdan ◽  
Vishwamitra Oree
Keyword(s):  
Tilt Angle ◽  
Thermal Efficiency ◽  
Thermal Stratification ◽  
Maximum Deviation ◽  
Water Tank ◽  
Solar Water Heater ◽  
Water Heater ◽  
Solar Water ◽  
Thermal Distribution ◽  
Evacuated Tubes

The effects of thermal separators within the evacuated tubes of a water-in-glass solar water heater (SWH) were numerically investigated using the commercial computational fluid dynamics (CFD) software ANSYS fluent. To validate the three-dimensional (3D) model, an experiment was performed for the passive operation of the SWH for a fortnight period, of which 3 h of recorded data was selected. The Boussinesq's approximation was employed, and the respective solar irradiance and ambient temperature profiles were incorporated. A maximum deviation of only 2.06% was observed between the experimental and numerical results. The model was then adapted for the case where thermal separators are inserted within the evacuated tubes of the SWH and both cases were run for two tilt angles, 10 deg and 40 deg. The temperature and velocity profiles within the evacuated tubes were analyzed alongside the temperature contours, thermal stratification, and overall thermal efficiency of the SWH. At a 40 deg tilt, without thermal separators, the flow streams within the evacuated tubes are restrained, and a chaotic thermal behavior was observed, thereby restricting thermal distribution to the water stored in the SWH tank. A lower tilt angle (10 deg) provided a more desirable thermal distribution. With thermal separators, however, the tilt angle preference was reversed. A faster and more uniform thermal distribution was achieved within the water tank, with a sizeable reduction in the thermal stratification at a 40 deg tilt. The overall thermal efficiency of the SWH was improved by 4.11% and 4.14% for tilt angles of 10 deg and 40 deg, respectively.

Recycling and Extraction of Zinc Ions in Disc-Donut Column Considering Forward Mixing Mass Transfer, Chemical Reaction and Effects of Pulsed and non-Pulsed Condition

2021 ◽  
Author(s):  
Mehdi Asadollahzadeh ◽  
Rezvan Torkaman ◽  
Meisam Torab-Mostaedi ◽  
Mojtaba Saremi
Keyword(s):  
Experimental Data ◽  
Mass Transfer ◽  
Flow Rate ◽  
Positive Impact ◽  
Plug Flow ◽  
Model Parameters ◽  
Zinc Ions ◽  
Zinc Extraction ◽  
Balance Equations ◽  
Transfer Rates

Abstract The current study focuses on the recovery of zinc ions by solvent extraction in the pulsed contactor. The Zn(II) ions from chloride solution were extracted into the organic phase containing D2EHPA extractant. The resulting data were characterized for the relative amount of (a) pulsed and no-pulsed condition; and (b) flow rate of both phases. Based on the mass balance equations for the column performance description, numerical computations of mass transfer in a disc-donut column were conducted and validated the experimental data for zinc extraction. Four different models, such as plug flow, backflow, axial dispersion, and forward mixing were evaluated in this study. The results showed that the intensification of the process with the pulsed condition increased and achieved higher mass transfer rates. The forward mixing model findings based on the curve fitting approach validated well with the experimental data. The results showed that an increase in pulsation intensity, as well as the phase flow rates, have a positive impact on the performance of the extractor, whereas the enhancement of flow rate led to the reduction of the described model parameters for adverse phase.

A Novel Approach to Detect Abnormal Chest X-rays of COVID-19 Patients Using Image Processing and Deep Learning

2021 ◽  
pp. 23-41
Author(s):  
Subhagata Chattopadhyay
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Hessian Matrix ◽  
Region Of Interest ◽  
Computational Time ◽  
X Rays ◽  
Feed Forward Neural Network ◽  
Novel Approach ◽  
Input Dataset

The study proposes a novel approach to automate classifying Chest X-ray (CXR) images of COVID-19 positive patients. All acquired images have been pre-processed with Simple Median Filter (SMF) and Gaussian Filter (GF) with kernel size (5, 5). The better filter is then identified by comparing Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) of denoised images. Canny's edge detection has been applied to find the Region of Interest (ROI) on denoised images. Eigenvalues [-2, 2] of the Hessian matrix (5 × 5) of the ROIs are then extracted, which constitutes the 'input' dataset to the Feed Forward Neural Network (FFNN) classifier, developed in this study. Eighty percent of the data is used for training the said network after 10-fold cross-validation and the performance of the network is tested with the remaining 20% of the data. Finally, validation has been made on another set of 'raw' normal and abnormal CXRs. Precision, Recall, Accuracy, and Computational time complexity (Big(O)) of the classifier are then estimated to examine its performance.

Data-driven seismic response prediction of structural components

2021 ◽  
pp. 875529302110533
Author(s):  
Huan Luo ◽  
Stephanie German Paal
Keyword(s):  
Experimental Data ◽  
Seismic Response ◽  
Computational Cost ◽  
Data Driven ◽  
Computational Time ◽  
Lateral Stiffness ◽  
Hysteretic Model ◽  
Structural Components ◽  
Rc Columns ◽  
Detailed Model

Lateral stiffness of structural components, such as reinforced concrete (RC) columns, plays an important role in resisting the lateral earthquake loads. The lateral stiffness relates the lateral force to the lateral deformation, having a critical effect on the accuracy of the lateral seismic response predictions. The classical methods (e.g. fiber beam–column model) to estimate the lateral stiffness require calculations from section, element, and structural levels, which is time-consuming. Moreover, the shear deformation and bond-slip effect may also need to be included to more accurately calculate the lateral stiffness, which further increases the modeling difficulties and the computational cost. To reduce the computational time and enhance the accuracy of the predictions, this article proposes a novel data-driven method to predict the laterally seismic response based on the estimated lateral stiffness. The proposed method integrates the machine learning (ML) approach with the hysteretic model, where ML is used to compute the parameters that govern the nonlinear properties of the lateral response of target structural components directly from a training set composed of experimental data (i.e. data-driven procedure) and the hysteretic model is used to directly output the lateral stiffness based on the computed parameters and then to perform the seismic analysis. We apply the proposed method to predict the lateral seismic response of various types of RC columns subjected to cyclic loading and ground motions. We present the detailed model formulation for the application, including the developments of a modified hysteretic model, a hybrid optimization algorithm, and two data-driven seismic response solvers. The results predicted by the proposed method are compared with those obtained by classical methods with the experimental data serving as the ground truth, showing that the proposed method significantly outperforms the classical methods in both generalized prediction capabilities and computational efficiency.

Sign in / Sign up

Export Citation Format

Share Document