scholarly journals IMPLEMENTATION OF QUADRATIC AXIAL TRIAL FUNCTIONS IN THE HIGH-FIDELITY TRANSPORT CODE PROTEUS-MOC

2021 ◽  
Vol 247 ◽  
pp. 03015
Author(s):  
Guangchun Zhang ◽  
Won Sik Yang
Keyword(s):  
Linear Approximation ◽  
Quadratic Approximation ◽  
Linear Functions ◽  
Computational Time ◽  
High Fidelity ◽  
Test Results ◽  
Memory Requirement ◽  
Transport Code ◽  
Axial Variation ◽  
Memory Reduction

PROTEUS-MOC is a pin-resolved high-fidelity transport code, in which the axial variation of angular flux is represented in terms of orthogonal polynomials. Currently, PROTEUS-MOC employs linear functions and requires relatively fine axial meshes to achieve high accuracy, which increases the number of axial meshes and hence the memory requirement. In this study, aiming to reduce the memory requirement and potentially the computational time by allowing larger axial meshes, we have extended the PROTEUS-MOC transport solution method to quadratic trial functions. Preliminary tests for the performance of quadratic trial functions have been performed using the 3-D C5G7 benchmark problem. Test results showed that for the same axial mesh configuration with relatively large sizes, the quadratic approximation yields about 2 to 5 times more accurate pin powers than the linear approximation, depending on the degree of axial variation of angular fluxes. The quadratic approximation also allows the use of about 3 times coarser axial meshes than the linear approximation for comparable pin power accuracy, which consequently reduces the memory requirement by about 2 times. The memory reduction is not proportional because of the increased number of coefficients in each element from 2 to 3. However, the quadratic approximation did not reduce the computational time as expected because of the deteriorated performance of the pCMFD acceleration scheme due to large axial mesh sizes.

Development of high-fidelity neutron transport code STREAM

2021 ◽  
pp. 107915
Author(s):  
Sooyoung Choi ◽  
Wonkyeong Kim ◽  
Jiwon Choe ◽  
Woonghee Lee ◽  
Hanjoo Kim ◽  
...  
Keyword(s):  
Neutron Transport ◽  
High Fidelity ◽  
Transport Code

Methodology Development for Simulating Full Frontal and Offset Frontal Impacts Using Full Vehicle MADYMO Models

1999 ◽  
Author(s):  
Bala Deshpande ◽  
Gunasekar TJ ◽  
Russell Morris ◽  
Sudhanshu Parida ◽  
Mostafa Rashidy ◽  
...  
Keyword(s):  
Rigid Body ◽  
Joint Stiffness ◽  
Side Impact ◽  
Computational Time ◽  
Test Results ◽  
Vehicle Interior ◽  
Significant Saving ◽  
Methodology Development ◽  
Full Vehicle ◽  
Frontal Impacts

Abstract MADYMO articulated full vehicle models of the 1992 Ford Taurus, 1995 Chevrolet Lumina and the 1994 Dodge Intrepid for frontal and side impact modes have been developed and validated against test data. MADYMO (Mathematical Dynamic Model) is typically used to model occupants in the environment of the vehicle interior and thus finds application mainly in assessing occupant injuries. In this study however, MADYMO has been employed not only to model the occupants but also to represent the major load bearing structures in the vehicles. Input for the MADYMO models consisting of rigid body joint stiffness was obtained from corresponding full vehicle Finite Element (FE) models. Model validation was done by comparing the vehicle and dummy numbers with the New Car Assessment Program (NCAP) test results. Models correlated very well with both test and FE data. This modeling approach demonstrates the utility of rigid body based full car models for crashworthiness analysis. Such models result in significant saving in computational time and resources. In this paper, we describe the simulation of two different crash modes: full frontal and offset frontal impacts using the full vehicle MADYMO models. These simulations were validated with the corresponding test results in full frontal mode and IIHS offset mode. The models are useful for simulating a variety of impact situations, for example, with different occupant sizes, occupant positions, impact velocities, and in car to car impacts for performing compatibility studies.

