Reservoir Operation for Hydropower Optimization: A Chance-Constrained Approach

This paper presents a chance-constrained linear programming formulation for reservoir operation of a multipurpose reservoir. The release policy is defined by a chance constraint that the probability of irrigation release in any period equalling or exceeding the irrigation demand is at least equal to a specified value P (called reliability level). The model determines the maximum annual hydropower produced while meeting the irrigation demand at a specified reliability level. The model considers variation in reservoir water level elevation and also the operating range within which the turbine operates. A linear approximation for nonlinear power production function is assumed and the solution obtained within a specified tolerance limit. The inflow into the reservoir is considered random. The chance constraint is converted into its deterministic equivalent using a linear decision rule and inflow probability distribution. The model application is demonstrated through a case study.

Chance constrained uncertain classification via robust optimization

This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out to be intractable. The key novelty is in employing Bernstein bounding schemes to relax the CCP as a convex second order cone program whose solution is guaranteed to satisfy the probabilistic constraint. Prior to this work, only the Chebyshev based relaxations were exploited in learning algorithms. Bernstein bounds employ richer partial information and hence can be far less conservative than Chebyshev bounds. Due to this efficient modeling of uncertainty, the resulting classifiers achieve higher classification margins and hence better generalization. Methodologies for classifying uncertain test data points and error measures for evaluating classifiers robust to uncertain data are discussed. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle data uncertainty and outperform state-of-the-art in many cases.

Video coding mode decision as a classification problem

In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

Robust formulations for clustering-based large-scale classification

Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.

Impact-Angle-Constrained Suboptimal Model Predictive Static Programming Guidance of Air-to-Ground Missiles

A nonlinear suboptimal guidance law is presented in this paper for successful interception of ground targets by air-launched missiles and guided munitions. The main feature of this guidance law is that it accurately satisfies terminal impact angle constraints in both azimuth as well as elevation simultaneously. In addition, it is capable of hitting the target with high accuracy as well as minimizing the lateral acceleration demand. The guidance law is synthesized using recently developed model predictive static programming (MPSP). Performance of the proposed MPSP guidance is demonstrated using three-dimensional (3-D) nonlinear engagement dynamics by considering stationary, moving, and maneuvering targets. Effectiveness of the proposed guidance has also been verified by considering first. order autopilot lag as well as assuming inaccurate information about target maneuvers. Multiple munitions engagement results are presented as well. Moreover, comparison studies with respect to an augmented proportional navigation guidance (which does not impose impact angle constraints) as well as an explicit linear optimal guidance (which imposes the same impact angle constraints in 3-D) lead to the conclusion that the proposed MPSP guidance is superior to both. A large number of randomized simulation studies show that it also has a larger capture region.

Generalized model predictive static programming and its application to 3D impact angle constrained guidance of air-to-surface missiles

A new `generalized model predictive static programming (G-MPSP)' technique is presented in this paper in the continuous time framework for rapidly solving a class of finite-horizon nonlinear optimal control problems with hard terminal constraints. A key feature of the technique is backward propagation of a small-dimensional weight matrix dynamics, using which the control history gets updated. This feature, as well as the fact that it leads to a static optimization problem, are the reasons for its high computational efficiency. It has been shown that under Euler integration, it is equivalent to the existing model predictive static programming technique, which operates on a discrete-time approximation of the problem. Performance of the proposed technique is demonstrated by solving a challenging three-dimensional impact angle constrained missile guidance problem. The problem demands that the missile must meet constraints on both azimuth and elevation angles in addition to achieving near zero miss distance, while minimizing the lateral acceleration demand throughout its flight path. Both stationary and maneuvering ground targets are considered in the simulation studies. Effectiveness of the proposed guidance has been verified by considering first order autopilot lag as well as various target maneuvers.

Biased PN based impact angle constrained guidance using a nonlinear engagement model

Impact angle constrained guidance laws are important in many applications such as guidance of torpedoes, anti-ballistic missiles and reentry vehicles. In this paper, we design a guidance law which is capable of achieving a wide range of impact angles. Biased proportional navigation guidance uses a bias term in addition to the basic PN command to satisfy additional constraints. Angle constrained BPNG (ACBPNG) uses small angle approximations to derive the bias term for impact angle requirement. We design a modified ACBPNG (MACBPNG) where the required bias term is derived in a closed form considering non-linear equations of motion. Simulations are carried out for a wide range of impact angle requirements. We also analyze capturability from different initial positions and also the launch angles possible at each initial position. The performance of the proposed law is compared with an existing law.

