Time-Efficient Method for Test-Based Optimization of Technical Systems Using Physical Models

2012 ◽  
Author(s):  
Albert Albers ◽  
Alexander Schwarz ◽  
Matthias Behrendt ◽  
Rolf Hettel
Keyword(s):  
Physical Model ◽  
Physical Models ◽  
Design Parameters ◽  
Model Structure ◽  
Unknown Parameters ◽  
Calibration Process ◽  
Automated Generation ◽  
Test Execution ◽  
Artificial Neuronal Networks ◽  
Technical Systems

Technical systems must be continuously improved so that they can remain competitive on the market. Also, the time-to-market is an important factor for the success of a product. To achieve this goal, new methods and processes are needed. Especially the testing and calibration are important phases in the development process. This paper introduces a method, which helps to reduce the time effort while increasing the quality of the calibration process. The basic idea is to use measured test data to parameterize a physical (or mostly physical) model structure to create adequate models for the optimization. The main advantage of the method is the reduction of test effort because the number of variations of the design parameter is one, or extremely decreased (depending on the system). Another advantage is that the uncertainty and the limit of the model can be quantified more accurately compared to common approaches based on non-physical model structures. These normally use artificial neuronal networks (ANN) or polynomial approaches for the test-based optimization. This contribution illustrates the method by using the example of the calibration process of a double clutch gearbox (DCT) regarding energy efficiency and drivability on a roller test bench. First step is the test planning and test execution. In this step the method calculates the optimal execution order of the measuring points. In this example 81% timesaving can be achieved compared to the equivalent on the test track. The second step is the automated generation of the simulation model. In this step the unknown parameters of the model structure are calculated. The contribution shows different approaches for the identification of non-linear systems. In the last step the model is used to perform the optimization of the design parameters.

Material and Posture Modeling for Sleeping on Soft Low-Density Porous Material

2018 ◽  
Author(s):  
Takahiro Yamaguchi ◽  
Hajime Kimura ◽  
Atsushi Sakuma ◽  
Kazushige Takahashi ◽  
Shigetoshi Mimura
Keyword(s):  
Physical Model ◽  
Mechanical Design ◽  
Human Life ◽  
Great Influence ◽  
Body Part ◽  
The Body ◽  
Physical Models ◽  
Design Parameters ◽  
Physical Parameters

Sleeping is one of the most important factors that influence the quality of human life, and this state of existence should be thoroughly investigated to improve the quality of the life. The mechanical design of bedding has great influence on the comfort of a mattress. Thus, objective and conventional techniques to evaluate the mechanics of mattress comfort could help improve the quality of sleep. In this report, an analysis technique for the assessment of the sleeping posture of humans is presented to facilitate the development of mattress design technology. Herein, an analytical model which imitates the human body has been formulated to determine the design parameters of a mass-spring-joint system on a soft underlay. The physical model is composed of five components that represent the head, chest, hip, femur, and calf, with each body part being represented by a simple ball model. The spring joint connecting the five parts reflects the neck, lumbar, hip, and knee joints. The specifications of the body model are determined by actual measurements and previous studies. In order to determine the physical properties of the mattress, two types of mattress urethane foam material are tested using the ball indenter method. The parameters include Young’s modulus, plateau stress, and other physical parameters. Variation due to the type of mattress has been observed in the laying test using a pressure distribution sensor sheet. In the analysis performed using the physical model, the variation in the lying posture and the extent of body sinking are observed to be the same during experiments. Both variations are compared using the change in force distribution in each body part. In conclusion, it was found that the observed changes in distribution are the same in the experimental and physical models. Therefore, the proposed model reliably reflects the design characteristics of the mattress.

scholarly journals Two-Dimensional Numerical Modeling of Flow in Physical Models of Rock Vane and Bendway Weir Configurations

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 458
Author(s):  
Drew C. Baird ◽  
Benjamin Abban ◽  
S. Michael Scurlock ◽  
Steven B. Abt ◽  
Christopher I. Thornton
Keyword(s):  
Numerical Modeling ◽  
Physical Model ◽  
Numerical Models ◽  
Hydraulic Performance ◽  
Physical Models ◽  
Protection Measures ◽  
Design Engineers ◽  
Model Study ◽  
Study Results ◽  
Wide Range

