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The town of Yucca Valley located in the southwest part of the Mojave Desert in southern California relies on groundwater pumping from the Warren groundwater basin as its sole source of water supply. This significant dependency has resulted in a large imbalance between groundwater pumpage and natural recharge, causing groundwater levels in the basin to decline more than 90 m from the late 1940s to 1994. Consequently, an artificial recharge program proposed by the Hi-Desert Water District, which provides water service to the town of Yucca Valley, was implemented for the purpose of recovering the groundwater levels; however, the rise in groundwater levels has caused nitrate ( NO3 ) concentration to increase simultaneously. The purpose of this study is to develop an optimal pump and recharge strategy for a planned conjunctive-use project to remove the high-nitrate concentration while maintaining groundwater levels at desired elevations at specified locations as well as meeting water demand. An optimization/ma...

This paper develops an iterative procedure for capacity expansion studies for water distribution systems. We propose a methodology to analyze an existing water distribution system and identify the potential bottlenecks in the system. Based on the results, capacity expansion alternatives are proposed and evaluated for improving the efficiency of water supply. The methodology includes a network flow based optimization model, four evaluation indices, and a series of evaluation steps. We first use a directed graph to configure the water distribution system into a network. The network flow based model optimizes the water distribution in the system so that different expansion alternatives can be evaluated on a comparable basis. This model lends itself to linear programming (LP) and can be easily solved by a standard LP code. The results from the evaluation tool help to identify the bottlenecks in the water distribution system and provide capacity expansion alternatives. A useful complementary tool for decision making is composed of a series of evaluation steps with the bottleneck findings, capacity expansion alternatives, and the evaluation of results. We apply the proposed methodology to the Tou-Qian River Basin, located in the northern region of Taiwan, to demonstrate its applicability in optimization and capacity expansion studies.

This work presents a novel approach for solving groundwater management problems with reduced computational effort. We replace a groundwater flow model governed by a partial differential equation with a simple model governed by an ordinary differential equation. Model reduction is achieved with empirical orthogonal functions, i.e., principal components. Replacement of the full-scale model by a reduced model allows implementation of the embedding approach for optimal groundwater management. Comparing the results obtained with the full-scale simulation model, preliminary analyses show that the reduced model is able to reproduce head variations in the flow domain with good accuracy and, to a certain degree, the sensitivities of head with respect to pumping. A key advantage of the reduced model is that it is simple and easy to solve, and in many instances captures the dominating characteristics of the original model. In view of the many sources of uncertainty influencing groundwater simulation, the accuracy provided by a reduced model may be sufficient for planning purposes. As with other examples of model reduction presented in recent research efforts, the methodology shows promise in presenting general trends, but does not eliminate the need for the original model when more detailed analyses are needed.

A calibrated simulation model is linked with two optimization models to investigate alternatives for enhancing seawater intrusion barrier operations for the Alamitos Barrier Project in Los Angeles. Two types of management problems are analyzed, the optimal scheduling problem (OSP) and the optimal well location problem. The OSP objective is to minimize the total injected water subject to constraints on the state variables: Hydraulic head and chloride concentration at target locations. Two OSP formulations are considered, a pure hydraulic gradient formulation, and a combined hydraulic and transport formulation. When considering all 43 injection wells over a five-year planning horizon, the simulation-optimization model could not significantly improve upon the assigned initial injection rates. However, if a subset of the injection wells is exclusively considered, more favorable injection policies are obtained where less water is injected, compared with either the mean or annual mean derived from the historica...

Reservoir operations play an important role in water resources planning and management. During periods of drought, when inflows to the reservoir are low, it may not be possible to satisfy the target delivery (planned demand), and shortage occurs. Reservoir hedging rules, which include a set of rule curves and rationing factors, are used to guide the operation under such a situation. In particular, hedging rules are employed to balance the current shortage in supply with future storage to avoid severe water shortages in the future. In general, hedging rules are determined at the planning stage, or at the early stage of a reservoir’s operating life. However, after years of operation, the reservoir system, as well as the demand characteristics, may change. Hence, it becomes necessary to reevaluate and update the existing hedging rules to incorporate changes that have taken place. The purpose of this paper is to devise new hedging rules for an existing multireservoir system. An original mixed-integer nonlinea...

