Clustered Cell Parallelization for GPU Computing of Silicon Anisotropic Etching Simulation

The parallelization of silicon anisotropic etching simulation with the cellular automata (CA) model on graphics processing units (GPUs) is challenging, because the numbers of computational tasks in etching simulation dynamically change and the existing parallel CA mechanisms do not fit in GPU computation well. In this paper, an improved CA model, called clustered cell model, is proposed for GPU-based etching simulation. The model consists of clustered cells, each of which manages a scalable number of atoms. In this model, only the etching and update of states for the atoms on the etching surface and their unexposed neighbors are performed at each CA time step, whereas the clustered cells are reclassified in a longer time step. With this model, a crystal cell parallelization method is given, where clustered cells are allocated to threads on GPUs in the simulation. With the optimizations from the spatial and temporal aspects as well as a proper granularity, this method provides a faster process simulation. The proposed simulation method is implemented with the Compute Unified Device Architecture (CUDA) application programming interface. Several computational experiments are taken to analyze the efficiency of the method.

Creating by Imagining: Use of Natural and Intuitive BCI in 3D CAD Modeling

Since its inception, computer aided 3D modeling has primarily relied on the Windows, Icons, Menus, Pointer (WIMP) user interface. WIMP has rarely been able to tap into the natural intuitiveness and imagination of the user which accompanies any design process. Brain-computer interface (BCI) is a novel modality that uses the brain signals of a user to enable natural and intuitive interaction with an external device. The BCI’s potential to become an important modality of natural interaction for 3D modeling is almost limitless and unexplored. In theory, using BCI one can create any 3D model by simply thinking about it. This paper presents a basic framework for using BCI as an interface for computer aided 3D modeling. This framework involves the task of recording and recognizing electroencephalogram (EEG) brain wave patterns and electromyogram (EMG) signals corresponding to facial movements. The recognized EEG/EMG brain signals and associated keystrokes are used to activate/control different commands of a CAD package. Eight sample CAD models are created using the Emotiv EEG head set based BCI interface and Google SketchUp and presented to demonstrate the efficacy of the developed system based on the framework. To further exhibit BCI’s usability, human factor studies have been carried out on subjects from different backgrounds. Based on preliminary results, it is concluded that EEG/EMG based BCI is suitable for computer aided 3D modeling purposes. Issues in signal acquisition, system flexibility, integration with other modalities, and data collection are also discussed.

Function-to-Form Mapping in Design Synthesis Taking Sustainable Manufacturing Issues Into Consideration

The function-to-form (F-T-F) mapping methodology provides a generic reasoning mechanism used in early design synthesis process to help designer map functional requirements of a product to a physical form (product) by optimally composing a set of pre-defined artifacts to satisfy the given physical constraints and design goals. The objective of this paper is to develop an integrated function-to-form technique that incorporates environmental constraints and other sustainable manufacturing issues into a previous function-to-form mapping framework. Since sustainability is considered as a global constraint for any product, a top-down design strategy and an assembly-centric product representation are needed for the product’s global evaluation and optimization. In this paper, it is proposed to integrate the Design for Manufacturing and Assembly (DFMA) and Life Cycle Assessment (LCA) techniques into the function-to-form mapping framework for considering the assemblability, manufacturability and other issues related to the product’s environmental impacts in its early design stage. A case study has been presented as a proof-of-concept of the proposed methodology.

Triangle Mesh Based In-Process Workpiece Update for General Milling Processes

A new methodology for modeling and updating the in-process workpiece geometry in milling is presented in this paper. The methodology is developed for general milling processes, in which the cutter can be any shape and follow any tool path trajectory even with self-intersections. And the in-process workpiece is updated with retained sharp features. The associated procedure starts by modeling both the cutter and the workpiece as closed manifold triangle meshes. The mesh model of the cutter swept volume is then generated from repeatedly sampled mesh vertices of the cutter along its trajectory using the ball-pivoting algorithm. The workpiece is updated by a subtraction Boolean operation between the workpiece and the cutter swept volume. An octree space partitioning algorithm is adopted in order to efficiently obtain the exact triangle-to-triangle intersection points. As the last step, a filling operation is performed around the intersection points to establish the closed manifold updated workpiece geometry. Several case studies have been performed to demonstrate the effectiveness of the proposed methodology.

