 |
|
Extreme Event Simulation
|
|
Building Fire Evacuation Simulation
- Particle Swarm Optimization (PSO) with human behaviors is used to simulate evacuation behavior as a result of fire. FDS is used for the fire modeling. The VACATE tool can be used to identify potential structural issues, simulate evacuation protocols, or even train first responders.
Emergency Vehicle Evacuation Simulation
-Heuristic-optimization coupled with human behaviors is used for this vehicle evacuation simulation capability. The approach can be used to help road network designers and first responders reveal potential problems in the event of an extreme event.
Pedestrian Evacuation Simulation
- This PSO-based simulator coupled with human behaviors simulates pedestrian movement as a result of an extreme event, capturing such behaviors as leader-follower, high risk taker, and group behaviors, amongst others. |
| |
| |
| |
|
Visualization of n-Dimensional Data for Design Selection
|
|
Hyperspace Pareto Frontier (HPF) Visualization
- This visualization approach is based on the Hyper-Space Diagonal Counting (HSDC) method. An n-dimensional Pareto frontier can be intuitively visualized in a lossless 2-D fashion.
Hyper-Radial Visualization (HRV)
- This new n-Dimensional visualziation method is based on a hyper-radial representation. The HRV is being used for concept selection in multi-attribute design.
Graph morphing Representation
- Graph Morphing Representation can help designers to obtain a better understanding of their complex problems. |
| |
|
Web-based Insfrastructures for Design and Collaboration
|
|
Visual Dependency Structure Matrix (VDSM)
- Coupled with underlying cost and error models, VDSM, a web-based framework, enables designers to explore the possibility of eliminating or suspending couplings on the fly.
Geographic Independent Virtual Environment (GIVE)
- Multiple designers from any geographic location can communicate through GIVE to share information about a design in real time.
Web-Based Visualization Environment For Decision-Making In Multidisciplinary Design Optimization
- A platform-independent visualization framework to assist the designers in their decision-making while solving MDO problems that could potentially have a physical representation.
Decision Support Tool For Multidisciplinary Design Optimazation (MDO)
- We want to understand and analyze the product development process effectively by capturing the dependencies within the three decomposition domains. |
| |
| |
| |
|
Multiobjective Optimization Methods for MDO
|
|
Multi-Objective Pareto Concurrent Subspace Optimization (MOPCSSO) method
- MOPCSSO is developed to concurrently handle the conflicting objectives that exist in multi-objective MDO problems.
Multi-Objective Range/Target Concurrent Subspace Optimization (MORTCSSO) method.
- MORTCSSO method can express the designer’s preferences through a combination of range and target specifications.
Multi-Objective Genetic Algorithm Concurrent Subspace Optimization (MOGACSSO) method.
- MOGACSSO method is a Genetic Algorithm-based heuristic solution strategy that can handle multi-objective problems in coupled multidisciplinary design. |
| |
| |
|
MDO Simulation and Validation
|
|
An MDO Test Suite
- An MDO Test Suite is under construction that will be available to the MDO community for testing and validation of a variety of MDO methodologies, including meta-model development (i.e. replacement analysis), optimization method development, and sensitivity analysis, amongst others. |
|
Optimization For Medical Imaging
|
|
Optimization in Medical Imaging
- Medical Imaging procedures frequently require inter- or intra-modality 3D object alignment. This project focuses on facilitating particle swarm optimization to find the optimal alignment between to similar 3D objects, in our case mouse-jaws used in a project of the UB Dental School in assessing bone decay. |
|
|
|
|
• Bloebaum leads interdisciplinary team of thirty faculty from across UB in developing an NSF IGERT preproposal on Infrastructure Resilience against Extreme Events (IREE). If funded, the IGERT would bring high quality domestic Ph.D. students to UB to work in areas of hazard science, infrastructure systems, cyberinfrastructure, and disaster management.
• MODEL student, Zhendan Xue, presents "A Particle Swarm Optimization-Based Behavioral and Probabilistic Fire Evacuation Model Incorporating Fire Hazards & Human Behaviors" at the 2007 Fire Conference at NIST.
• MDO Test Suite to go online Fall 2007. Sponsored by the American Institute of Aeronautics and Astronautics (AIAA) MDO Technical Committee, with the assistance and oversight of the Applications and Benchmarking subcommittee, the MDO Test Suite is being redeveloped, reformulated, and expanded for broad use in the MDO community to validate a wide range of methods. The new Test Suite should be available to the MDO community by November 2007.
•An interdisciplinary team from Mechanical and Aerospace Engineering, Urban and Regional Planning, School of Management, and School of Social Work, are developing new methodologies and simulation capabilities for multi-mode and multi-scale evacuation simulation.
|
|
|
|
• MDO Test Suite
Multidisciplinary design optimization (MDO) is an emerging field of engineering that uses optimization methods to solve inherently coupled design problems, typically involving multiple disciplines. MDO methods enable the design of complex coupled systems in which the synergistic effects of coupling between various interacting disciplines are explored and exploited at every stage of the design process.
The MDO test suite is a web-based suite for the collection, distribution and maintenance of standard MDO test problems. It includes standard test problems with problem descriptions, classification of the problems and their benchmark solution methods. This provides a platform for researchers to significantly advance the use of MDO in industry.
|
|