A nine-layered confined-unconfined flow and transport model is developed for the Alamitos saltwater intrusion barrier in Southern California. The conceptual model is based on the geological structure of the coastal aquifer system. The key parameters in the flow and transport models are calibrated using a two-phase procedure which matches the types of data available for calibration. Because of the abundance of point measurements of hydraulic conductivity, the heterogeneous and random hydraulic conductivity field for each of the five aquifers is estimated by the geostatiscal method of natural-neighbor-kriging in Phase 1. In Phase 2, the longitudinal and transverse dispersivities in the transport model are estimated by a traditional inverse procedure that minimizes the least-squares error for concentration (LSE-CON). The minimum LSE-CON is achieved near 15.2 and 1.52 m for the longitudinal and transverse dispersivities, respectively. Additional simulations with increasing transport parameter complexity did not yield significant improvements in LSE-CON. Also, tracking least-squares error for head while parametrically varying the transport parameters revealed there is a negligible interaction between predicted head and transport parameters.

The paper develops an efficient macro-evolutionary multiobjective genetic algorithm (MMGA) for optimizing the rule curves of a multi-purpose reservoir system in Taiwan. Macro-evolution is a new kind of high-level species evolution that can avoid premature convergence that may arise during the selection process of conventional GAs. MMGA enriches the capabilities of GA to handle multiobjective problems by diversifying the solution set. Simulation results using a benchmark test problem indicate that the proposed MMGA yields better-spread solutions and converges closer to the true Pareto frontier than the nondominated sorting genetic algorithm-II (NSGA-II). When applied to a real case study, MMGA is able to generate uniformly spread solutions for a two-objective problem involving water supply and hydropower generation. Results of this work indicate that the proposed MMGA is highly competitive and provides a viable alternative to solve multiobjective optimization problems for water resources planning and management.

This paper evaluates the impacts of multiple water uses on the operation of a system of existing reservoirs that originally were designed for hydropower generation. The research reported in this paper utilizes a nonlinear optimization model, developed to optimize hydropower production for a system of interconnected reservoirs. This model was modified to include water withdrawals for consumptive uses. The formulated multiobjective optimization problem is solved by employing the weighting method. The formulation considers water allocation policy for consumptive uses and individual hydropower plants. By parametrically varying the weighting coefficients, the tradeoff relationship (Pareto front) between hydropower generation and water demand for consumptive uses was traced out. The modified model is applied to the Sao Francisco River Basin in Brazil, where there are several hydropower plants in operation with a total installed capacity of 10.7 GW. The river basin is an important agricultural land that ...

We measure the time dependence of the ratio of decay rates for D-0 -> K+ pi(-) to the Cabibbo- favored decay D-0 -> K- pi(+). The charge conjugate decays are included. A signal of 3: 3 x 10(4) D*(+) -> pi D-+(0), D-0 -> K+ pi(-) decays is obtained with D-0 proper decay times between 0.75 and 10 mean D-0 lifetimes. The data were recorded with the CDF II detector at the Fermilab Tevatron and correspond to an integrated luminosity of 9: 6 fb(-1) for p (p) over bar collisions at root s = 1: 96 TeV. Assuming CP conservation, we search for D-0-(D) over bar (0) mixing and measure the mixing parameters to be R-D = (3: 51 +/- 0: 35) x 10(-3), y' = (4: 3 +/- 4: 3) x 10(-3), and x'(2) = (0: 08 +/- 0: 18) x 10(-3). We report Bayesian probability intervals in the x'(2)- y' plane and find that the significance of excluding the no- mixing hypothesis is equivalent to 6.1 Gaussian standard deviations, providing the second observation of D-0-(D) over bar (0) mixing from a single experiment.