While there are a wide range of design recommendations for using rock vanes and bendway weirs as streambank protection measures, no comprehensive, standard approach is currently available for design engineers to evaluate their hydraulic performance before construction. This study investigates using 2D numerical modeling as an option for predicting the hydraulic performance of rock vane and bendway weir structure designs for streambank protection. We used the Sedimentation and River Hydraulics (SRH)-2D depth-averaged numerical model to simulate flows around rock vane and bendway weir installations that were previously examined as part of a physical model study and that had water surface elevation and velocity observations. Overall, SRH-2D predicted the same general flow patterns as the physical model, but over- and underpredicted the flow velocity in some areas. These over- and underpredictions could be primarily attributed to the assumption of negligible vertical velocities. Nonetheless, the point differences between the predicted and observed velocities generally ranged from 15 to 25%, with some exceptions. The results showed that 2D numerical models could provide adequate insight into the hydraulic performance of rock vanes and bendway weirs. Accordingly, design guidance and implications of the study results are presented for design engineers.

A Modified Algorithm for the Least Squares Identification

1983 ◽  
Vol 105 (1) ◽  
pp. 50-52
Author(s):  
C. Batur
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Mechanical Systems ◽  
Model Structure ◽  
Input Output ◽  
Unknown Parameters ◽  
Estimation Errors ◽  
Usual Practice ◽  
Unknown Disturbances ◽  
Modified Algorithm

To identify the dynamics of mechanical systems, the usual practice is to assume a certain model structure and try to estimate the unknown parameters of this model on the basis of input output observations. For mechanical systems operating under noisy industrial conditions, the number of unknowns of the problem exceeds the number of equations available. It is then inevitable that certain assumptions must be made on the unknown disturbances. This paper assumes that the only reliable feature of the disturbance is its independence of input. This yields a set of assumptions in excess of the minimal requirements and an endeavor has been made to exploit this excess to minimize the parameter estimation errors. Th resulting algorithm is similar to that of the Two Stage Least Squares method [1].

Model Test Study on Influences of Layered Rock Mass Dip Angle on Stability of Deep-Buried Tunnel

2011 ◽  
Vol 90-93 ◽  
pp. 2363-2371
Author(s):  
Bin Wei Xia ◽  
Ke Hu ◽  
Yi Yu Lu ◽  
Dan Li ◽  
Zu Yong Zhou
Keyword(s):  
Rock Mass ◽  
Physical Model ◽  
Model Test ◽  
Physical Models ◽  
Physical Model Test ◽  
Stress Distributions ◽  
Failure Characteristics ◽  
Layered Rock ◽  
Layered Rock Mass ◽  
Dip Angle

Physical models of layered rock mass with different dip angles are built by physical model test in accordance with the bias failure characteristics of surrounding rocks of layered rock mass in Gonghe Tunnel. Bias failure characteristics of surrounding rocks in thin-layered rock mass and influences of layered rock mass dip angle on stability of tunnel are studied. The research results show that failure characteristics of physical models generally coincide with those of surrounding rocks monitored from the tunnel site. The failure regions of surrounding rock perpendicular to the stratification planes are obviously larger than those parallel to. The stress distributions and failure characteristics in the surrounding rocks are similar to each physical model of different dip angles. The stress distributions and failure regions are all elliptic in shape, in which the major axis is in the direction perpendicular to the stratification planes while the minor axis is parallel to them. As a result, obvious bias failure of surrounding rocks has gradually formed. The physical model tests provide reliable basis for theoretical analysis on the failure mechanism of deep-buried layered rock mass.

Accelerating Climate Model Computation by Neural Networks: A Comparative Study

2021 ◽  
Author(s):  
Maha Mdini ◽  
Takemasa Miyoshi ◽  
Shigenori Otsuka
Keyword(s):  
Neural Networks ◽  
Computational Complexity ◽  
Statistical Model ◽  
Physical Model ◽  
Climate Model ◽  
Numerical Models ◽  
Computation Time ◽  
High Accuracy ◽  
Physical Models ◽  
Computer Resources

