Reservoir performance under uncertainty in hydrologic impacts of climate change

Relatively few studies have addressed water management and adaptation measures in the face of changing water balances due to climate change. The current work studies climate change impact on a multipurpose reservoir performance and derives adaptive policies for possible futurescenarios. The method developed in this work is illustrated with a case study of Hirakud reservoir on the Mahanadi river in Orissa, India,which is a multipurpose reservoir serving flood control, irrigation and power generation. Climate change effects on annual hydropower generation and four performance indices (reliability with respect to three reservoir functions, viz. hydropower, irrigation and flood control, resiliency, vulnerability and deficit ratio with respect to hydropower) are studied. Outputs from three general circulation models (GCMs) for three scenarios each are downscaled to monsoon streamflow in the Mahanadi river for two future time slices, 2045-65 and 2075-95. Increased irrigation demands, rule curves dictated by increased need for flood storage and downscaled projections of streamflow from the ensemble of GCMs and scenarios are used for projecting future hydrologic scenarios. It is seen that hydropower generation and reliability with respect to hydropower and irrigation are likely to show a decrease in future in most scenarios, whereas the deficit ratio and vulnerability are likely to increase as a result of climate change if the standard operating policy (SOP) using current rule curves for flood protection is employed. An optimal monthly operating policy is then derived using stochastic dynamic programming (SDP) as an adaptive policy for mitigating impacts of climate change on reservoir operation. The objective of this policy is to maximize reliabilities with respect to multiple reservoir functions of hydropower, irrigation and flood control. In variations to this adaptive policy, increasingly more weightage is given to the purpose of maximizing reliability with respect to hydropower for two extreme scenarios. It is seen that by marginally sacrificing reliability with respect to irrigation and flood control, hydropower reliability and generation can be increased for future scenarios. This suggests that reservoir rules for flood control may have to be revised in basins where climate change projects an increasing probability of droughts. However, it is also seen that power generation is unable to be restored to current levels, due in part to the large projected increases in irrigation demand. This suggests that future water balance deficits may limit the success of adaptive policy options. (C) 2010 Elsevier Ltd. All rights reserved.

Predicting price-tag for customized goods

We discuss a dynamic pricing model which will aid automobile manufacturer in choosing the right price for customer segment. Though there is oligopoly market structure, the customers get "locked" into a particular technology/company which virtually makes the situation akin to a monopoly. There are associated network externalities and positive feedback. The key idea in monopoly pricing lies in extracting the customer surplus by exploiting the respective elasticities of demand. We present a Walrasian general equilibrium approach to determine the segment price. We compare the prices obtained from optimization model with that from Walrasian dynamics. The results are encouraging and can serve as a critical factor in Customer Relationship Management (CRM) and thereby effectively manage the lock-in.

Enzymatic Degradation of Poly(soybean oil-g-methyl methacrylate)

This study discusses grafting of methyl methacrylate units from thepolymeric soybean oil peroxide to produce poly(soybean oil-graft-methyl methacrylate) (PSO-g-PMMA). The degradation of this copolymer in solution was evaluated in the presence of different lipases, viz Candida rugosa (CR), Lipolase 100T (LP), Novozym 435 (N435) and Porcine pancreas (PP), at different temperatures The copolymer degraded by specific chain end scission and the mass fraction of the specific product evolved was determined The degradation was modeled using continuous distribution kinetics to determine the rate coefficients ofmenzymatic chain end scission and deactivation of the enzyme The enzymes, CR. LP and N435 exhibited maximum activity for the degradation of PSO-g-PMMA at 60 degrees C, while PP was most active at 50 degrees C. The thermal degradability of the copolymer, assessed by thermo-gravimetry, indicated that the activation energy of degradation of the copolymer was 154 kJ mol(-1), which was lesser than that of the PMMA homopolymer.

Tribology of steel/steel interaction in oil-in-water mulsion; a rationale for lubricity

Oil droplets are dispersed in water by an anionic urfactant to form an emulsion. The lubricity of this emulsion in steel/steel interaction is explored in a ball on flat nanotribometer. The droplet size and charge are measured using dynamic light scattering, while the substrate charge density is estimated using the pH titration method. These data are combined to calculate the DLVO forces for the droplets generated for a range of surfactant concentration and two oil to water volume ratios. The droplets have a clear bi-modal size distribution. The study shows that the smaller droplets which experience weak repulsion are situated (at the highest DLVO barrier) much closer to the substrate than thebigger droplets, which experience the same DLVO force, are. We suggest that the smaller droplets thus play a more important role in lubricity than what the bigger droplets do. The largest volume of such small droplets occurs in the 0.5 mM-1 mM range of surfactant concentration and 1% oil to water volume ratio, where the coefficient of friction is also observed to be the least. (C) 2010 Elsevier Inc. All rights reserved.

Studies in the Sandalwood Oil Series. III. Chain Effect on Terpene Transformations

The carboxyl chain of some molecules has been found to be responsible for causing rearrangements and controlling their course. This chain effect, which operates during reactions involving carbonium ions, is illustrated with examples from Sandalwood oil chemistry.

Studies in the sandalwood-oil series. I. The structure, synthesis, and configuration of the lactone of tricycloekasantalic acid

The structure, synthesis, and configuration of the lactone of tricycloekasantalic acid have been described. It has been shown that in the formation of this lactone (XII) from the acids (I) or (II) a rearrangement is involved.