We report on a search for B0s→μ+μ− and B0→μ+μ− decays using proton-antiproton collision data at s√=1.96 TeV corresponding to 10 fb−1 of integrated luminosity collected by the CDF II detector at the Fermilab Tevatron collider. The observed number of B0 candidates is consistent with background-only expectations and yields an upper limit on the branching fraction of B(B0→μ+μ−)

This paper reviews the role of probability density function (PDF) choice on: (1) the statistical characterization of hydraulic conductivity; and (2) the estimation of the local-scale effective hydraulic conductivity. The most widely used skewed PDFs, namely, the lognormal, gamma, and log-gamma PDFs are included in this study. It is shown that the gamma and log-gamma PDFs possess statistical features that render them competitive, if not advantageous, to the more commonly used and better-known lognormal PDF in: (1) the statistical description of hydraulic conductivity; and (2) the estimation of the effective hydraulic conductivity in local-scale groundwater flow. The effective hydraulic conductivity is the parameter relating the average specific discharge to the average hydraulic gradient. Several examples dealing with the statistical analysis of hydraulic conductivity and the estimation of the effective hydraulic conductivity are presented, including a sample of 201 slug-test measurements of hydraulic cond...

This paper develops a multicommodity flow model to optimize water distribution and water quality in a regional water supply system. Waters from different sources with different qualities are considered as distinct commodities that concurrently share a single water distribution system. The model can accommodate two-way flow pipes, represented by undirected arcs, and the perfect mixing condition. Additionally, blending requirements are specified at certain control nodes within the system to ensure that downstream users receive the desired water quality. The optimization model is highly nonlinear and solved by a hybrid genetic algorithm (GA). The GA is first used to globally search for the directions of all undirected arcs. Then a generalized reduced gradient (GRG) algorithm embedded in the GA is used to optimize the objective function for fitness evaluation. The proposed methodology was first tested and verified on a hypothetical system and then applied to the regional water distribution system of the Metro...

A natural neighbor interpolation (NN) method based on Voronoi tessellation and Delaunay triangulation is developed for both parameter heterogeneity characterization and parameter structure identification in groundwater modeling. Honoring information from the natural neighboring basis points, NN generates a continuously distributed field. With NN, parameter structure identification seeks to identify the optimal parameter distribution in terms of the number, values, and locations of basis points. At each level of parameter structure complexity, the estimated distributed parameter is obtained by minimizing a regularized fitting residual. This is done sequentially, first by a genetic algorithm (GA) and then by a gradient-based algorithm (BFGS). In this study, sensitivity equations of state variables to both values and locations of basis points are developed for optimization as well as for parameter uncertainty analysis. The results obtained from numerical experiments show that, for a given set of head observations and point transmissivity measurements, the proposed inverse methodology successfully captures the variation of the true transmissivity field. The parameter structure complexity as represented by the parameter dimension is determined by considering the trade-off between the fitting residual and the parameter uncertainty error. An optimal parameter dimension is selected when the head fitting residual is close to the observation error and the uncertainty associated with identified transmissivity structure is acceptable.

We report an analysis of the Λb0→Λc+π-π+π- decay in a data sample collected by the CDF II detector at the Fermilab Tevatron corresponding to 2.4 fb-1 of integrated luminosity. We reconstruct the currently largest samples of the decay modes Λb0→Λc(2595)+π- (with Λc(2595)+→Λc+π+π-), b0→Λc(2625)+π- (with Λc(2625)+→Λc+π+π-), Λb0→Σc(2455)++π-π- (with Σc(2455)++→Λc+π+), and Λb0→Σc (2455)0π+π- (with Σc(2455)0→Λc+π-) and measure the branching fractions relative to the Λb0→Λc+π- branching fraction. We measure the ratio B(Λb0→Λc +π-π+π-)/ B(Λb0→Λc+π-)=3.04±0.33(stat)-0.55+0.70(syst) which is used to derive B(Λb0→Λc+π-π+π-)=(26.8-11.2+11.9)×10-3.

