Warm forming die design,part I: Experimental validation of a novel thermal finite element modeling code

Finite element analysis (FEA) has become an invaluable tool in the design of sheet metal stamping dies and processes. FEA has gained widespread acceptance as the best method of optimizing dies for conventional stamping processes. More recently, FEA has been shown to be an effective method of designing tooling for sheet forming processes. In this work, an FEA based approach is applied to the warm stamping (warm forming) process. This work introduces a new thermal finite element analysis software called PASSAGE®/Forming (PASSAGE) that enables the up-front design of the thermal management of warm forming dies. This thermal finite element analysis software is designed to specifically handle the forming and optimization scenarios related to the heating of a stamping die while minimizing user interface time. In this work, PASSAGE has been applied to a simple block of steel embedded with cartridge heaters to validate the prediction capability of this software under two different heating conditions. The results show that PASSAGE is capable of predicting the actual steady-state temperature distribution within the block with an acceptable level of accuracy while yielding notable information to the user with respect to specifying power requirements. A finite element software package like PASSAGE is a valuable tool that will aid greatly in the implementation of warm forming as a manufacturing process beyond the scope of the laboratory and into production.     

Part based process performance monitoring (PbPPM)

The performances of completed manufacturing processes were evaluated using the surface response to excitation (SuRE) and Lamb wave methods. Both methods used the same piezoelectric elements attached to the surface of the workpiece. The SuRE method and the Lamb wave method were used to identify the structural changes created by welding, drilling, coating, filling a slot with glue, and composite patching. This study indicates that the tested methods are feasible for part based process performance monitoring (PbPPM) which evaluates the quality of the completed process with the sensors attached to the workpiece.     

Meeting emission targets under uncertainty—the case of Finnish non-emission-trading sector

The European Union (EU) has set a target to reduce its greenhouse gas (GHG) emissions at least 10 % below the 2005 levels by 2020 in the non-Emission Trading Sector (non-ETS). As part of this, each Member State has a binding national emission limitation target for the non-ETS sector. Finland’s target, examined as a case study in this paper, is to reduce emissions at least 16 % below 2005 levels by 2020. The objective of this study is to find cost optimal mitigation portfolios that meet Finland’s reduction target and to analyze the risks of not attaining the emission target or exceeding the assumed costs. The question was addressed with a stochastic optimization model, Stochastic Optimization of non-ETS Emissions (SONETS) selecting separate mitigation measures that meet the target on expectation. The results show that optimal portfolios include relatively high uncertainty both in costs and achieved reductions. The prices of crude oil and diesel, and the abatement cost of reducing hydrofluorocarbon (HFC) emissions seem to account for the majority of uncertainty regarding total costs. The baseline predictions for various non-ETS subsectors (such as transport and agriculture) were found to have the greatest contribution to the uncertainty of attaining emission target. The results also show that some abatement actions are chosen in nearly all efficient portfolios, while other actions are seldom chosen. For example replacing oil burners in the end of technical life time or recovery of methane (CH₄) from waste are often chosen whereas ban of landfilling of organic waste is chosen extremely seldom. It also seems that the results are somewhat sensitive to the inclusion or exclusion of the interdependencies of mitigation measures.     

Dimensional analysis and scaling in mechanical mixing for fabrication of metal matrix nanocomposites

For a successful enhancement of mechanical properties of metal matrix nanocomposites, a homogeneous nanoparticle dispersion and distribution in the solidified metal is required. Mechanical mixing can be used for initial break-up of agglomerates, and its study can be simplified with dimensional analysis. Using this technique, mixing time and vortex height were assessed while varying fluid properties, impeller angle, and angular speed. Three relevant dimensionless numbers were recognized: the Reynolds (Re), Froude and Galilei (Ga) numbers. Based on blade and impeller shaft angles, a modified Froude number (Fr*) was defined. These parameters were calculated experimentally, varying angular speed from 200 to 1000 rpm for three different impeller angles: 0°, 15° and 30°. This procedure was performed with three fluids: water, and two aqueous glycerin solutions (25% and 50% by volume). Digital images were taken and processed to measure vortex height. Mixing time was measured for water at 0° impeller angle, angular speed ranging from 200 to 1200 rpm. Results showed an optimal dimensionless mixing time with respect to Re. A linear relationship was found between dimensionless vortex height and Fr*. The first had a second order polynomial relationship with the product ReFr*, regardless of impeller angle. This relationship, together with the Ga, specific for each fluid, allows scaling the results to other fluids such as molten pure aluminum. This study allows experimenting in simpler systems that involve transparent fluids, room temperature and low cost, to then elaborate a prediction of vortex height in fluids where measurements are difficult and costly, such as molten metals.     