Effect of matrix cracking and material uncertainty on composite plates

A laminated composite plate model based on first order shear deformation theory is implemented using the finite element method.Matrix cracks are introduced into the finite element model by considering changes in the A, B and D matrices of composites. The effects of different boundary conditions, laminate types and ply angles on the behavior of composite plates with matrix cracks are studied.Finally, the effect of material property uncertainty, which is important for composite material on the composite plate, is investigated using Monte Carlo simulations. Probabilistic estimates of damage detection reliability in composite plates are made for static and dynamic measurements. It is found that the effect of uncertainty must be considered for accurate damage detection in composite structures. The estimates of variance obtained for observable system properties due to uncertainty can be used for developing more robust damage detection algorithms. (C) 2010 Elsevier Ltd. All rights reserved.

Contribution of different physical forces to the disjoining pressure of a thin water film being pressed by an oil droplet

With an objective to understand the nature of forces which contribute to the disjoining pressure of a thin water film on a steel substrate being pressed by an oil droplet, two independent sets of experiments were done. (i) A spherical silica probe approaches the three substrates; mica, PTFE and steel, in a 10 mM electrolyte solution at two different pHs (3 and 10). (ii) The silica probe with and without a smeared oil film approaches the same three substrates in water (pH = 6). The surface potential of the oil film/water was measured using a dynamic light scattering experiment. Assuming the capacity of a substrate for ion exchange the total interaction force for each experiment was estimated to include the Derjaguin-Landau-Verwey-Overbeek (DLVO) force, hydration repulsion, hydrophobic attraction and oil-capillary attraction. The best fit of these estimates to the force-displacement characteristics obtained from the two sets of experiment gives the appropriate surface potentials of the substrates. The procedure allows an assessment of the relevance of a specific physical interaction to an experimental configuration. Two of the principal observations of this work are: (i) The presence of a surface at constant charge, as in the presence of an oil film on the probe, significantly enhances the counterion density over what is achieved when both the surfaces allow ion exchange. This raises the corresponding repulsion barrier greatly. (ii) When the substrate surface is wettable by oil, oil-capillary attraction contributes substantially to the total interaction. If it is not wettable the oil film is deformed and squeezed out. (C) 2010 Elsevier Inc. All rights reserved.

Guessing under source uncertainty with side information

We study the problem of guessing the realization of a finite alphabet source, when some side information is provided, in a setting where the only knowledge the guesser has about the source and the correlated side information is that the joint source is one among a family. We define a notion of redundancy, identify a quantity that measures this redundancy, and study its properties. We then identify good guessing strategies that minimize the supremum redundancy (over the family). The minimum value measures the richness of the uncertainty class.

Constraining uncertainty in regional hydrologic impacts of climate change: Nonstationarity in downscaling

Regional impacts of climate change remain subject to large uncertainties accumulating from various sources, including those due to choice of general circulation models (GCMs), scenarios, and downscaling methods. Objective constraints to reduce the uncertainty in regional predictions have proven elusive. In most studies to date the nature of the downscaling relationship (DSR) used for such regional predictions has been assumed to remain unchanged in a future climate. However,studies have shown that climate change may manifest in terms of changes in frequencies of occurrence of the leading modes of variability, and hence, stationarity of DSRs is not really a valid assumption in regional climate impact assessment. This work presents an uncertainty modeling framework where, in addition to GCM and scenario uncertainty, uncertainty in the nature of the DSR is explored by linking downscaling with changes in frequencies of such modes of natural variability. Future projections of the regional hydrologic variable obtained by training a conditional random field (CRF) model on each natural cluster are combined using the weighted Dempster-Shafer (D-S) theory of evidence combination. Each projection is weighted with the future projected frequency of occurrence of that cluster (''cluster linking'') and scaled by the GCM performance with respect to the associated cluster for the present period (''frequency scaling''). The D-S theory was chosen for its ability to express beliefs in some hypotheses, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The methodology is tested for predicting monsoon streamflow of the Mahanadi River at Hirakud Reservoir in Orissa, India. The results show an increasing probability of extreme, severe, and moderate droughts due to limate change. Significantly improved agreement between GCM predictions owing to cluster linking and frequency scaling is seen, suggesting that by linking regional impacts to natural regime frequencies, uncertainty in regional predictions can be realistically quantified. Additionally, by using a measure of GCM performance in simulating natural regimes, this uncertainty can be effectively constrained.

Learning dynamic prices in multiseller electronic retail markets with price sensitive customers, stochastic demands, and inventory replenishments

In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.

A method for Estimating the Degree of Uncertainty With Respect to Life Cycle Assessment During Design

Life cycle assessment (LCA) is used to estimate a product's environmental impact. Using LCA during the earlier stages of design may produce erroneous results since information available on the product's lifecycle is typically incomplete at these stages. The resulting uncertainty must be accounted for in the decision-making process. This paper proposes a method for estimating the environmental impact of a product's life cycle and the associated degree of uncertainty of that impact using information generated during the design process. Total impact is estimated based on aggregation of individual product life cycle processes impacts. Uncertainty estimation is based on assessing the mismatch between the information required and the information available about the product life cycle in each uncertainty category, as well as their integration. The method is evaluated using pre-defined scenarios with varying uncertainty. DOI: 10.1115/1.4002163]