Assessing the impact of meta-model evolution: a measure and its automotive application

2017 ◽  
Vol 18 (2) ◽  
pp. 1419-1445
Author(s):  
Darko Durisic ◽  
Miroslaw Staron ◽  
Matthias Tichy ◽  
Jörgen Hansson
Keyword(s):  
Automotive Application ◽  
Model Evolution ◽  
Meta Model ◽  
The Impact

Performance and Lightweight Thermoplastic Materials for Automotive Application using Hollow Microspheres

2014 ◽  
Vol 611-612 ◽  
pp. 859-867 ◽  
Author(s):  
Awa S. Doumbia ◽  
Denis Jouannet ◽  
Thierry Falher ◽  
Laurent Cauret
Keyword(s):  
Glass Fibers ◽  
Pilot Scale ◽  
Melt Processing ◽  
Hollow Microspheres ◽  
Automotive Application ◽  
Regulatory Requirements ◽  
Innovative Design ◽  
Passenger Vehicles ◽  
Mineral Fillers ◽  
The Impact

In recent decades, the weight of passenger vehicles has constantly increased. This leads to a rise in fuel consumption and higher CO2 emissions. On this basis, vehicle weight reduction is a privileged research axis to meet regulatory requirements on emissions by 2020. The current study is focused on the development of thermoplastic polymer used in the automotive sector. In fact, thermoplastic polymers allow innovative design and offer the advantage of being recycled for sustainable development purposes. Some lighter fillers were incorporated in this polymer by melt processing for weight saving benefits. We were interested mainly in hollow microspheres which are lower density than conventional mineral fillers (such as: talc, calcium carbonate, glass fibers etc ...). This study explores the impact of pilot-scale melt-processing on six (6) hollow microspheres embedded in high impact polypropylene commonly used for car bumpers. We found that two commercially available microspheres (grades iM30K and K37) withstand melt-processing successfully and reduce the polymer density.

New Emerging Al7075 Based Hybrid Nanocomposite for Automotive Applications: A Sustainability Approach

2020 ◽  
Vol 856 ◽  
pp. 29-35
Author(s):  
Sweety Mahanta ◽  
M. Chandrasekaran ◽  
Sutanu Samanta
Keyword(s):  
Tensile Strength ◽  
Impact Strength ◽  
Hybrid Composites ◽  
High Strength ◽  
Stir Casting ◽  
Automotive Application ◽  
Percentage Increase ◽  
Casting Technique ◽  
Ultrasonic Assisted Stir Casting ◽  
The Impact

Aluminium matrix composites (AMCs) have emerged as the substitute for the monolithic (unreinforced) materials over the past few decades. The applications of AMCs are common in automotive, aerospace, defence and biomedical sectors due to its lower weight, high strength, high resistance against corrosion and high thermal and electrical conductivity. In this work, it is aimed fabricate a new class Al 7075 based hybrid composites reinforcing with nanoparticulates suitable for automotive application. Al7075 reinforced with fixed quantity of boron carbide (B4C) (1.5 wt.%) and varying wt % of flyash (0.5 wt.%, 1.0 wt.%, 1.5 wt.%) is fabricated using ultrasonic-assisted stir casting technique. Physical and mechanical characterization such as density, porosity, micro hardness, tensile strength and impact strength were estimated for three different compositions. The tensile strength and percentage increase in hardness value of the nanocomposite Al7075-B4C (1.5 wt. %)-flyash (0.5 wt. %): HNC3 found maximum as 294 MPa and 32.93%. In comparison with Al7075 alloy the impact strength of HNC3 shows the highest percentage of 9.31% respectively.

Simulation Study on Electric Turbo-Compound (ETC) for Thermal Energy Recovery in Turbocharged Internal Combustion Engine

2015 ◽  
Vol 799-800 ◽  
pp. 895-901
Author(s):  
Alias Mohd Noor ◽  
Rosnizam Che Puteh ◽  
Srithar Rajoo ◽  
Uday M. Basheer ◽  
Muhammad Hanafi Md Sah ◽  
...  
Keyword(s):  
Thermal Energy ◽  
Energy Recovery ◽  
Internal Combustion Engines ◽  
Waste Heat ◽  
Internal Combustion ◽  
Automotive Application ◽  
System Modelling ◽  
Brake Mean Effective Pressure ◽  
Major Interest ◽  
The Impact

Exhaust gas heat utilization in the form of Thermal Energy Recovery (TER) has attracted a major interest due to its potentials with Internal Combustion Engines (ICE). Recovering useful energy, for example in the form of electrical power from the engine exhaust waste heat could benefit in the form of direct fuel economy or increase in the available electric power for the auxillary systems. The methodology in this paper includes the assessment of each waste heat recovery technology based on the current research and development trends for automotive application. It also looked into the potential for energy recovery, performances of each technology and factors affecting its implementation. Finally, the work presents an Electric Turbo Compounding (ETC) simulation using a Ford Eco-Boost as a baseline engine modeled with the 1-Dimensional AVL Boost software. A validated 1-D engine model was used to investigate the impact on the Brake Specific Fuel Consumption (BSFC) and Brake Mean Effective Pressure (BMEP) at full load. This paper presents some reviews on the turbo-compounding method and also the modelling efforts and results of an electric turbo-compounding system. Modelling shows that the turbo-compounding setup can be more beneficial than turbo-charging alone.

