Experimental validation of the generalized accurate modelling method for system-level bulk current injection setups up to 1 GHz

2015 ◽  
Author(s):  
Sergey Miropolsky ◽  
Stefan Jahn ◽  
Frank Klotz ◽  
Stephan Frei
Keyword(s):  
Experimental Validation ◽  
Current Injection ◽  
System Level ◽  
Modelling Method

Experimental and Numerical Study of Supersonic Non-ideal Flows for Organic Rankine Cycle Applications

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Miles Robertson ◽  
Peter Newton ◽  
Tao Chen ◽  
Aaron Costall ◽  
Ricardo Martinez-Botas
Keyword(s):  
Experimental Validation ◽  
Numerical Study ◽  
Pressure Ratio ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Helmholtz Energy ◽  
System Level ◽  
Low Grade ◽  
Dense Gas ◽  
Cfd Simulations

Abstract The organic Rankine cycle (ORC) is low-grade heat recovery technology, for sources as diverse as geothermal, industrial, and vehicle waste heat. The working fluids used within these systems often display significant real-gas effects, especially in proximity of the thermodynamic critical point. Three-dimensional (3D) computational fluid dynamics (CFD) is commonly used for performance prediction and flow field analysis within expanders, but experimental validation with real gases is scarce within the literature. This paper therefore presents a dense-gas blowdown facility constructed at Imperial College London, for experimentally validating numerical simulations of these fluids. The system-level design process for the blowdown rig is described, including the sizing and specification of major components. Tests with refrigerant R1233zd(E) are run for multiple inlet pressures, against a nitrogen baseline case. CFD simulations are performed, with the refrigerant modeled by ideal gas, Peng–Robinson, and Helmholtz energy equations of state. It is shown that increases in fluid model fidelity lead to reduced deviation between simulation and experiment. Maximum and mean discrepancies of 9.59% and 8.12% in nozzle pressure ratio with the Helmholtz energy EoS are reported. This work demonstrates an over-prediction of pressure ratio and power output within commercial CFD packages, for turbomachines operating in non-ideal fluid environments. This suggests a need for further development and experimental validation of CFD simulations for highly non-ideal flows. The data contained within this paper are therefore of vital importance for the future validation and development of CFD methods for dense-gas turbomachinery.

Non-linear thermal simulation at system level: Compact modelling and experimental validation

2018 ◽  
Vol 80 ◽  
pp. 223-229 ◽  
Author(s):  
Mirko Bernardoni ◽  
Nicola Delmonte ◽  
Diego Chiozzi ◽  
Paolo Cova
Keyword(s):  
Experimental Validation ◽  
Thermal Simulation ◽  
System Level ◽  
Non Linear

scholarly journals Multi-physics analysis of valve train systems: From system level to microscale interactions

2007 ◽  
Vol 221 (3) ◽  
pp. 349-361 ◽  
Author(s):  
M Teodorescu ◽  
M Kushwaha ◽  
H Rahnejat ◽  
S J Rothberg
Keyword(s):  
Experimental Validation ◽  
Valve Train ◽  
System Level ◽  
Test Rig ◽  
Component Level ◽  
Multi Scale ◽  
Single Cylinder Engine ◽  
Underlying Causes ◽  
Noise Vibration ◽  
Physical Phenomena

The paper highlights a holistic, integrated, and multi-disciplinary approach to design analysis of valve train systems, referred to as multi-physics. The analysis comprises various forms of physical phenomena and their interactions, including large displacement inertial dynamics, small amplitude oscillations due to system compliances, tribology, contact mechanics, and durability at the cam-tappet contact. Therefore, it also represents a multi-scale investigation, where the phenomena can be investigated at system level and referred back to underlying causes at subsystem or component level, in other words, implications of an event at microcosm can be ascertained on the overall system performance. This approach is often referred to in industry as down-cascading and up-cascading. The particular case reported here to outline the merits of this approach concerns a four-stroke single-cylinder engine. This promotes a system approach to engineering analysis for integrated noise, vibration, and harshness, durability and frictional assessment (efficiency). Experimental validation is provided with a motored test rig, using laser doppler vibrometry.

scholarly journals Processor-in-the-Loop Architecture Design and Experimental Validation for an Autonomous Racing Vehicle

2021 ◽  
Vol 11 (16) ◽  
pp. 7225
Author(s):  
Eugenio Tramacere ◽  
Sara Luciani ◽  
Stefano Feraco ◽  
Angelo Bonfitto ◽  
Nicola Amati
Keyword(s):  
Real Time ◽  
Personal Computer ◽  
Trajectory Planning ◽  
Autonomous Vehicles ◽  
High Performance ◽  
Experimental Validation ◽  
Low Cost ◽  
Autonomous Driving ◽  
Obstacle Detection ◽  
System Level

Self-driving vehicles have experienced an increase in research interest in the last decades. Nevertheless, fully autonomous vehicles are still far from being a common means of transport. This paper presents the design and experimental validation of a processor-in-the-loop (PIL) architecture for an autonomous sports car. The considered vehicle is an all-wheel drive full-electric single-seater prototype. The retained PIL architecture includes all the modules required for autonomous driving at system level: environment perception, trajectory planning, and control. Specifically, the perception pipeline exploits obstacle detection algorithms based on Artificial Intelligence (AI), and the trajectory planning is based on a modified Rapidly-exploring Random Tree (RRT) algorithm based on Dubins curves, while the vehicle is controlled via a Model Predictive Control (MPC) strategy. The considered PIL layout is implemented firstly using a low-cost card-sized computer for fast code verification purposes. Furthermore, the proposed PIL architecture is compared in terms of performance to an alternative PIL using high-performance real-time target computing machine. Both PIL architectures exploit User Datagram Protocol (UDP) protocol to properly communicate with a personal computer. The latter PIL architecture is validated in real-time using experimental data. Moreover, they are also validated with respect to the general autonomous pipeline that runs in parallel on the personal computer during numerical simulation.

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