Definition and Implementation of a Method for Uncertainty Aggregation in Component-Based System Simulation Models

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Magnus Eek ◽  
Hampus Gavel ◽  
Johan Ölvander
Keyword(s):  
Cooling System ◽  
System Simulation ◽  
Measurement Data ◽  
Simulation Models ◽  
Bench Test ◽  
Aggregation Method ◽  
Component Level ◽  
Output Uncertainty ◽  
Liquid Cooling System ◽  
And Control

Component-based system simulation models are used throughout all development phases for design and verification of both physical systems and control software, not least in the aeronautical industry. However, the application of structured methods for uncertainty quantification (UQ) of system simulation models is rarely seen. To enable dimensionality reduction of a UQ problem and to thereby make UQ more feasible for industry-grade system simulation models, this paper describes a pragmatic method for uncertainty aggregation. The central idea of the proposed aggregation method is to integrate information obtained during common practice component-level validation directly into the components, and to utilize this information in model-level UQ. A generic component output uncertainty description has been defined and implemented in a Modelica library for modeling and simulation (M&S) of aircraft vehicle systems. An example is provided on how to characterize and quantify a component's aggregated output uncertainty based on the component-level bench test measurement data. Furthermore, the industrial applicability of the uncertainty aggregation method is demonstrated in an approximate UQ of an aircraft liquid cooling system simulation model. For cases when the concept of thorough UQ resulting in probability boxes is not feasible, the demonstrated approximate UQ using aggregated uncertainties is considered to be a pragmatic alternative fairly in reach for the common M&S practitioner within the area of system simulation.

scholarly journals Evaluating Model Uncertainty Based on Probabilistic Analysis and Component Output Uncertainty Descriptions

2012 ◽  
Author(s):  
Magnus Carlsson ◽  
Hampus Gavel ◽  
Johan Ölvander
Keyword(s):  
Cooling System ◽  
Measurement Data ◽  
Simulation Models ◽  
System Level ◽  
Upper And Lower Bounds ◽  
Early Model ◽  
Model Uncertainties ◽  
Component Level ◽  
Output Uncertainty ◽  
Model Components

To support early model validation, this paper describes a method utilizing information obtained from the common practice component level validation to assess uncertainties on model top level. Initiated in previous research, a generic output uncertainty description component, intended for power-port based simulation models of physical systems, has been implemented in Modelica. A set of model components has been extended with the generic output uncertainty description, and the concept of using component level output uncertainty to assess model top level uncertainty has been applied on a simulation model of a radar liquid cooling system. The focus of this paper is on investigating the applicability of combining the output uncertainty method with probabilistic techniques, not only to provide upper and lower bounds on model uncertainties but also to accompany the uncertainties with estimated probabilities. It is shown that the method may result in a significant improvement in the conditions for conducting an assessment of model uncertainties. The primary use of the method, in combination with either deterministic or probabilistic techniques, is in the early development phases when system level measurement data are scarce. The method may also be used to point out which model components contribute most to the uncertainty on model top level. Such information can be used to concentrate physical testing activities to areas where it is needed most. In this context, the method supports the concept of Virtual Testing.

scholarly journals A Real-Time Dynamic Fuel Cell System Simulation for Model-Based Diagnostics and Control: Validation on Real Driving Data

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3148 ◽  
Author(s):  
Daniel Ritzberger ◽  
Christoph Hametner ◽  
Stefan Jakubek
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Combustion Engine ◽  
System Simulation ◽  
Measurement Data ◽  
Fuel Cell Vehicle ◽  
Feedback Controls ◽  
Model Based ◽  
And Control ◽  
Stack Model