Automating the Migration of Enterprise Architecture Models

2016 ◽  
Vol 7 (2) ◽  
pp. 72-90 ◽  
Author(s):  
Nuno Silva ◽  
Francisco Ferreira ◽  
Pedro Sousa ◽  
Miguel Mira da Silva
Keyword(s):  
Enterprise Architecture ◽  
Development Projects ◽  
Migration Process ◽  
Model Evolution ◽  
Management Tools ◽  
Meta Model ◽  
Manual Task ◽  
Business Requirements ◽  
Enterprise Architectures

The evolution of Enterprise Architectures (EA) is the result of applying EA development projects within organizations with the goal of accomplishing specific business requirements. Recent approaches seek to automate and improve EA practice within organizations by employing EA management tools. Thus, evolving the organization's EA meta-model is a consequence of fulfilling such initiatives. Currently, the migration of EA models conforming to a specific EA meta-model evolution is a manual task in which EA data corresponding to the actual models is gathered and the models re-designed. This results in an error-prone and time-consuming task. To address this issue, the authors propose a set of migration rules to automate the migration process. The proposed migration rules were implemented within an EA tool and then demonstrated and validated using a fictitious organization migration scenario.

Second-Moment-Based Design of Dynamic Systems with Both Uncertain Excitations and Parameters Via Differentiable Meta-Models

2019 ◽  
Vol 26 (04) ◽  
pp. 1950019
Author(s):  
G. J. Savage ◽  
Young Kap Son
Keyword(s):  
Least Squares ◽  
Dynamic Systems ◽  
Mechanistic Model ◽  
Computational Effort ◽  
Response Matrix ◽  
Computationally Efficient ◽  
Meta Model ◽  
Second Moments ◽  
Performance Indexes ◽  
The Impact

Design using second-moments is readily understood by engineers. The output means (first-moments) and covariances (second-moments) are expressed through the means and covariances of the inputs. Further, various performance indexes can be formulated in terms of the second-moments and used to measure the “goodness” of the system’s performance. This paper addresses the design of nonlinear dynamic systems with uncertainty in both the component parameters and the excitations. In order to reduce the computational effort needed for design iterations on the mechanistic model, meta-models are introduced as computationally efficient surrogates. Herein, a novel, differentiable, meta-model that finds the response of dynamic systems with simultaneous component and excitation uncertainty is presented. Operationally, a family of training excitations and sets of training parameters are chosen and stored in respective matrices. Both types of inputs must have some realistic bounds. The corresponding responses, produced by the mechanistic model, make use of all of the training parameter sets interleafed with the training excitations: the time-sampled results are stored in the response matrix. An application of singular value decomposition on the response matrix reveals a repeating pattern of sub-vectors in the left singular vectors. Each sub-vector (viewed as the output) is replaced by a least-squares meta-model that links in the parameter matrix. The result is a parameter-response matrix with the same number of rows as the excitation matrix. Finally, to complete the meta-model, another application of the least-squares paradigm links the excitation matrix to the columns of the parameter-response matrix. Performance indexes, and approximations of their means and covariances through Taylor series, provide cogent optimization measures. The required derivatives are easily obtained from the explicit form of the meta-model. The efficacy of the meta-model is shown through the design of a nonlinear, quarter automobile, system. The accuracy, increased computation speed and robustness of the methodology provide the impact of the work herein. The sources of errors are identified and ways to mitigate them are discussed.