Increasing demands for water by competing users in semiarid regions pose new challenges for water resources managers. Decision makers must understand the interactions between surface water, groundwater, and the environmental system. Additionally, the decisions made with regard to water transfer and allocation must take into consideration the diverse objectives that include water supply, cost efficiency, and ecosystem protection. The work presented herein demonstrates the use of groundwater simulation and optimization to construct a decision support system (DSS) for solving a groundwater management problem associated with the Upper San Pedro River Basin, located in southeastern Arizona. The case is treated as a multiobjective optimization problem in which environmental objectives are explicitly considered by minimizing the magnitude and extent of drawdown within a prespecified region. The approach adopted uses the constraint method to derive the tradeoffs among three competing objectives. Once the proposed algorithm identifies a set of efficient solutions (alternatives), concepts borrowed from fuzzy set theory are applied to rank the alternatives and to assist decision makers in selecting a suitable policy among them, each of which is optimum with regard to its goal and the corresponding consequences.

This article reports a measurement of the production cross section of prompt isolated photon pairs in proton-antiproton collisions at √s=1.96TeV using the CDF II detector at the Fermilab Tevatron collider. The data correspond to an integrated luminosity of 5.36fb -1. The cross section is presented as a function of kinematic variables sensitive to the reaction mechanisms. The results are compared with three perturbative QCD calculations: (1) a leading-order parton shower Monte Carlo, (2) a fixed next-to-leading-order calculation and (3) a next-to-leading-order/next-to-next-to-leading-log resummed calculation. The comparisons show that, within their known limitations, all calculations predict the main features of the data, but no calculation adequately describes all aspects of the data. © 2011 American Physical Society.

A practical monthly optimization model, called SISOPT, is developed for the management and operations of the Brazilian hydropower system. The system, one of the largest in the world, consists of 75 hydropower plants with an installed capacity of 69,375 MW, producing 92% of the nation's electrical power. The system size and nonlinearity pose a real challenge to the modelers. The basic model is formulated in nonlinear programming ~NLP!. The NLP model is the most general formulation and provides a foundation for analysis by other methods. The formulated NLP model was first linearized by two different linearization techniques and solved by linear programming ~LP!. A comparative analysis was made of the results obtained from the linearized and the NLP models. The results show that the simplest linearized model ~referred to as the LP model! without iteration is suitable for planning purposes. For example, the LP model could be used in system capacity expansion studies or to explore various design parameters in connection with feasibility studies, where details in storage variation are not as important as the power production. With a good initial policy provided by the LP model, the successive linear programming ~SLP! model produced excellent results with fast convergence. The NLP model, the most complex and accurate model in the suite, is particularly suited for setting up guidelines for real-time operations using inflow forecast with frequent updating. The performance of the NLP model was checked against the historical operational records, and the comparison yields indica- tions of superior performance.

This research develops a mixed integer linear programming (MILP) model that considers simultaneously both the traditional reservoir rule curves and the hedging rules to manage and operate a multipurpose, multireservoir system. During normal periods of operation, when inflows are plentiful, this optimization model efficiently distributes the available stored water from different reservoirs to meet the planned demands imposed by competing users. However, during periods of drought, or when anticipating a drought, the planned demands cannot be fully met, and a water shortage occurs. By considering the hedging rules along with the rule curves, guidelines are provided for reservoir releases. To minimize the impact of drought, the hedging rules effectively reduce the ongoing water supply to balance with the target storage requirement. The MILP model is applied to a multireservoir system in the southern region of Taiwan, where the results obtained demonstrate the applicability and utility of the model.

This paper presents a systematic approach for solving the management problem of a contaminated groundwater supply system. The proposed methodology begins with the selection of a supply water quality criterion based on a stochastic health risk assessment and concludes with the establishment of a trade-off relationship between the increased management cost and the desired level of protection. In the uncertainty analysis, Guassian quadrature numerical integration is used as an alternative to nested Monte Carlo simulation. Two management approaches—treating the contaminated groundwater with granular activated carbon and using imported water to lower the contamination level in the supply water—are used in a test problem. A random hydraulic conductivity field is used to produce the contamination variability at each extraction well. A trade-off relationship is obtained between the increased management cost and the level of protection by performing the uncertainty analysis at several supply water quality criteria for each of the two management approaches. This study demonstrates that despite the complexity in a contaminated groundwater supply system, a systematic approach can be used to quantify the many uncertainties associated with the management problem.

