990 resultados para Task constraints
Resumo:
Topology optimization methods have been shown to have extensive application in the design of microsystems. However, their utility in practical situations is restricted to predominantly planar configurations due to the limitations of most microfabrication techniques in realizing structures with arbitrary topologies in the direction perpendicular to the substrate. This study addresses the problem of synthesizing optimal topologies in the out-of-plane direction while obeying the constraints imposed by surface micromachining. A new formulation that achieves this by defining a design space that implicitly obeys the manufacturing constraints with a continuous design parameterization is presented in this paper. This is in contrast to including manufacturing cost in the objective function or constraints. The resulting solutions of the new formulation obtained with gradient-based optimization directly provide the photolithographic mask layouts. Two examples that illustrate the approach for the case of stiff structures are included.
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A multiple UAV search and attack mission in a battlefield involves allocating UAVs to different target tasks efficiently. This task allocation becomes difficult when there is no communication among the UAVs and the UAVs sensors have limited range to detect the targets and neighbouring UAVs, and assess target status. In this paper, we propose a team theoretic approach to efficiently allocate UAVs to the targets with the constraint that UAVs do not communicate among themselves and have limited sensor range. We study the performance of team theoretic approach for task allocation on a battle field scenario. The performance obtained through team theory is compared with two other methods, namely, limited sensor range but with communication among all the UAVs, and greedy strategy with limited sensor range and no communication. It is found that the team theoretic strategy performs the best even though it assumes limited sensor range and no communication.
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Garnet-kyanite-staurolite gneiss in the Pangong complex, Ladakh Himalaya, contains porphyroblastic euhedral garnets, blades of kyanite and resorbed staurolite surrounded by a fine-grained muscovite-biotite matrix associated with a leucogranite layer. Sillimanite is absent. The gneiss contains two generations of garnet in cores and rims that represent two stages of metamorphism. Garnet cores are extremely rich in Mn (X(Sps) = 0.35-038) and poor in Fe (X(Alm) = 0.40-0.45), whereas rims are relatively Mn-poor (X(Sps) =0.07-0.08), and rich in Fe (X(Alm), = 0.75-0.77). We suggest that garnet cores formed during prograde metamorphism in a subduction zone followed by abrupt exhumation, during early collision of the Ladakh arc and Karakoram block. The subsequent India-Asia continental collision subducted the metamorphic rocks to a mid-crustal level, where the garnet rims overgrew the Mn-rich cores at ca. 680 degrees C and ca. 8.5 kbar. PT calculations were estimated from phase diagrams calculated using a calculated bulk chemical composition in the Mn-NCKFMASHT system for the garnet-kyanite-staurolite-bearing assemblage. Muscovites from the metamorphic rocks and associated leucogranites have consistent K-Ar ages (ca. 10 Ma), closely related to activation of the Karakoram fault in the Pangong metamorphic complex. These ages indicate the contemporaneity of the exhumation of the metamorphic rocks and the cooling of the leucogranites. (C) 2011 Elsevier B.V. All rights reserved.
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A series of deoxycholic and cholic acid-derived oligomers were synthesized and their ability to extract hydrophilic dye molecules of different structure, size, and functional groups into nonpolar media was studied. The structure of the dye and dendritic effect in the extraction process was examined using absorption spectroscopy and dynamic light scattering (DLS). The efficiency of structurally preorganized oligomers in the aggregation process was evaluated by 1-anilinonaphthalene-8-sulfonic acid (ANS) fluorescence studies. The possible formation of globular structures for higher-generation molecules was investigated by molecular modeling studies and the results were correlated with the anomaly observed in the extraction process with this molecule. The ability of these molecules for selective extraction of specific dyes from blended colors is also reported.
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A sufficiently long lived warm dark matter could be a source of X-rays observed by satellite based X-ray telescopes. We consider axinos and gravitinos with masses between 1 keV and 100 keV in supersymmetric models with sin all R-parity violation. We show that axino dark matter receives significant constraints from X-ray observations of Chandra and SPI, especially for the lower end of the allowed range of the axino decay constant f(a), while the gravitino dark matter remains unconstrained.
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In this paper, sliding-mode-control-based guidance laws to intercept stationary, constant-velocity, and maneuvering targets at a desired impact angle are proposed. The desired impact angle, which is defined in terms of a desired line-of-sight angle, is achieved in finite time by selecting the missile's lateral acceleration to enforce terminal sliding mode on a switching surface designed using nonlinear engagement dynamics. The conditions for capturability are also presented. In addition, by considering a three-degree-of-freedom linear-interceptor dynamic model and by following the procedure used to design a dynamic sliding-mode controller, the interceptor autopilot is designed as a simple static controller to track the lateral acceleration generated by the guidance law. Numerical simulation results are presented to validate the proposed guidance laws and the autopilot design for different initial engagement geometries and impact angles.