Building regional priorities in forests for development and adaptation to climate change in the Congo Basin

Indentifying common priorities in shared natural resource systems constitutes an important platform for implementing adaptation and a major step in sharing a common responsibility in addressing climate change. Predominated by discourses on REDD + (Reduced Emissions from Deforestation and Forest Degradation and conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries) with little emphasis on adaptation there is a risk of lack of policy measures in addressing climate change in the Congo Basin. Forest products and ecosystem services provide security portfolios for the predominantly rural communities, and play major roles in national development programmes in both revenue and employment opportunities. Thus, raising the profile of forests in the policy arena especially in the twin roles of addressing climate change in mitigation and adaptation and achieving resilient development is crucial. Within the framework of the Congo Basin Forests and Climate Change Adaptation project (COFCCA) project, science policy dialogue was conducted to identify and prioritize forest based sectors vulnerable to climate change but important to household livelihoods and national development. The goal of the prioritization process was for the development of intervention in forest as measures for climate change adaptation in Central Africa. Participants constituted a wide range of stakeholders (government, Non Governmental Organizations, research institutions, universities, community leaders, private sectors etc.) as representatives from three countries directly involved in the project: Cameroon, Central African Republic and Democratic Republic of Congo. Building on national priorities, four forest related sectors were identified as common priorities at the regional level for focus on climate change adaptation. These sectors included: (1) energy with emphasis on fuel wood and Charcoal; (2) Water principally quality, quantity, accessibility, etc.; (3) Food with emphasis on Non Timber Forest Products, and (4) Health linked to healthcare products (medicinal plants). Using these prioritized sectors, the project focused on addressing the impacts of climate change on local communities and the development of adaptation strategies in the three pilot countries of the Congo Basin region. The four sectors constitute the key for development in the region and equally considered as priority sectors in the poverty reduction papers. Focused research on these sectors can help to inject the role of forests in national and local development and their potentials contributions to climate change adaptation in national and public discourses. Mainstreaming forest for climate change adaptation into national development planning is the key to improve policy coherence and effectiveness in forest management in the region.     

Establishment of facultative sexuals

The existence of sex is one of the major unsolved problems in biology. We use computer simulations to model conditions in which sex may first become established. We develop an individual-based population model and show that a hypothetical facultative sex gene can fix, provided that the initial cost is low. It is demonstrated that the equilibrium fitness in the population increases with increasing population size and decreasing mutation rate. The probability of the establishment of the sex gene is found not to be directly related to the fitness difference between the asexual and sexual populations. This change in fitness on changing the parameters of the model is investigated.     

Impact analysis of drought, water excess and salinity on grass production in The Netherlands using historical and future climate data

The coupled SWAP-WOFOST model was used to study the effects of increasing salinity of groundwater, drought and water excess on grass production in The Netherlands. WOFOST simulates crop growth and SWAP simulates transport of water, solutes and heat in the vadose zone. The model was tested using several datasets from field experiments. We applied the models at regional scale where we quantified the impact of various groundwater salinity levels on grass growth and production using historical weather data (1971-2000). The salt concentrations in the subsoil were derived from the National Hydrological Instrument. The results show that salinity effects on grass production are limited. In wet years the excess rainfall will infiltrate the soil and reduce salt water seepage. In a next step we used future weather data for the year 2050, derived from 3 Global Circulation Models. From each model we used data from two CO₂ emission scenarios. As expected higher temperatures increased drought stress, however, the production reduction as a result of salt water in the root zone is limited. Salt stress mainly occurred when irrigation was applied with saline water. The increased CO₂ concentration in combination with the limited drought stress resulted in increasing simulated actual and potential yields. Overall conclusion for grassland in The Netherlands: drought stress is stronger than stress caused by water excess which on its turn is stronger than salinity stress. Future water demand for irrigation may increase by 11-19% and result in water scarcity if water supply is insufficient.