A Modular Code for Real Time Dynamic Simulation of Gas Turbines in Simulink

2002 ◽  
Vol 128 (3) ◽  
pp. 506-517 ◽  
Author(s):  
S. M. Camporeale ◽  
B. Fortunato ◽  
M. Mastrovito
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Gas Turbine ◽  
Dynamic Behavior ◽  
Gas Turbines ◽  
Simulation Software ◽  
Computational Time ◽  
High Fidelity ◽  
Time Step ◽  
The Mathematical Model

A high-fidelity real-time simulation code based on a lumped, nonlinear representation of gas turbine components is presented. The code is a general-purpose simulation software environment useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of gas turbine engines. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft aero-derivative industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed.

A parallel multi-fidelity optimization approach in induction hardening

2019 ◽  
Vol 39 (1) ◽  
pp. 133-143
Author(s):  
Marco Baldan ◽  
Alexander Nikanorov ◽  
Bernard Nacke
Keyword(s):  
Parallel Computing ◽  
Optimization Technique ◽  
Computational Cost ◽  
Induction Hardening ◽  
Computational Time ◽  
High Fidelity ◽  
Optimization Approach ◽  
Content Type ◽  
Fidelity Model ◽  
Hardening System

Purpose Reliable modeling of induction hardening requires a multi-physical approach, which makes it time-consuming. In designing an induction hardening system, combining such model with an optimization technique allows managing a high number of design variables. However, this could lead to a tremendous overall computational cost. This paper aims to reduce the computational time of an optimal design problem by making use of multi-fidelity modeling and parallel computing. Design/methodology/approach In the multi-fidelity framework, the “high-fidelity” model couples the electromagnetic, thermal and metallurgical fields. It predicts the phase transformations during both the heating and cooling stages. The “low-fidelity” model is instead limited to the heating step. Its inaccuracy is counterbalanced by its cheapness, which makes it suitable for exploring the design space in optimization. Then, the use of co-Kriging allows merging information from different fidelity models and predicting good design candidates. Field evaluations of both models occur in parallel. Findings In the design of an induction heating system, the synergy between the “high-fidelity” and “low-fidelity” model, together with use of surrogates and parallel computing could reduce up to one order of magnitude the overall computational cost. Practical implications On one hand, multi-physical modeling of induction hardening implies a better understanding of the process, resulting in further potential process improvements. On the other hand, the optimization technique could be applied to many other computationally intensive real-life problems. Originality/value This paper highlights how parallel multi-fidelity optimization could be used in designing an induction hardening system.

scholarly journals Predictive modelling to support sensitivity analysis for robust design in aerospace engineering

2020 ◽  
Vol 61 (5) ◽  
pp. 2177-2192 ◽  
Author(s):  
Siva Krishna Dasari ◽  
Abbas Cheddad ◽  
Petter Andersson
Keyword(s):  
Sensitivity Analysis ◽  
Response Surface ◽  
Robust Design ◽  
Aerospace Engineering ◽  
Multivariate Adaptive Regression Splines ◽  
Linear Functions ◽  
Computational Time ◽  
Surface Modelling ◽  
Non Linear ◽  
Response Surface Modelling

AbstractThe design of aircraft engines involves computationally expensive engineering simulations. One way to solve this problem is the use of response surface models to approximate the high-fidelity time-consuming simulations while reducing computational time. For a robust design, sensitivity analysis based on these models allows for the efficient study of uncertain variables’ effect on system performance. The aim of this study is to support sensitivity analysis for a robust design in aerospace engineering. For this, an approach is presented in which random forests (RF) and multivariate adaptive regression splines (MARS) are explored to handle linear and non-linear response types for response surface modelling. Quantitative experiments are conducted to evaluate the predictive performance of these methods with Turbine Rear Structure (a component of aircraft) case study datasets for response surface modelling. Furthermore, to test these models’ applicability to perform sensitivity analysis, experiments are conducted using mathematical test problems (linear and non-linear functions) and their results are presented. From the experimental investigations, it appears that RF fits better on non-linear functions compared with MARS, whereas MARS fits well on linear functions.