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We study the orbital modulation of X-rays from Cyg X-3, using data from Swift, INTEGRAL and RXTE. Using the wealth of data presently available and an improved averaging method, we obtain energy-dependent folded and averaged light curves with unprecedented accuracy. We find that above similar to 5?keV the modulation depth decreases with increasing energy, which is consistent with the modulation being caused by both boundfree absorption and Compton scattering in the stellar wind of the donor, with minima corresponding to the highest optical depth, which occurs around the superior conjunction. We find a decrease of the depth below similar to 3?keV, which appears to be due to re-emission of the absorbed continuum by the wind in soft X-ray lines. Based on the shape of the folded light curves, any X-ray contribution from the jet in Cyg X-3, which emits ?-rays detected at energies >0.1?GeV in the soft spectral states, is found to be minor up to similar to 100?keV. This implies the presence of a rather sharp low-energy break in the jet MeV-range spectrum. We also calculate phase-resolved RXTE X-ray spectra and show that the difference between the spectra corresponding to phases around superior and inferior conjunctions can indeed be accounted for by the combined effect of boundfree absorption in an ionized medium and Compton scattering.
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The K pi form factors are investigated at low energies by the method of unitarity bounds adapted so as to include information on the phase and modulus along the elastic region of the unitarity cut. Using as input the values of the form factors at t = 0, and at the Callan-Treiman point in the scalar case, stringent constraints are obtained on the slope and curvature parameters of the Taylor expansion at the origin.
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We address the problem of phase retrieval, which is frequently encountered in optical imaging. The measured quantity is the magnitude of the Fourier spectrum of a function (in optics, the function is also referred to as an object). The goal is to recover the object based on the magnitude measurements. In doing so, the standard assumptions are that the object is compactly supported and positive. In this paper, we consider objects that admit a sparse representation in some orthonormal basis. We develop a variant of the Fienup algorithm to incorporate the condition of sparsity and to successively estimate and refine the phase starting from the magnitude measurements. We show that the proposed iterative algorithm possesses Cauchy convergence properties. As far as the modality is concerned, we work with measurements obtained using a frequency-domain optical-coherence tomography experimental setup. The experimental results on real measured data show that the proposed technique exhibits good reconstruction performance even with fewer coefficients taken into account for reconstruction. It also suppresses the autocorrelation artifacts to a significant extent since it estimates the phase accurately.
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We consider the problem of optimal routing in a multi-stage network of queues with constraints on queue lengths. We develop three algorithms for probabilistic routing for this problem using only the total end-to-end delays. These algorithms use the smoothed functional (SF) approach to optimize the routing probabilities. In our model all the queues are assumed to have constraints on the average queue length. We also propose a novel quasi-Newton based SF algorithm. Policies like Join Shortest Queue or Least Work Left work only for unconstrained routing. Besides assuming knowledge of the queue length at all the queues. If the only information available is the expected end-to-end delay as with our case such policies cannot be used. We also give simulation results showing the performance of the SF algorithms for this problem.
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We consider precoding strategies at the secondary base station (SBS) in a cognitive radio network with interference constraints at the primary users (PUs). Precoding strategies at the SBS which satisfy interference constraints at the PUs in cognitive radio networks have not been adequately addressed in the literature so far. In this paper, we consider two scenarios: i) when the primary base station (PBS) data is not available at SBS, and ii) when the PBS data is made available at the SBS. We derive the optimum MMSE and Tomlinson-Harashima precoding (THP) matrix Alters at the SBS which satisfy the interference constraints at the PUs for the former case. For the latter case, we propose a precoding scheme at the SBS which performs pre-cancellation of the PBS data, followed by THP on the pre-cancelled data. The optimum precoding matrix filters are computed through an iterative search. To illustrate the robustness of the proposed approach against imperfect CSI at the SBS, we then derive robust precoding filters under imperfect CSI for the latter case. Simulation results show that the proposed optimum precoders achieve good bit error performance at the secondary users while meeting the interference constraints at the PUs.
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The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.
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In animal populations, the constraints of energy and time can cause intraspecific variation in foraging behaviour. The proximate developmental mediators of such variation are often the mechanisms underlying perception and associative learning. Here, experience-dependent changes in foraging behaviour and their consequences were investigated in an urban population of free-ranging dogs, Canis familiaris by continually challenging them with the task of food extraction from specially crafted packets. Typically, males and pregnant/lactating (PL) females extracted food using the sophisticated `gap widening' technique, whereas non-pregnant/non-lactating (NPNL) females, the relatively underdeveloped `rip opening' technique. In contrast to most males and PL females (and a few NPNL females) that repeatedly used the gap widening technique and improved their performance in food extraction with experience, most NPNL females (and a few males and PL females) non-preferentially used the two extraction techniques and did not improve over successive trials. Furthermore, the ability of dogs to sophisticatedly extract food was positively related to their ability to improve their performance with experience. Collectively, these findings demonstrate that factors such as sex and physiological state can cause differences among individuals in the likelihood of learning new information and hence, in the rate of resource acquisition and monopolization.
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We consider a power optimization problem with average delay constraint on the downlink of a Green Base-station. A Green Base-station is powered by both renewable energy such as solar or wind energy as well as conventional sources like diesel generators or the power grid. We try to minimize the energy drawn from conventional energy sources and utilize the harvested energy to the maximum extent. Each user also has an average delay constraint for its data. The optimal action consists of scheduling the users and allocating the optimal transmission rate for the chosen user. In this paper, we formulate the problem as a Markov Decision Problem and show the existence of a stationary average-cost optimal policy. We also derive some structural results for the optimal policy.