Fuel cell systems are regarded as a promising candidate in replacing the internal combustion engine as a renewable and emission free alternative in automotive applications. However, the operation of a fuel cell stack fulfilling transient power-demands poses significant challenges. Efficiency is to be maximized while adhering to critical constraints, avoiding adverse operational conditions (fuel starvation, membrane flooding or drying, etc.) and mitigating degradation as to increase the life-time of the stack. Owing to this complexity, advanced model-based diagnostic and control methods are increasingly investigated. In this work, a real time stack model is presented and its experimental parameterization is discussed. Furthermore, the stack model is integrated in a system simulation, where the compressor dynamics, the feedback controls for the hydrogen injection and back-pressure valve actuation, and the purging strategy are considered. The resulting system simulation, driven by the set-point values of the operating strategy is evaluated and validated on experimental data obtained from a fuel cell vehicle during on-road operation. It will be shown how the internal states of the fuel cell simulation evolve during the transient operation of the fuel cell vehicle. The measurement data, for which this analysis is conducted, stem from a fuel cell research and demonstrator vehicle, developed by a consortium of several academic and industrial partners under the lead of AVL List GmbH.

Experimental Error Measurement in Monte Carlo Simulation

2010 ◽  
pp. 92-142 ◽  
Author(s):  
Lucia Cassettari ◽  
Roberto Mosca ◽  
Roberto Revetria
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Experimental Error ◽  
System Simulation ◽  
Simulation Models ◽  
Error Measurement ◽  
Mean Square ◽  
Optimal Functioning ◽  
Set Up ◽  
And Control

This chapter describes the set up step series, developed by the Genoa Research Group on Production System Simulation at the beginning of the ’80s, as a sequence, through which it is possible at first statistically validate the simulator, then estimate the variables which effectively affect the different target functions, then obtain, through the regression meta-models, the relations linking the independent variables to the dependent ones (target functions) and, finally, proceed to the detection of the optimal functioning conditions. The authors pay great attention to the treatment, the evaluation and control of the Experimental Error, under the form of Mean Square Pure Error (MSPE), a measurement which is always culpably neglected in the traditional experimentation on the simulation models but, that potentially can consistently invalidate with its magnitude the value of the results obtained from the model.

Multi-objective optimization of a chip-attached micro pin fin liquid cooling system

2021 ◽  
pp. 117187
Author(s):  
Vahideh Radmard ◽  
Yaser Hadad ◽  
Srikanth Rangarajan ◽  
Cong H. Hoang ◽  
Najmeh Fallahtafti ◽  
...  
Keyword(s):  
Cooling System ◽  
Multi Objective Optimization ◽  
Liquid Cooling ◽  
Multi Objective ◽  
Pin Fin ◽  
Liquid Cooling System

scholarly journals Performance Analysis of Hybrid Desiccant Cooling System with Enhanced Dehumidification Capability Using TRNSYS

2021 ◽  
Vol 11 (7) ◽  
pp. 3236
Author(s):  
Ji Hyeok Kim ◽  
Joon Ahn
Keyword(s):  
Thermal Comfort ◽  
Cooling System ◽  
Operation Mode ◽  
Heat Removal ◽  
Simulation Models ◽  
Coefficient Of Performance ◽  
Dimensional Structure ◽  
Dominant Factor ◽  
Exhaust Heat ◽  
Chp System

In a field test of a hybrid desiccant cooling system (HDCS) linked to a gas engine cogeneration system (the latter system is hereafter referred to as the combined heat and power (CHP) system), in the cooling operation mode, the exhaust heat remained and the latent heat removal was insufficient. In this study, the performance of an HDCS was simulated at a humidity ratio of 10 g/kg in conditioned spaces and for an increasing dehumidification capacity of the desiccant rotor. Simulation models of the HDCS linked to the CHP system were based on a transient system simulation tool (TRNSYS). Furthermore, TRNBuild (the TRNSYS Building Model) was used to simulate the three-dimensional structure of cooling spaces and solar lighting conditions. According to the simulation results, when the desiccant capacity increased, the thermal comfort conditions in all three conditioned spaces were sufficiently good. The higher the ambient temperature, the higher the evaporative cooling performance was. The variation in the regeneration heat with the outdoor conditions was the most dominant factor that determined the coefficient of performance (COP). Therefore, the COP was higher under high temperature and dry conditions, resulting in less regeneration heat being required. According to the prediction results, when the dehumidification capacity is sufficiently increased for using more exhaust heat, the overall efficiency of the CHP can be increased while ensuring suitable thermal comfort conditions in the cooling space.