Generalized Model Predictive Static Programming and Angle-Constrained Guidance of Air-to-Ground Missiles

A new generalized model predictive static programming technique is presented for rapidly solving a class of finite-horizon nonlinear optimal control problems with hard terminal constraints. Two key features for its high computational efficiency include one-time backward integration of a small-dimensional weighting matrix dynamics, followed bya static optimization formulation that requires only a static Lagrange multiplier to update the control history. It turns out that under Euler integration and rectangular approximation of finite integrals it is equivalent to the existing model predictive static programming technique. In addition to the benchmark double integrator problem, usefulness of the proposed technique is demonstrated by solving a three-dimensional angle-constrained guidance problem for an air-to-ground missile, which demands that the missile must meet constraints on both azimuth and elevation angles at the impact point in addition to achieving near-zero miss distance, while minimizing the lateral acceleration demand throughout its flight path. Simulation studies include maneuvering ground targets along with a first-order autopilot lag. Comparison studies with classical augmented proportional navigation guidance and modern general explicit guidance lead to the conclusion that the proposed guidance is superior to both and has a larger capture region as well.

Left-Handed DNA in Synthetic and Topologically Constrained Form V-DNA

We have investigated structural transitions in Poly(dG-dC) and Poly(dG-Me5dC) in order to understand the exact role of cations in stabilizing left-handed helical structures in specific sequences andthe biological role, if any, of these structures. From a novel temperature dependent transition it has been shown that a minor fluctuation in Na+ concentration at ambient temperature can bring about Β to Ζ transition. Forthe first time, wehave observed a novel double transition in poly(dG-Me5dC) as the Na+ concentration is gradually increased. This suggests that a minor fluctuation in Na+ concentration in conjunction with methylation may transform small stretches of CG sequences from one conformational state to another. These stretches could probably serve as sites for regulation. Supercoiled formV DNA reconstituted from pBR322 and pßG plasmids have been studied as model systems, in order to understand the nature and role of left-handed helical conformation in natural sequences. A large portion of DNA in form V, obtained by reannealing the two complementary singlestranded circles is forced to adopt left-handed double helical structure due to topological constraints (Lk = 0). Binding studies with Z-DNA specific antibody and spectroscopic studies confirm the presence of left-handed Z-structure in the pßG and pßR322 form V DNA. Cobalt hexamine chloride, which induces Z-form in Poly(dG-dC) stabilizes the Z-conformation in form V DNA even in the non-alternating purine-pyrimidine sequences. A reverse effect is observed with ethidium bromide. Interestingly, both topoisomerase I and II (from wheat germ) act effectively on form V DNA to give rise to a species having an electrophoretic mobility on agarose gel similar to that of open circular (form II) DNA. Whether this molecule is formed as a result of the left-handed helical segments of form V DNA undergoing a transition to the right-handed B-form during the topoisomerase action remains to be solved.

Flow of metal in constrained plane-strain extrusion forging- Part II

With many innovations in process technology, forging is establishing itself as a precision manufacturing process: as forging is used to produce complex shapes in difficult materials, it requires dies of complex configuration of high strength and of wear-resistant materials. Extensive research and development work is being undertaken, internationally, to analyse the stresses in forging dies and the flow of material in forged components. Identification of the location, size and shape of dead-metal zones is required for component design. Further, knowledge of the strain distribution in the flowing metal indicates the degree to which the component is being work hardened. Such information is helpful in the selection of process parameters such as dimensional allowances and interface lubrication, as well as in the determination of post-forging operations such as heat treatment and machining. In the presently reported work the effect of aperture width and initial specimen height on the strain distribution in the plane-strain extrusion forging of machined lead billets is observed: the distortion of grids inscribed on the face of the specimen gives the strain distribution. The stress-equilibrium approach is used to optimise a model of flow in extrusion forging, which model is found to be effective in estimating the size of the dead-metal zone. The work carried out so far indicates that the methodology of using the stress-equilibrium approach to develop models of flow in closed-die forging can be a useful tool in component, process and die design.

