scholarly journals Toward Automated Inventory Modeling in Life Cycle Assessment: The Utility of Semantic Data Modeling to Predict Real-World Chemical Production

2017 ◽  
Vol 6 (2) ◽  
pp. 1961-1976 ◽  
Author(s):  
Vinit K. Mittal ◽  
Sidney C. Bailin ◽  
Michael A. Gonzalez ◽  
David E. Meyer ◽  
William M. Barrett ◽  
...  
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Real World ◽  
Data Modeling ◽  
Chemical Production ◽  
Semantic Data ◽  
Semantic Data Modeling

A Meta-Analysis Comparing Relational and Semantic Models

2013 ◽  
pp. 394-409
Author(s):  
Keng Siau ◽  
Fiona F.H. Nah ◽  
Qing Cao
Keyword(s):  
Statistical Power ◽  
Meta Analysis ◽  
Data Modeling ◽  
Systems Development ◽  
Data Models ◽  
The Past ◽  
Semantic Data ◽  
Semantic Models ◽  
Semantic Data Modeling

Data modeling is the sine quo non of systems development and one of the most widely researched topics in the database literature. In the past three decades, semantic data modeling has emerged as an alternative to traditional relational modeling. The majority of the research in data modeling suggests that the use of semantic data models leads to better performance; however, the findings are not conclusive and are sometimes inconsistent. The discrepancies that exist in the data modeling literature and the relatively low statistical power in the studies make meta-analysis a viable choice in analyzing and integrating the findings of these studies.

OPEN ONTOLOGY-BASED INTEGRATION PLATFORM FOR MODELING AND SIMULATION IN ENGINEERING

2012 ◽  
Vol 03 (02) ◽  
pp. 1250004 ◽  
Author(s):  
TOMMI KARHELA ◽  
ANTTI VILLBERG ◽  
HANNU NIEMISTÖ
Keyword(s):  
Modeling And Simulation ◽  
System Integration ◽  
Data Modeling ◽  
Simulation Tools ◽  
Semantic Data ◽  
Engineering Information ◽  
Mapping Techniques ◽  
Aided Design ◽  
And Control ◽  
Semantic Data Modeling

The benefits of the use of modeling and simulation in engineering are acknowledged widely. It has proven its advantages e.g., in virtual prototyping i.e., simulation aided design and testing as well as in training and R&D. It is recognized to be a tool for modern decision making. However, there are still reasons that slow down the wider utilization of modeling and simulation in companies. Modeling and simulation tools are separate and are not an integrated part of the other engineering information management in the company networks. They do not integrate well enough into the used CAD, PLM/PDM and control systems. The co-use of the simulation tools themselves is poor and the whole modeling process is considered often to be too laborious. In this article we introduce an integration solution for modeling and simulation based on the semantic data modeling approach. Semantic data modeling and ontology mapping techniques have been used in database system integration, but the novelty of this work is in utilizing these techniques in the domain of modeling and simulation. The benefits and drawbacks of the chosen approach are discussed. Furthermore, we describe real industrial project cases where this new approach has been applied.

scholarly journals Sensitivity Analysis in the Life-Cycle Assessment of Electric vs. Combustion Engine Cars under Approximate Real-World Conditions

2020 ◽  
Vol 12 (3) ◽  
pp. 1241 ◽  
Author(s):  
Eckard Helmers ◽  
Johannes Dietz ◽  
Martin Weiss
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Real World ◽  
Emission Inventory ◽  
Combustion Engine ◽  
Climate Impacts ◽  
Impact Categories ◽  
Passenger Cars ◽  
Electric Cars ◽  
On The Road

This study compares the environmental impacts of petrol, diesel, natural gas, and electric vehicles using a process-based attributional life cycle assessment (LCA) and the ReCiPe characterization method that captures 18 impact categories and the single score endpoints. Unlike common practice, we derive the cradle-to-grave inventories from an originally combustion engine VW Caddy that was disassembled and electrified in our laboratory, and its energy consumption was measured on the road. Ecoivent 2.2 and 3.0 emission inventories were contrasted exhibiting basically insignificant impact deviations. Ecoinvent 3.0 emission inventory for the diesel car was additionally updated with recent real-world close emission values and revealed strong increases over four midpoint impact categories, when matched with the standard Ecoinvent 3.0 emission inventory. Producing batteries with photovoltaic electricity instead of Chinese coal-based electricity decreases climate impacts of battery production by 69%. Break-even mileages for the electric VW Caddy to pass the combustion engine models under various conditions in terms of climate change impact ranged from 17,000 to 310,000 km. Break-even mileages, when contrasting the VW Caddy and a mini car (SMART), which was as well electrified, did not show systematic differences. Also, CO2-eq emissions in terms of passenger kilometers travelled (54–158 g CO2-eq/PKT) are fairly similar based on 1 person travelling in the mini car and 1.57 persons in the mid-sized car (VW Caddy). Additionally, under optimized conditions (battery production and use phase utilizing renewable electricity), the two electric cars can compete well in terms of CO2-eq emissions per passenger kilometer with other traffic modes (diesel bus, coach, trains) over lifetime. Only electric buses were found to have lower life cycle carbon emissions (27–52 g CO2-eq/PKT) than the two electric passenger cars.

scholarly journals Life cycle assessment of fine chemical production: a case study of pharmaceutical synthesis

2010 ◽  
Vol 15 (3) ◽  
pp. 294-303 ◽  
Author(s):  
Gregor Wernet ◽  
Sarah Conradt ◽  
Hans Peter Isenring ◽  
Concepción Jiménez-González ◽  
Konrad Hungerbühler
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Chemical Production ◽  
Fine Chemical

Application of Semantic Data Modeling to Science and Engineering

1993 ◽  
Author(s):  
Naphtali Rishe ◽  
Qiang Li
Keyword(s):  
Data Modeling ◽  
Scientific Data ◽  
Environmental Engineering ◽  
Semantic Modeling ◽  
Science And Engineering ◽  
Database Model ◽  
Semantic Data ◽  
Engineering Database ◽  
Semantic Data Modeling

Abstract This paper describes the application of semantic modeling using the Semantic Binary Database Model, SBM, to the design of databases having embedded measurement and scientific data, as well as complex interrelations between various objects. A case study of an environmental engineering database is considered.

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