The effect of practicing yoga during pregnancy on labor stages length, anxiety and pain: a randomized controlled trial

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ellahe Mohyadin ◽  
Zohreh Ghorashi ◽  
Zahra Molamomanaei
Keyword(s):  
Controlled Trial ◽  
Intervention Group ◽  
Total Duration ◽  
Measurement Data ◽  
Labor Pain ◽  
Control Group ◽  
Chi Square ◽  
Nulliparous Women ◽  
Two Stages ◽  
And Control

AbstractBackgroundAnxiety and fear of labor pain has led to elevated cesarean section rate in some countries. This study was conducted to investigate the effect of yoga in pregnancy on anxiety, labor pain and length of labor stages.MethodsThis clinical trial study was performed on 84 nulliparous women who were at least 18 years old and were randomly divided into two groups of yoga and control groups. Pregnancy Yoga Program consisting of 6 60-min training sessions was started every 2 weeks from week 26 of pregnancy and continued until 37 weeks of gestation. Anxiety severity at maternal admission to labor was measured by the Spielbergers State-Trait Anxiety Inventory, and labor pain was measured by Visual Analogue Scale (VAS) at dilatation (4–5 cm) and 2 h after the first measurement. Data were analyzed using Chi-Square and t-test.ResultsIntervention group reported less pain at dilatation (4–5 cm) (p=0.001) and 2 h after the first measurement (p=0.001) than the control group. Stat anxiety was also lower in intervention group than the control group (p=0.003) at the entrance to labor room. Subjects in the control group required more induction compared to intervention group (p=0.003). Women in intervention group experienced shorter duration of the first phase of the labor than the control group (p=0.002). Also, the total duration of two stages of labor was shorter in intervention group than the control group (p=0.003).ConclusionsPracticing yoga during pregnancy may reduce women’s anxiety during labor; shorten labor stages, and lower labor pain.

Design and Simulation of Pedal Simulator in Brake by Wire System

2014 ◽  
Vol 556-562 ◽  
pp. 1358-1361 ◽  
Author(s):  
Wen Bo Zhu ◽  
Fen Zhu Ji ◽  
Xiao Xu Zhou
Keyword(s):  
Simulation Models ◽  
Control Algorithms ◽  
Brake Pedal ◽  
Braking System ◽  
Pedal Force ◽  
Performance Requirements ◽  
System A ◽  
Pedal Feel ◽  
And Control ◽  
Wire System

Wire of the brake pedal is not directly connected to the hydraulic environment in the braking By-wire system so the driver has no direct pedal feel. Then pedal simulator is an important part in the brake-by-wire system. A pedal force simulator was designed based on the traditional brake pedal curve of pedal force and pedal travel, AMESim and Matlab / Simulink were used as a platform to build simulation models and control algorithms. The simulation results show that the pedal stroke simulator and the control strategy meet the performance requirements of traditional braking system. It can be used in brake by wire system.

System Level Bench Test for Trailing Arm Strength Estimation

2006 ◽  
Author(s):  
Jaychandar Muthu ◽  
Kanak Soundrapandian ◽  
Jyoti Mukherjee
Keyword(s):  
Failure Mode ◽  
Real Life ◽  
Element Model ◽  
Suspension System ◽  
System Level ◽  
Bench Test ◽  
Component Level ◽  
Arm Strength ◽  
Bench Testing ◽  
Nonlinear Finite Element Model

For suspension components, bench testing for strength is mostly accomplished at component level. However, replicating loading and boundary conditions at the component level in order to simulate the suspension system environment may be difficult. Because of this, the component's bench test failure mode may not be similar to its real life failure mode in vehicle environment. A suspension system level bench test eliminates most of the discrepancies between simulated component level and real life vehicle level environments resulting in higher quality bench tests yielding realistic test results. Here, a suspension level bench test to estimate the strength of its trailing arm link is presented. A suspension system level nonlinear finite element model was built and analyzed using ABAQUS software. The strength loading was applied at the wheel end. The analysis results along with the hardware test correlations are presented. The reasons why a system level test is superior to a component level one are also highlighted.

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