Delayed recovery from surgery causes personal suffering and substantial societal and economic costs. Whether immune mechanisms determine recovery after surgical trauma remains ill-defined. Single-cell mass cytometry was applied to serial whole-blood samples from 32 patients undergoing hip replacement to comprehensively characterize the phenotypic and functional immune response to surgical trauma. The simultaneous analysis of 14,000 phosphorylation events in precisely phenotyped immune cell subsets revealed uniform signaling responses among patients, demarcating a surgical immune signature. When regressed against clinical parameters of surgical recovery, including functional impairment and pain, strong correlations were found with STAT3 (signal transducer and activator of transcription), CREB (adenosine 3′,5′-monophosphate response element–binding protein), and NF-κB (nuclear factor κB) signaling responses in subsets of CD14 + monocytes ( R = 0.7 to 0.8, false discovery rate

Hydrothermal systems are formed by hydropower plants and different types of thermal power plants, i.e., plants that use different types of fuel. Thermal power plants are very versatile to meet energy demand; therefore, they can be dispatched at any time, with the exception of certain plants, such as nuclear, that are operated on a demand basis. Hydropower plants are also versatile, but exhibit a serious operational constraint, which is water availability. It is clear, therefore, the importance of planning the operation, especially in large hydrothermal systems. In countries where a high percentage of the energy consumed is produced by hydropower, there is a need to determine the degree of connection of the hydro system to increase its effectiveness and efficiency. A large interconnected hydro system can be better managed considering the hydrological diversity occurring in different watersheds. On the other hand, isolated subsystems of smaller sizes, may possibly be able to operate with greater safety. This paper discusses the issue of the energy gain of a hydrothermal system in view of its size. The case study is the national interconnected hydrothermal system in Brazil. The analysis employs an optimization model, HIDROTERM, which has been developed for the optimal planning and operation of the Brazilian hydrothermal system. A comparative analysis is made comparing the Brazilian system operated in a fully interconnected scheme and with some isolated subsystems operating independently. The results can be used to determine the optimal configuration of the hydrothermal system.

In Brazil over the last 12 years, on average 90% of energy consumed has come from hydropower generation. The hydro system includes 150 medium and large hydropower plants. Among these 150 plants, 135 are in operation today and 15 are planned to be operational by the end of 2017. The Brazilian hydro system is completely interconnected. About half of the hydropower plants have large storage capacities to regulate flows. The system is linked with the power grids in Paraguay, Argentina, Venezuela, and Uruguay. Brazil also receives natural gas imports from Bolivia. Each month hydropower generation must be determined. This is a complex decision-making process. The objective is to optimize the entire system operation, which depends on the inflows, storages, forecasts of demands, fuel prices for thermal units, and expansion of the system over a given planning horizon, typically looking ahead five years. Environmental, technical, social, and economic constraints have made it increasingly difficult to project and build new reservoirs with large storage capacities. As a result, newly built hydropower plants are mostly the run-of-river type. To better understand the process, this paper presents a historical survey of the installed capacity of hydropower and storage capacity of the system since 1908 and extends to the planned expansion over the next four years, through 2017. The storage capacity is represented by the concept of maximum stored energy in each reservoir and subsystem. The paper also presents the history of operation over the last 12 years. Data from 2000 and projections through 2017 indicate a significant reduction of relative regulating capacity, represented by the ratio of maximum storage and installed capacity. This reduction has a direct impact on decisions regarding operation and expansion of the complementary thermal system.

In this work we develop an inverse modeling procedure to identify the location and the dimensions of a single-component dense nonaqueous phase liquid (DNAPL) pool in a saturated porous medium under steady flow conditions. The inverse problem is formulated as a least squares minimization problem and solved by a search procedure based on the Levenberg-Marquardt method. Model output is calculated by an existing three-dimensional analytical model describing the transport of solute from a dissolving distributed noise upon the forward model-generated concentration field. We further test the algorithm's ability to predict the location and size of a DNAPL pool placed in a controlled three-dimensional bench-scale experiment. In this case we apply the Levenberg-Marquardt algorithm to the minimization of three types of residuals: ordinary residuals, weighted residuals with weights equal to the square of the inverse of the observations, and weighted residuals with weights obtained by adding a constant term to the observed concentrations. The results are sensitive to the location of the observation wells and to the type of residuals minimized. In general, better results in terms of pool location and dimensions were obtained by the minimization of weighted residuals with weights obtained by adding a constant term to the observed concentrations. The results also indicate that the inverse problem is nonunique and nonconvex even in the absence of observation errors. Finally, the sensitivity of the inverse modeling scheme to transport parameter uncertainty was addressed. The inverse solution was found to be extremely sensitive to errors in the dispersion coefficients and relatively insensitive to errors in the mass transfer coefficient.