<p>In the era of modern science, scientists have developed numerical models to predict and understand the weather and ocean phenomena based on fluid dynamics. While these models have shown high accuracy at kilometer scales, they are operated with massive computer resources because of their computational complexity.  In recent years, new approaches to solve these models based on machine learning have been put forward. The results suggested that it be possible to reduce the computational complexity by Neural Networks (NNs) instead of classical numerical simulations. In this project, we aim to shed light upon different ways to accelerating physical models using NNs. We test two approaches: Data-Driven Statistical Model (DDSM) and Hybrid Physical-Statistical Model (HPSM) and compare their performance to the classical Process-Driven Physical Model (PDPM). DDSM emulates the physical model by a NN. The HPSM, also known as super-resolution, uses a low-resolution version of the physical model and maps its outputs to the original high-resolution domain via a NN. To evaluate these two methods, we measured their accuracy and their computation time. Our results of idealized experiments with a quasi-geostrophic model [SO3] show that HPSM reduces the computation time by a factor of 3 and it is capable to predict the output of the physical model at high accuracy up to 9.25 days. The DDSM, however, reduces the computation time by a factor of 4 and can predict the physical model output with an acceptable accuracy only within 2 days. These first results are promising and imply the possibility of bringing complex physical models into real time systems with lower-cost computer resources in the future.</p>

Physical Model of Estuarine Salinity Intrusion into Rivers: A Review

2014 ◽  
Vol 905 ◽  
pp. 348-352 ◽  
Author(s):  
Nuryazmeen Farhan Haron ◽  
Wardah Tahir
Keyword(s):  
Physical Model ◽  
Physical Models ◽  
Salinity Intrusion ◽  
Mixing Process ◽  
Salt Wedge ◽  
Laboratory Investigations ◽  
Estuarine Salinity

This paper reviews the physical models that had been used in order to conduct the experiment of estuarine salinity intrusion into rivers. Several studies used the physical models to get a better understanding of the estuary salinity mixing process and salt-wedge estuary characteristics along the flume. Besides, the laboratory investigations using the physical model also useful for verification purposes as discussed by previous researchers.

Using Integration of Thermal-Balance Based and Data-Driven Models to Determine Single Duct Variable Air Volume System Cooling Baseline

2013 ◽  
Author(s):  
Gyujin Shim ◽  
Li Song ◽  
Gang Wang
Keyword(s):  
Physical Model ◽  
Least Square Method ◽  
Energy Performance ◽  
Least Square ◽  
Physical Models ◽  
Data Driven ◽  
Lumped Model ◽  
Variable Air Volume ◽  
Data Driven Approach ◽  
Cooling Coil

In order to use real-time energy measurements to identify system operation faults and inefficiencies, a cooling coil energy baseline is studied in an air-handling unit (AHU) through an integration of physical models and a data driven approach in this paper. A physical model for an AHU cooling coil energy consumption is first built to understand equipment mechanism and to determine the variables impacting cooling coil energy performance, and then the physical model is simplified into a lumped model by reducing the number of independent variables needed. Regression coefficients in the lumped model are determined statistically through searching optimal fit using the least square method with short periods of measured data. Experimental results on an operational AHU (8 ton) are presented to validate the effectiveness of this approach with statistical analysis. As a result of this experiment, the proposed cooling energy baselines at the cooling coil have ±20% errors at 99.7% confidence. Six-day data for obtaining baseline is preferred since it shows similar results as 12-day.

A Methodology for the Analysis of Physical Model Scale Effects on the Simulation of Wave Propagation up to Wave Breaking: Preliminary Physical Model Results

2008 ◽  
Author(s):  
Conceic¸a˜o Fortes ◽  
Maria da Grac¸a Neves ◽  
Joa˜o Alfredo Santos ◽  
Rui Capita˜o ◽  
Artur Palha ◽  
...  
Keyword(s):  
Wave Propagation ◽  
Physical Model ◽  
Scale Effects ◽  
National Laboratory ◽  
Physical Models ◽  
Type Model ◽  
Research Activity ◽  
Joint Research ◽  
Common Structure ◽  
Constant Slope

This paper describes the experiments performed at the National Laboratory for Civil Engineering (LNEC) aiming at simulating, in a flume, the wave propagation along a constant slope bottom that ends on a sea wall coastal defence structure, a common structure employed in the Portuguese coast. The objective of these tests is to calibrate the parameters of FUNWAVE, a Boussinesq type model, for wave propagation in coastal regions. This is the first step in the validation of a methodology to combine numerical and physical models in the study of the interactions between beaches and structures. This work is performed in the framework of the Composite Modelling of the Interactions between Beaches and Structures (CoMIBBs) project, a joint research activity of the HYDRALAB III European project.

scholarly journals Wetropolis extreme rainfall and flood demonstrator: from mathematical design to outreach