Estimation of Bending Fatigue Life of Hypoid Gears Using a Multiaxial Fatigue Criterion

2013 ◽  
Vol 135 (10) ◽  
Author(s):  
M. A. Hotait ◽  
A. Kahraman
Keyword(s):  
Crack Initiation ◽  
Multiaxial Fatigue ◽  
Automotive Application ◽  
Hypoid Gear ◽  
Hypoid Gears ◽  
Bending Fatigue ◽  
Fatigue Model ◽  
Time Histories ◽  
The Impact ◽  
Fatigue Criterion

In this study, a crack initiation life prediction methodology for the tooth bending fatigue of hypoid gears is proposed. This methodology employs a previously developed finite-element based hypoid gear root stress model (Hotait et al. 2011, “An Investigation of Root Stresses of Hypoid Gears with Misalignments,” ASME J. Mech. Des., 133, p. 071006) of face-milled and face-hobbed hypoid gears to establish the multiaxial stress time histories within the root fillet regions. These stress time histories are combined with a multiaxial crack initiation fatigue criterion to predict life distributions along roots of the pinion and the gear. The predictions of the multiaxial fatigue model are compared to those from a conventional uniaxial fatigue model to establish the necessity for a multiaxial approach. The model is exercised with an example face-milled hypoid gear set from an automotive application to demonstrate the impact of various misalignments well as the key cutting tool parameters on the resultant tooth bending lives.

Evaluation of the Influence of Volute Roughness on Turbocharger Compressor Performance From a Manufacturing Perspective

2014 ◽  
Author(s):  
A. Javed ◽  
E. Kamphues
Keyword(s):  
Sensitivity Analysis ◽  
Surface Roughness ◽  
Automotive Application ◽  
Performance Sensitivity ◽  
Performance Variation ◽  
Compressor Performance ◽  
The Impact ◽  
Limited Surface ◽  
Made In ◽  
A Performance

This paper presents a comprehensive surface roughness evaluation of a mass-produced turbocharger centrifugal compressor for automotive application. The aim is to study the impact of surface roughness on compressor performance and manufacturability of the volute. Surface roughness data for different components has been obtained from drawing specifications and sample measurements. Detailed compressor performance evaluation has been made in three parts using CFD. In the first part, the overall compressor performance variation has been simulated from stall to choke over a speed line; initially with all smooth surfaces and later, with rough surfaces. The second part decomposes the performance variation into its sources by simulating each compressor component individually with its specific roughness. Moreover, a performance sensitivity analysis has been conducted to identify the components most responsive to limited surface roughness deviation. In the third part, the volute is subdivided into five sections and a performance sensitivity analysis has been performed by sequentially varying the surface roughness for each section within a particular deviation range. The analysis revealed the sections which essentially require smoothing via sand core coating. Lastly, the roughness specifications have been reviewed especially for the volute, keeping in view the benefits the new specifications may have on overall compressor performance and manufacturing costs.

A Method for Aspect-oriented Meta-Model Evolution

2014 ◽  
Author(s):  
Reiner Jung ◽  
Robert Heinrich ◽  
Eric Schmieders ◽  
Misha Strittmatter ◽  
Wilhelm Hasselbring
Keyword(s):  
Model Evolution ◽  
Meta Model

UMLS Semantic Network as a UML Metamodel for Improving Biomedical Ontology and Application Modeling

2015 ◽  
Vol 10 (2) ◽  
pp. 34-56 ◽  
Author(s):  
Rishi Kanth Saripalle
Keyword(s):  
Software Engineering ◽  
Health Informatics ◽  
Semantic Network ◽  
Medical Knowledge ◽  
Current Status ◽  
Domain Modeling ◽  
Modeling Framework ◽  
Meta Model ◽  
Medical Concepts ◽  
The Impact

In the domain of biomedical and health informatics, ontologies are widely used to capture knowledge ranging from bioinformatics such as gene, protein, protein interactions, etc. to clinical/healthcare informatics knowledge such as diseases, symptoms, treatment, medication, etc. Currently, one medical knowledge source that encapsulates a broad spectrum of medical knowledge is the Unified Medical Language System (UMLS), which can be defined as a compendium of diverse medical ontological standards. The primary components of the UMLS are: Semantic Network (UMLS-SN) – designed by interconnecting well-defined semantic types with semantic relationships, and Metathesaurus (UMLS-META) – the base of UMLS system that is comprised of millions of medical concepts from diverse medical standards. However, within the biomedical and health informatics community, the concepts of software engineering and domain modeling (using meta-models such as ERD, UML, and XML) are very successful in designing and implementing biomedical/health domain application models. In the current status, the UMLS-SN is primarily employed for classification of medical concepts in UMLS-META, but UMLS-SN knowledge can't be viewed or employed as a modeling framework for designing ontological models and is restricted to the UMLS environment. Thus, the impact of the biomedical semantics captured by UMLS-SN might be minimal in medical facilities, research and healthcare organizations that are highly influenced by software engineering, meta-models and domain model-based practices. In order fill this gap, the authors propose a meta-modeling framework for UMLS-SN based on the UML Profile (built using UML meta-model) that will result in a customized domain specific meta-model. This specialized meta-model that encapsulates the medical knowledge semantics of UMLS-SN can then be employed for designing ontological models or relevant healthcare application models and simultaneously be coherent with software meta-models and domain modeling practices.

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