Browsing by Subject "Optimal design"

Now showing 1 - 4 of 4

Open Access
Designing emergency response networks for hazardous materials transportation
(2007) Berman O.; Verter V.; Kara, B.Y.
Undesirable consequences of dangerous goods incidents can be mitigated by quick arrival of specialized response teams at the accident site. We present a novel methodology to determine the optimal design of a specialized team network so as to maximize its ability to respond to such incidents in a region. We show that this problem can be represented via a maximal arc-covering model. We discuss two formulations for the maximal arc-covering problem, a known one and a new one. Through computational experiments, we establish that the known formulation has excessive computational requirements for large-scale problems, whereas the alternative model constitutes a basis for an efficient heuristic. The methodology is applied to assess the emergency response capability to transport incidents, that involve gasoline, in Quebec and Ontario. We point out the possibility of a significant improvement via relocation of the existing specialized teams, which are currently stationed at the shipment origins. © 2005 Elsevier Ltd. All rights reserved.
Open Access
Optimal stochastic design for multi-parameter estimation problems
(IEEE, 2014- 05) Soğancı, Hamza; Gezici, Sinan; Arıkan, Orhan
In this study, we consider performance improvement of an array of fixed estimators by using stochastic design techniques. The optimal design is investigated both in the absence and presence of an average power constraint. Two different performance criteria are considered; the average Bayes risk and the maximum Bayes risk. It is shown that the optimal stochastic parameter design results in a randomization between different numbers of parameter values depending on the type of the performance criterion. © 2014 IEEE.
Open Access
Optimal stochastic signal design and detector randomization in the Neyman-Pearson framework
(IEEE, 2012-03) Dülek, Berkan; Gezici, Sinan
Power constrained on-off keying communications systems are investigated in the presence of stochastic signaling and detector randomization. The joint optimal design of decision rules, stochastic signals, and detector randomization factors is performed. It is shown that the solution to the most generic optimization problem that employs both stochastic signaling and detector randomization can be obtained as the randomization among no more than three Neyman-Pearson (NP) decision rules corresponding to three deterministic signal vectors. Numerical examples are also presented. © 2012 IEEE.
Open Access
Trapping of vibration energy into a set of resonators: theory and application to aerospace structures
(2012) Carcaterra, A.; Akay, A.; Bernardini, C.
This paper presents the theory of a novel mechanism of energy absorption and induced damping in structural systems and its application to aerospace industry. The underlying principles of the physical phenomena have been addressed in several earlier publications, which focused on prototypical systems of absorbers that consist of a set of single-degree-of-freedom resonators. This paper generalizes those theoretical developments to the case of a cluster of beams attached to a continuous primary structure, to develop predictive methods for the expected performance of this new type of absorber, with particular emphasis on its optimal design. An embodiment of the conceived device is illustrated for an aerospace structure, a satellite, with the purpose of reducing the vibration of the electronic components on board during lift-off. Experimental results illustrate the feasibility and the attractiveness of this new absorption technique. © 2011 Elsevier Ltd. All rights reserved.