Predicting Reliability of Structural Systems Using Classification Method

This research examines classification approaches for estimating the reliability of structural systems. To validate the accuracy and efficiency of the classification methods, a practical engineering problem; namely, a spider assembly of a washing machine, has been considered. For the spider assembly, fatigue life test, finite element analysis, physical experimentation, and a classification processes are conducted in order to establish the analytical certification of its current design. Specifically, the finite element analysis and fatigue life analysis are performed and their results are validated compared to physical experimental results. The classification process is developed to estimate the probability of failure of the spider assembly in terms of stress and fatigue life. The relationship between the random quantities and structural responses of the spider assembly is established using probabilistic neural network and the support vector machine classifiers. The performance margin of the spider assembly is fully identified based on the estimated failure probability and structural analysis results from the fatigue life analysis and classifications.

Implicit Boundary Approach for Reissner-Mindlin Plates

Implicit boundary method enables the use of background mesh to perform finite element analysis while using solid models to represent the geometry. This approach has been used in the past to model 2D and 3D structures. Thin plate or shell-like structures are more challenging to model. In this paper, the implicit boundary method is shown to be effective for plate elements modeled using Reissner-Mindlin plate theory. This plate element uses a mixed formulation and discrete collocation of shear stress field to avoid shear locking. The trial and test functions are constructed by utilizing approximate step functions such that the boundary conditions are guaranteed to be satisfied. The incompatibility of discrete collocation with implicit boundary approach is overcome by using irreducible weak form for computing the stiffness associated with essential boundary conditions. A family of Reissner-Mindlin plate elements is presented and evaluated in this paper using several benchmark problems to test their validity and robustness.

Design Ideation Framework to Support Reframing and Reformulation

The long term aim of this research is to develop a framework for holistic ideation which will integrate both intuitive and experiential methods. Towards that goal, we have developed a computer tool that consists of a variety of disparate knowledge-bases, databases and design repositories that the designer can choose from as his ideation state evolves. Such a strategy is in contrast with the approach of using a single ideation method/tool. Conceptual design requires both problem formulation/re-formulation and alternative generation. This paper discusses an organizational framework to support reformulation and ideation in a multi-tool environment. The proposed framework consists of cascading hierarchical morphological charts that are dynamic. We also discuss how this framework can be used in supporting provocative stimuli, analogical reasoning and make random or deliberate connections between sub-solutions. Web implementation of the tool will make it available to the design community for education and experimentation.

Defining the Phenomenon of Mental Models for Critical Events

People use cognitive representations in order to characterize, understand, reason and predict the surrounding world. A class of these representations are called mental models. Designers of informing systems are interested in how mental models influence decision making, especially during critical events. With this knowledge they could optimize the content and amount of information that is needed for a dependable decision making process. New insights are needed about the operation of mental models in the course of critical events, as well as on how informing influences the real life operationalization of mental models. Most of the definitions available in the literature are overly general, and no definition was found that would support the design of informing systems for critical events. Therefore, the objective of our research was to derive a definition of mental models that play a role in critical events. Actually, we systematically constructed a definition from those attributes of mental model descriptions that were found to be relevant to critical events. First we decomposed 125 published descriptions to a set of attributes, and then assessed each attribute to see if they were associated with critical events, or not. In fact, this analysis involved not only the relevance of the attributes to critical events, but also the frequency of occurrence in the surveyed papers. This exploration provided a large number of attributes for a new mental model definition. Based on the top rated attributes, a definition was synthesized which, theoretically, has a strong relation to critical events. Though further validation will be needed, we argue that the derived mental model definition is strong because it establishes relationships with all generic features of critical events and makes the related information contents explicit. Hence the proposed definition can be considered a starting platform for investigations of the influence of informing on decision making processes in critical events.

Post-Tsunami Evacuation Simulation Using 3D Kinematic Digital Human Models and Experimental Verification

A post-tsunami evacuation simulation using 3D kinematic digital human models (KDHs) and its experimental verification are addressed in the present study. Methods for carrying or assisting (transporting) injured people were experimentally investigated and the results were used for KDH data calibration to increase the accuracy of the simulations. It was found that, on flat ground, both the transit speed and the amount of time spent on intermittent rests were strongly affected by the load on the transporters. During ascent of stairways, the transit speed depended on the type of carry method being used, and decreased in the order saddleback carry, two-person arm carry and slightly injured walking. Several KDH evacuee motion primitives were developed for stairway ascent to a tsunami evacuation tower. The simulation results show that the evacuation time was affected by the number of evacuees and the congestion due to the transportation of injured people. The developed simulation techniques can be effectively utilized in the planning of tsunami tower evacuation and predicting related crowd behavior.