2020 ◽  
Vol 24 (5) ◽  
pp. 2483-2503
Author(s):  
Onno Bokhove ◽  
Tiffany Hicks ◽  
Wout Zweers ◽  
Thomas Kent
Keyword(s):  
Physical Model ◽  
Return Period ◽  
River Flow ◽  
Extreme Rainfall ◽  
Flood Plain ◽  
Flood Management ◽  
Physical Models ◽  
Flood Mitigation ◽  
Design Changes ◽  
Extreme Flooding

Abstract. Government and consulting experts on flood mitigation generally face difficulties when trying to explain the science of extreme flooding to the general public, in particular the concept of a return period. Too often, for example, people perceive they are safe for the next 100 years after a 1:100-year return-period flood has hit their town. UK flood practitioners therefore gave us the challenge to design an outreach tool that conceptualises the science of flooding in a way that is accessible to and directly engages the public, and in particular demonstrates what a return period is. Furthermore, we were tasked with designing a live 3-D physical model rather than a graphical or animated 2-D game on a screen. We show here how we tackled that challenge by designing, constructing, and showcasing the Wetropolis Flood Demonstrator. Wetropolis is a transportable and conceptual physical model with random rainfall, river flow, a flood plain, an upland reservoir, a porous moor, representing the upper catchment and visualising groundwater flow, and a city which can flood following extreme and random rainfall. A key novelty is the supply of rainfall every Wetropolis day. Several aspects of Wetropolis are considered. i. We present the modular mathematical and numerical design on which Wetropolis is based. It guided the choice of parameter values of Wetropolis, which was loosely inspired by the Leeds Boxing Day floods of the River Aire in 2015. The design model further serves as the building block and inspiration for adaptations suited to particular local demands. Moreover, the model is purposely lean and therefore quick to compute, serving flexibility in the outreach-tool design, but is less suitable for any detailed scientific validation.ii. The constructed Wetropolis is described here in broad terms, but we include a link to a GitHub site with details to inspire other bespoke designs. The goal, again, is to facilitate new adaptations of Wetropolis for particular catchments different to the Leeds River Aire case.iii. Our experience in showcasing Wetropolis is summarised and discussed, with the purpose of giving an overview as well as inspiring improved and bespoke adaptations. While Wetropolis should be experienced live, with videos found on the GitHub site, here we provide a photographic overview. To date, Wetropolis has been showcased to 500 to 1000 people at public workshops and exhibitions on recent UK floods, as well as to flood practitioners and scientists at various research and stakeholder workshops.iv. We conclude with some ongoing design changes, including how people can experience natural flood management in a revised Wetropolis design. Finally, we also discuss how Wetropolis, although originally focussed solely on outreach, led to a new cost-effectiveness analysis and protocol for assessing flood-mitigation plans and inspired other physical models for use in education and water management.

A performance investigation of small-bore sewers

2007 ◽  
Vol 55 (4) ◽  
pp. 85-91 ◽  
Author(s):  
F.A. Memon ◽  
A. Fidar ◽  
K. Littlewood ◽  
D. Butler ◽  
C. Makropoulos ◽  
...  
Keyword(s):  
Physical Model ◽  
Water Cycle ◽  
Design Guidelines ◽  
Design Parameters ◽  
New Developments ◽  
Tissue Paper ◽  
Solids Transport ◽  
Implementation Methodology ◽  
Gradient Variation ◽  
The Impact

This paper describes a full-scale physical model and its application to investigate the effectiveness/performance of small-bore sewers for a range of operational and design parameters. The implementation methodology involves observing the movement of synthetic gross solids in three small bore sewers (150, 100 and 75 mm diameter) for different volumes of simulated flush waves and gradients. The simulated flush waves were generated, using an automated wave sequencer, for three different flush volumes (3, 4.5 and 6 litres). To investigate the impact of solid shape factor, a number of tests were carried out using synthetic solids in combination with toilet tissue paper. In total, more than 1,000 tests were performed for different operational and design parameter combinations. Results obtained to date have confirmed earlier studies, particularly with respect to the role of flush volume in solids transport, and identified the impact of gradient variation and its significance particularly in small-bore sewers receiving low flush volume. Results from the physical model application exercise will be used to propose new design guidelines for wastewater collection systems with specific consideration to new developments and inform the decision support system, currently being developed as part of a research project on water cycle management for new developments (WaND).

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