In a multisource, multiquality regional water distribution system, water agencies often find that it is necessary to impose blending requirements at certain control points in the system in order to secure the desired water quality downstream of the control points. A nonlinear multicommodity flow model is proposed to optimize water delivery in such a system while at the same time meeting the imposed blending requirements. Waters from different sources with different water quality are considered as different commodities concurrently sharing a common distribution system. The model incorporates a set of nonlinear constraints to account for the perfect mixing condition at nodes where waters from multiple sources merge. The proposed model was first tested and verified on a simplified hypothetical system and then applied to a large-scale regional water distribution system in Southern California. The model is steady state and monthly. The results obtained indicate that the proposed methodology can efficiently con...

This paper proposes a new methodology for constructing groundwater models. The proposed methodology, which determines simultaneously both model structure and model parameters, is based on the following ideas: (1) When solving the inverse problem, different model structures always produce different model parameters; (2) since the number of possible model structures of an aquifer is infinite, the number of possible representative parameters is also infinite; (3) to obtain a set of appropriate representative model parameters, we must have an appropriate model structure; and (4) an appropriate model structure should be determined not only by observation data and prior information but also by the accuracy requirements of model applications. In this proposed methodology we start with a homogeneous model structure and, step by step, gradually increase the complexity of the model structure. At each level of complexity we calculate not only the fitting residual of parameter identification but also the error of model structure to determine if a more complex model structure is needed. The model structure error of using one model structure to replace another model structure is defined by a maximum-minimum (max-min) problem that is based on the distance between the two models and is measured in parameter, observation, and prediction (or decision) spaces. This proposed methodology is used to solve a hypothetical remediation design problem in which the true hydraulic conductivity is a random field with a certain trend. We have found that for the example problem, virtually identical pumping policy is obtained when a five-zone model with an optimized zonation pattern is used to represent the nonstationary random field. We have also found that observation errors have minimum impact on management solution in comparison with structure errors. To calculate the model structure error for this example, the inverse solution is coupled with a management problem. We have also developed an effective iteration method to handle nonlinear water quality constraints.

A nonlinear multiobjective management model has been developed for managing water use within a coastal region. Two conflicting objectives are considered: cost-effective allocation of surface water and ground water supplies, and minimization of saltwater intrusion. Optimal control of the system is examined by studying the response of these objectives to changes in ground water pumping rates and transfer of surface water between sources and users. System constraints include economic, operational, and institutional requirements. The objectives, some of the constraints, and the ground water flow equations are formulated as nonlinear functions of the decision variables. The flow model simulates the flow of ground water using a quasi-three-dimensional finite-difference model based on the sharp interface assumption. The nonlinear optimization problem is solved with MINOS. The flow simulation and the optimization model are considered simultaneously by linking the simulation directly into the optimization procedur...

Soil vapor extraction is a cost-effective technique for removing volatile organic compounds (VOCs) immobilized in the unsaturated zone. The design of a soil vapor extraction system (SVES) requires that the number and location of extraction wells and the extraction schedule for each extraction well be determined. In this study, schedule optimization for selected active wells is embedded in location optimization to provide an equal basis for system comparison. A combinatorial two-change local search is employed in both optimizations, but with different user-defined properties to address their distinct problem characteristics. The results indicate that the proposed two-change local search is robust and produces reliable designs. Impacts of soil heterogeneity and initial guess of design are evaluated. A detailed analysis of optimization results indicates that extraction well locations dominate the efficiency of contaminant removal. To reduce additional computation, a screening test based on results at the ear...

