Catálogo de publicaciones - libros

Active structures capable of responding to external stimulii represent the emerging frontier in structural design. Robust and real-time sensing, control, and actuation pose fundamental challenges that must be addressed in this context. As part of an ambitious project funded by the National Science Foundation, researchers at Purdue, Rice, Florida State, and the Catholic (Belgium) Universities have undertaken development of these core technologies. Over the past 18 months, considerable progress has been made in the areas of model reduction and control, sensing, and simulation-based validation. This paper describes our results in high-fidelity simulations of large structures, subject to various (mechanical and thermal) stresses.

A high-fidelity simulation infrastructure poses a number of challenges. These include geometric modeling (generating a suitable mesh for the structure), physical modeling (developing mathematical models for coupling between various phenomena, specifying material properties), computational modeling (developing efficient numerical schemes and their parallel formulations), and appropriate visualization techniques. We have made fundamental contributions in each of these areas. Here, we overview some of our major contributions, along with sample simulations of existing structures. As part of our ongoing work, we also aim to perform a high-fidelity simulation of the tragic World Trade Center (WTC) crash. To this end, we have developed, from available blueprints, a highly resolved geometric model of the WTC. We also aim to complement all of our computational studies with detailed experimental validation on full-scale structures at the Bowen Lab for Structural Engineering. To the best of our knowledge, this is the first comprehensive effort to fully integrate simulation and modeling with sensing, control, and actuation in an experimental setting. In this sense, we believe that this project is a novel realization of the concept of dynamic data-driven application systems in the realm of large-scale structures.

In the future, advanced biomechanical simulations of brain deformation during surgery will require access to multi-teraflop parallel hardware, supporting operating room infrastructure. This will allow surgeons to view images of intra-operative brain deformation within the strict time constraints of the surgical procedure – typically on the order of minutes, multiple times during a six or eight hour long surgery. In this paper we explore the grid infrastructure issues involved in scheduling, on-demand computing, data transfer and parallel finite element biomechanical simulation, which would guarantee that such a dynamic data driven real time application is actually feasible.

This paper presents a case study of interdisciplinary collaboration in building a set of tools to simulate and visualize airflow around bat wings during flight. A motion capture system is used to generate 3D coordinates of infrared markers attached to the wings of a bat flying in a wind tunnel. Marker positions that cannot be determined due to high wing deformation are reconstructed on the basis of the proper orthogonal decomposition (POD). The geometry obtained for the wings is used to generate a sequence of unstructured tetrahedral meshes. The incompressible Navier-Stokes equations in arbitrary Lagrangian-Eulerian formulation are solved using the hybrid spectral/hp element solver Nektar. Preliminary simulation results are visualized in the CAVE, an immersive, 3D, stereo display environment.

A state-of-the-art integrated environment was created to study interaction among fire, structure and agent models in a fire evacuation from a typical office building. For the fire simulations NIST large-eddy simulation code Fire Dynamics Simulator (FDS) was used. The code is based on a mixture fraction model. FDS provided time resolved temperature, CO, CO2, soot distribution in the building. The agent software was designed to simulate agent behaviors during evacuation by tracking the behavior of each individual in the building taking into account effects of temperature, CO, and soot on the behavior and health for each agent. The created integrated environment was designed to provide the bridge between multiple simulations for data transfer and model interaction. It was shown that fire position, agent positions, and number of exits available affect significantly agents’ health and death toll. The results can be used for better fire safety building design and regulations.

In crisis, decisions must be made in human perceptual timeframes under pressure to respond to dynamic uncertain conditions. To be effective management must have access to real time environmental data in a form that can be immediately understood and acted upon. The emerging computing model of Dynamic Data-Driven Application Systems (DDDAS) fits well in crisis situations where rapid decision-making is essential. We explore the value of a DDDAS (iRevive) in support of emergency medical treatment decisions in response to a crisis. This complex multi-layered dynamic environment both feeds and responds to an ever-changing stream of real-time data that enables coordinated decision-making by heterogeneous personnel across a wide geography at the same time. This complex multi-layered dynamic environment both feeds and responds to an ever-changing stream of real-time data that enables coordinated decision-making by heterogeneous personnel across a wide geography at the same time.

Ultimate DDDAS success demands that DDDAS simulations be increasingly reconfigurable and adaptable to a growing variety of runtime sensor feedback. Because we expect a simulation’s requirements to change during its lifetime, a new emphasis is placed on designing simulations that are prepared for transformation. In this paper, we address this new interest in designing for transformation. Our technology combines the specialized insight of simulation designers with the principled application of automation techniques to capitalize on untapped human and computational resources. In addressing simulation transformation issues that arise at design time, composition time, and runtime, we demonstrate how a semi-automated process impacts the entire simulation life cycle. The resulting suite of simulation transformation tools supports the crosscutting needs of DDDAS practitioners.

Recent advances in Dynamic Data Driven Application Systems (DDDAS) facilitated by the present level of computational technologies, as well as advances in data-driven modeling and simulation, impose the need for a critical evaluation of paradigms underlying Qualification, Validation and Verification (QV&V). This paper discusses the fundamental irrelevance of conventional validation procedures with respect to data-driven models and simulations. This inherent property of data-driven models and simulations makes the data-driven approaches extremely desirable from a reliability perspective. An informal comparison of the logical flow of traditional and evolved QV&V demonstrates the tautological nature of data-driven model validation. A brief epistemological review of the origins of traditional and evolved QV&V is also presented.

is a distributed virtual shared-memory implementation of a high-level parallel language for computational Grids. While the implementation delivers good speedups on multiple homogeneous clusters with low-latency interconnect, on heterogeneous clusters, however, poor load balance limits performance. Here we present new load management mechanisms that combine static and partial dynamic information to adapt to heterogeneous Grids. The mechanisms are evaluated by measuring four non-trivial programs with different parallel properties, and show runtime improvements between 17% and 57%, with the most dynamic program giving the greatest improvement.

We define the concepts of and as they arise in the description of skeletal parallel programming systems. We suggest that these new concepts encapsulate fundamental design issues and may play a useful role in defining and distinguishing between the capabilities of competing systems. We present the decisions taken in our own Edinburgh Skeleton Library , and review the approaches chosen by a selection of other skeleton libraries.

We propose a semantic framework for parallel programming based on the orthogonalization of data access and control concerns by means of set of abstraction mechanisms. Such mechanisms regard the description of how data has to be accessed, the description of how data has to be computed and the description of how coupling data accesses and patterns of control. Each description is represented by an abstraction mechanism formalized through a formal semantics. The set of semantics specifications defines a method to investigate the structure of the whole application. We demonstrate how this semantics provides a formal, provable method to statically or dynamically evaluate the overall performance of the application and, eventually, apply optimization rules.