Proline ring conformations corresponding to a bistable jump model from 13C spin-lattice relaxation times

A formalism for extracting the conformations of a proline ring based on the bistable jump model of R. E. London [(1978) J. Am. Chem. Soc. 100, 2678-2685] from 13C spin-lattice relaxation times (T1) is given. The method is such that the relaxation data are only partially used to generate the conformations; these conformations are constrained to satisfy the rest of the relaxation data and to yield acceptable ring geometry. An alternate equation for T1 of 13C nuclei to that of London is given. The formalism is illustrated through an example.

An incipient 310 helix in Piv-Pro-Pro-Ala-NHMe as a model for peptide folding

The molecular mechanism of helix nucleation in peptides and proteins is not yet understood and the question of whether sharp turns in the polypeptide backbone serve as nuclei for protein folding has evoked controversy1,2. A recent study of the conformation of a tetrapeptide containing the stereochemically constrained residue alpha-aminoisobutyric acid, both in solution and the solid state, yielded a structure consisting of two consecutive beta-turns, leading to an incipient 310 helical conformation3,4. This led us to speculate that specific tri- and tetra-peptide sequences may indeed provide a helical twist to the amino-terminal segment of helical regions in proteins and provide a nucleation site for further propagation. The transformation from a 310 helical structure to an alpha-helix should be facile and requires only small changes in the phi and psi conformational angles and a rearrangement of the hydrogen bonding pattern5. If such a mechanism is involved then it should be possible to isolate an incipient 310 helical conformation in a tripeptide amide or tetrapeptide sequence, based purely on the driving force derived from short-range interactions. We have synthesised and studied the model peptide pivaloyl-Pro-Pro-Ala-NHMe (compound I) and provide here spectroscopic evidence for a 310 helical conformation in compound I.

A finite element analysis of quasistatic crack growth in a pressure sensitive constrained ductile layer

Polymeric adhesive layers are employed for bonding two components in a wide variety of technological applications, It has been observed that, unlike in metals, the yield behavior of polymers is affected by the state of hydrostatic stress. In this work, the effect of pressure sensitivity of yielding and layer thickness on quasistatic interfacial crack growth in a ductile adhesive layer is investigated. To this end, finite deformation, finite element analyses of a cracked sandwiched layer are carried out under plane strain, small-scale yielding conditions for a wide range of mode mixities. The Drucker-Prager constitutive equations are employed to represent the behavior of the layer. Crack propagation is simulated through a cohesive zone model, in which the interface is assumed to follow a prescribed traction-separation law. The results show that for a given mode mixity, the steady state Fracture toughness [K](ss) is enhanced as the degree of pressure sensitivity increases. Further, for a given level of pressure sensitivity, [K](ss) increases steeply as mode Il loading is approached. (C) 2000 Elsevier Science Ltd. All rights reserved.

Stereochemically constrained peptides. Theoretical and experimental studies on the conformations of peptides containing 1-aminocyclohexane carboxylic acid

Conformational energy calculations on the model system N-acetyl- 1 -aminocyclohexanecarboxylic acid N'methylamide (Ac-Acc6-NHMe), using an average geometry derived from 13 crystallographic observations, establish that the Acc6 residue is constrained to adopt conformations in the helical regions of In contrast, the a,a-dialkylated residue with linear hydrocarbon side chains, a,a-di-n-propylglycine favors fully extended backbone structures (6 1= $ = 180'). The crystal structures of two model peptides, Boc-(Acc6),-OMe (type 111 @-turn at -Acc6(1)-Acc6(2)-) and Boc-Pro-Acc6-Ala-OMe (type I1 P-turn at -Pro-Acc6-), establish that Acc6 residues can occupy either position of type 111 P-turns and the i + 2 position of type I1 @-turns. The stereochemical rigidity of these peptides is demonstrated in solution by NMR studies, which establish the presence of one intramolecular hydrogen bond in each peptide in CDCI, and (CDJ2S0. Nuclear Overhauser effects permit characterization of the @-turn conformations in solution and establish their similarity to the solid-state structures. The implications for the use of Acc6 residues in conformational design are considered.