Worcester Polytechnic Institute

About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Computer science & Population. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.

Invariant Properties of the Stress in Plane Elasticity and Equivalence Classes of Composites

Abstract: Attention is drawn to the invariance of the stress field in a two-dimensional body loaded at the boundary by fixed forces when the compliance tensor $\scr{G}$($\chi $) is shifted uniformly by $\ell^{\text{I}}$($\lambda $, -$\lambda $), where $\lambda $ is an arbitrary constant and $\scr{G}^{\text{I}}$($\kappa $, $\mu $) is the compliance tensor of a isotropic material with two-dimensional bulk and shear moduli $\kappa $ and $\mu $. This invariance is explained from two simple observations: first, that in two dimensions the tensor $\scr{G}^{\text{I}}$($\frac{1}{2}$, -$\frac{1}{2}$) acts to locally rotate the stress by 90 degrees and the second that this rotated field is the symmetrized gradient of a vector field and therefore can be treated as a strain. For composite materials the invariance of the stress field implies that the effective compliance tensor $\ell^{\ast}$ also gets shifted by $\scr{G}^{\text{I}}$($\lambda $, -$\lambda $) when the constituent moduli are each shifted by $\ell^{\text{I}}$($\lambda $, -$\lambda $). This imposes constraints on the functional dependence of $\ell^{\ast}$ on the material moduli of the components. Applied to an isotropic composite of two isotropic components it implies that when the inverse bulk modulus is shifted by the constant 1/$\lambda $ and the inverse shear modulus is shifted by -1/$\lambda $, then the inverse effective bulk and shear moduli undergo precisely the same shifts. In particular it explains why the effective Young's modulus of a two-dimensional media with holes does not depend on the Poisson's ratio of the matrix material.

Separating changes in the intra- and extracellular water apparent diffusion coefficient following focal cerebral ischemia in the rat brain

Abstract: Selective intracellular (IC) and extracellular (EC) brain water apparent diffusion coefficient (ADC) values were measured in normal and ischemic rat brain. Selective T1-relaxation enhancement of the EC water, using intracerebroventricular (ICV) infusion of an NMR contrast reagent (CR), was used to separate the IC and EC signal contributions. In the CR-infused, normal brain (n = 4), T1 = 235 ± 10 ms and T2 = 46 ± 2 ms for IC water (85%) and T1 = 48 ± 8 ms and T2 = 6 ± 2 ms for EC water (15%). Volume-localized ADCz (z-gradient axis) values were 0.90 ± 0.02 (EC+IC), 0.81 ± 0.05 (IC), 0.51 ± 0.02 (EC+IC), and 0.53 ± 0.07 (IC), for normal, CR-infused, ischemic, and ischemic/CR-infused groups, respectively (ADC values are ×10-3 mm2/s; n = 5 for each group). Imaging ADCz values were 0.81 ± 0.03 (EC+IC), 0.75 ± 0.05 (IC), 0.51 ± 0.04 (EC+IC), and 0.52 ± 0.05 (IC), respectively, for the same groups. Imaging ADCav (average diffusivity) values for the same groups were 0.70 ± 0.05 (EC+IC), 0.69 ± 0.06 (IC), 0.45 ± 0.06 (EC+IC), and 0.44 ± 0.06 (IC), respectively. These results suggest that the IC water ADC determines the overall water ADC value in normal and ischemic rat brain. Magn Reson Med 48:826–837, 2002. © 2002 Wiley-Liss, Inc.

Mass transfer and chemical reactions in bubble swarms with dynamic interfaces

Abstract: Detailed, high-resolution numerical simulations have been performed on the buoyancy-driven motion of deformable, chemically reacting bubbles for different operating conditions, that is, Weber, Morton, and Schmidt numbers. In our simulations different bubble shapes and types of bubble wakes were observed. The wake types range from a closed wake without recirculation, to a closed wake with recirculation, to an unsteady wake, leading to vortex-shedding wakes. Two different bubble-rise trajectories were observed for different conditions: straight and zigzag shaped. The mass-transfer rates and the yields and selectivities of liquid-phase chemical reactions were determined for each case. A detailed analysis of the results was carried out, relating the differences in chemical reaction efficiencies to the dynamics of each flow. Furthermore, to obtain a better understanding of the dynamics of the flows inside bubble swarms and their impact on chemical reactions, numerical simulations were performed of multiple bubbles rising in a swarm. Different bubble counts, geometric configurations, and size distributions were considered. Mass-transfer rates and chemical reaction selectivities were determined and a comparison is presented between the results for bubble swarms and single bubbles. It was shown that for mixing-sensitive reaction networks, the hydrodynamics of the bubble swarm may significantly impact the reaction selectivity. Furthermore, it was demonstrated that bubble swarm dynamics differ from the dynamics of single bubbles. © 2005 American Institute of Chemical Engineers AIChE J, 2005

Predicting human reaching motion in collaborative tasks using Inverse Optimal Control and iterative re-planning

Abstract: To enable safe and efficient human-robot collaboration in shared workspaces, it is important for the robot to predict how a human will move when performing a task. While predicting human motion for tasks not known a priori is very challenging, we argue that single-arm reaching motions for known tasks in collaborative settings (which are especially relevant for manufacturing) are indeed predictable. Two hypotheses underlie our approach for predicting such motions: First, that the trajectory the human performs is optimal with respect to an unknown cost function, and second, that human adaptation to their partner's motion can be captured well through iterative replanning with the above cost function. The key to our approach is thus to learn a cost function which “explains” the motion of the human. To do this, we gather example trajectories from two participants performing a collaborative assembly task using motion capture. We then use Inverse Optimal Control to learn a cost function from these trajectories. Finally, we predict a human's motion for a given task by iteratively replanning a trajectory for a 23 DoF human kinematic model using the STOMP algorithm with the learned cost function in the presence of a moving collaborator. Our results suggest that our method outperforms baseline methods and generalizes well for tasks similar to those that were demonstrated.

Imprecise DEA via Standard Linear DEA Models with a Revisit to a Korean Mobile Telecommunication Company

Abstract: Data Envelopment Analysis (DEA) requires that the data for all inputs and outputs are known exactly. When some outputs and inputs are unknown decision variables, such as bounded and ordinal data, the DEA model becomes a nonlinear programming problem and is called imprecise DEA (IDEA). The nonlinear IDEA program can be converted into a linear program by an algorithm based upon scale transformations and variable alterations. Such an algorithm requires a set of special computational codes for each evaluation, because a different objective function and a different constraint with a set of new variables are present for each unit under evaluation. The current paper revisits a published Korean telecommunication analysis, and, by so doing, presents a new and simple approach to execute the IDEA through the standard linear DEA models. This greatly enhances the applicability of IDEA in applications, and the IDEA analysis is no longer limited to obtaining the efficiency scores. The key to the new approach lies in the finding that imprecise data can be easily converted into exact data. Based upon the exact data, models can be developed to determine all possible multiple optimal solutions in imprecise data, and to perform efficiency sensitivity analysis in IDEA.