A High-Fidelity Real-Time Simulation Code of Gas Turbine Dynamics for Control Applications

2002 ◽  
Author(s):  
S. M. Camporeale ◽  
B. Fortunato ◽  
M. Mastrovito
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Gas Turbine ◽  
Dynamic Behavior ◽  
Computational Time ◽  
High Fidelity ◽  
Simulation Code ◽  
Real Time Simulation ◽  
Time Simulation ◽  
The Mathematical Model

A novel high-fidelity real-time simulation code based on a lumped, non-linear representation of gas turbine components is presented. The aim of the work is to develop a general-purpose simulation code useful for setting up and testing control equipments. The mathematical model and the numerical procedure are specially developed in order to efficiently solve the set of algebraic and ordinary differential equations that describe the dynamic behavior of the gas turbine engine. The paper presents the model and the adopted solver procedure. The code, developed in Matlab-Simulink using an object-oriented approach, is flexible and can be easily adapted to any kind of plant configuration. For high-fidelity purposes, the mathematical model takes into account the actual composition of the working gases and the variation of the specific heats with the temperature, including a stage-by-stage model of the air-cooled expansion. Simulation tests of the transients after load rejection have been carried out for a single-shaft heavy-duty gas turbine and a double-shaft industrial engine. Time plots of the main variables that describe the gas turbine dynamic behavior are shown and the results regarding the computational time per time step are discussed.

Consistent Transport Transient Solvers of the High-Fidelity Transport Code PROTEUS-MOC

2020 ◽  
Vol 194 (7) ◽  
pp. 508-540
Author(s):  
Albert Hsieh ◽  
Guangchun Zhang ◽  
Won Sik Yang
Keyword(s):  
High Fidelity ◽  
Transport Code ◽  
Transient Solvers

Time-Dependent, Three Dimensional Nodal Transport Code Development Based on Unstructured Mesh

2014 ◽  
Author(s):  
Mingtao He ◽  
Hongchun Wu ◽  
Liangzhi Cao ◽  
Youqi Zheng ◽  
ShengCheng Zhou
Keyword(s):  
Direct Method ◽  
Three Dimensional ◽  
Computational Time ◽  
Neutron Kinetics ◽  
Nodal Method ◽  
Transport Code ◽  
Geometry Configuration ◽  
Nodal Transport ◽  
Complicated Geometry ◽  
Predictor Corrector

A space-time nodal transport code, DAISY, was developed to evaluate dynamic neutron behavior in innovative nuclear system. The steady transport process is based on an arbitrary triangles-z mesh nodal method which can treat complicated geometry configuration with enough precision and acceptable calculated quantity. This code employs the improved quasi-static method for neutron kinetics with a predictor-corrector scheme to improve computational efficiency. The direct method and the point approximation for neutron kinetics are also implemented into DAISY to evaluate the precision and efficiency of this predictor-corrector scheme. This code was verified by several transient benchmarks. It shows that the predictor-corrector scheme in DAISY can greatly reduce the computational time with enough precision.

A HIGH PERFORMANCE LARGE SPARSE SYMMETRIC SOLVER FOR THE MESHFREE GALERKIN METHOD

2008 ◽  
Vol 05 (04) ◽  
pp. 533-550 ◽  
Author(s):  
S. C. WU ◽  
H. O. ZHANG ◽  
C. ZHENG ◽  
J. H. ZHANG
Keyword(s):  
High Performance ◽  
Information Matrix ◽  
Computational Cost ◽  
Initial Boundary ◽  
Field Analysis ◽  
Iteration Step ◽  
Gradient Field ◽  
Computational Time ◽  
Preconditioned Conjugate Gradient ◽  
Memory Requirement

One main disadvantage of meshfree methods is that their memory requirement and computational cost are much higher than those of the usual finite element method (FEM). This paper presents an efficient and reliable solver for the large sparse symmetric positive definite (SPD) system resulting from the element-free Galerkin (EFG) approach. A compact mathematical model of heat transfer problems is first established using the EFG procedure. Based on the widely used Successive Over-Relaxation–Preconditioned Conjugate Gradient (SSOR–PCG) scheme, a novel solver named FastPCG is then proposed for solving the SPD linear system. To decrease the computational time in each iteration step, a new algorithm for realizing multiplication of the global stiffness matrix by a vector is presented for this solver. The global matrix and load vector are changed in accordance with a special rule and, in this way, a large account of calculation is avoided on the premise of not decreasing the solution's accuracy. In addition, a double data structure is designed to tackle frequent and unexpected operations of adding or removing nodes in problems of dynamic adaptive or moving high-gradient field analysis. An information matrix is also built to avoid drastic transformation of the coefficient matrix caused by the initial-boundary values. Numerical results show that the memory requirement of the FastPCG solver is only one-third of that of the well-developed AGGJE solver, and the computational cost is comparable with the traditional method with the increas of solution scale and order.

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