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Lookup tables and functions are widely used in real-time embedded automotive applications to conserve scarce processor resources. To minimize the resource utilization, these lookup tables (LUTs) commonly use custom data structures. The lookup function code is optimized to process these custom data structures. The legacy routines for these lookup functions are very efficient and have been in production for many years. These lookup functions and the corresponding data structures are typically used for calibration tables. The third-party calibration tools are specifically tailored to support these custom data structures. These tools assist the calibrators in optimizing the control algorithm performance for the targeted environment for production. Application software typically contains a mix of both automatically generated software and manually developed code. Some of the same calibration tables may be used in both auto generated and hand-code [ 1 ] [ 2 ].

Diesel particulate trap regeneration is a complex process involving the interaction of phenomena at several scales. A hierarchy of models for the relevant physicochemical processes at the different scales of the problem (porous wall, filter channel, entire trap) is employed to obtain a rigorous description of the process in a multidimensional context. The final model structure is validated against experiments, resulting in a powerful tool for the computer-aided study of the regeneration behavior. In the present work we employ this tool to address the effect of various spatial non-uniformities on the regeneration characteristics of diesel particulate traps. Non-uniformities may include radial variations of flow, temperature and particulate concentration at the filter inlet, as well as variations of particulate loading. In addition, we study the influence of the distribution of catalytic activity along the filter wall.

In terms of manufacturing processes and systems, decision-makers may encounter difficulty in making environmentally friendly choices. This difficulty arises largely because of the nascency of environmentally responsible manufacturing. There is a sparsity of environmental information on processes and a variety of seemingly unconnected tools, methods, concepts, etc. To help decisions-makers understand the nature of a process and identify the appropriate tools/methods that may be most suited to reducing environmental impact, a classification system for manufacturing processes is established. Methods and tools for environmentally responsible manufacturing are then identified for each class. Two examples are presented to show how the new classification system may be applied in environmentally responsible manufacturing.

As the pool of existing non-renewable natural resources continues to shrink, it will be necessary for government and industrial leaders to achieve a workable strategy for the intelligent allocation of scarce resources. In this paper, a method of quantifying the environmental and resource impacts of product redesign is proposed. This new method utilizes Input Output Analysis coupled with the Markovian decision making into a single matrix-based tool. The benefit of a fully developed tool would be the ability to make informed pre-production decisions leading to optimum product and process designs with minimal environmental impact. This paper illustrates this technique with an example based upon real industry data and extrapolated effects.

Thermal Analysis (TA) can be a valuable analytical tool in the development of gasket materials. This technique can be helpful in qualifying raw materials and analyzing the thermal properties of gasket composites as it relates to performance. Examples of how TA can be utilized are cited, along with means of complementing other types of analysis.