A methodology is developed for the design of an automatic gate controller for an on-demand canal system. The design is based on the EL-FLO plus RESET control concept developed previously by the U.S. Bureau of Reclamation. Two additional design parameters are included in this study to ensure a smooth upstream gate operation. The basic design parameters are optimized to achieve a stable flow condition in the entire canal system where multiple gates are operated to supply water to meet unexpected turnout demands along the canal. Due to the complexity involved in canal hydraulics, the optimization model is highly nonlinear. Decomposition allied with successive approximations is used for solution. The proposed design methodology, when applied to a section of the Caraibas Project in northeastern Brazil, showed that the proposed methodology is successful in minimizing hydraulic transients in a multipool canal system. A sensitivity analysis of the optimal design is conducted with respect to maximum demand level and the two new design parameters.

A chimeric gene was constructed from the genes coding for the human complement regulatory proteins, membrane cofactor protein (CD46) and decay-accelerating factor (CD55). The recombinant chimeric gene was transfected into Chinese hamster ovary cells. The gene product is a soluble, glycosylated, 110-kDa protein named complement activation blocker-2 (CAB-2). This protein possesses both factor I cofactor activity and decay-accelerating activity, and inactivates classical and alternative C3/C5 convertases in vitro. The specific activity of CAB-2 against cell-associated convertases is greater than that of soluble forms of either membrane cofactor protein or decay-accelerating factor or of both factors combined. CAB-2 also blocks the activation of complement in vivo, inhibiting both the Arthus reaction and Forssman shock in guinea pigs. Studies in rats demonstrate CAB-2 to exhibit favorable biphasic pharmacokinetics with a t1/2 alpha of 10 min and a t1/2 beta of 8 h; the beta phase accounts for 93% of the administered dose. CAB-2 may be an effective therapeutic treatment of acute human diseases in which excessive complement activation causes damage to normal tissues.

The Brazilian hydrothermal system consists of a completely linked network of 143 medium and large hydropower plants, 888 small hydropower plants, and 1602 thermal and 82 wind power plants, with a total installed capacity of 128,570 MW. The hydropower plants produce, on average, 91% of the total electricity consumed in the country, while the complementary thermal system is dispatched mainly during periods of drought. In our previous studies, we developed a nonlinear programming model, HIDROTERM, to optimize the management and operation of the hydrothermal system, considering individual hydropower plants, thermal generation and exchange, multiple uses of the water, and system expansion. The model is deterministic. In this paper, we develop a new version of HIDROTERM to incorporate the stochasticity of the inflows in the formulation. Additionally, hourly load variation is represented by three levels: peak, base, and low. The proposed approach is based on a two-stage stochastic programming with recourse. In the first stage (first time period) the system passes from its initial state to the final state based on deterministic inflow forecasts. From the second time period on (the second stage), the state of the system branches out according to inflow scenarios. The branching can be scaled up gradually until the end of the planning horizon. New developments are made in the formulation, interface, database and the underlying simulation model. The newly developed integrated decision support system is being tested on the entire Brazilian hydrothermal system. 1 Assistant Professor, University of Sao Paulo; e-mail: rczambon@usp.br; ASCE/EWRI Member 2 Professor, University of Sao Paulo, Brazil; e-mail: mtbarros@usp.br; ASCE Member 3 Professor, University of Campinas; e-mail: franco@fec.unicamp.br 4 Assistant Professor, University of Campinas; e-mail: francato@fec.unicamp.br 5 Consulting Engineer; e-mail: jelopes1@gmail.com 6 Engineer, Companhia Energetica de Sao Paulo; e-mail: luis.nogueira@cesp.com.br 7 Distinguished Professor, UCLA; e-mail: williamy@seas.ucla.edu; ASCE Honorary Member 1563 World Environmental and Water Resources Congress 2013: Showcasing the Future © ASCE 2013

This paper presents a methodology to analyze the reliability of a regional water distribution network. The proposed reliability analysis method focuses on the impact of link failures on source-demand connectivity, which is used as a measure of the mechanical reliability of the network. The mechanical reliability index is computed using the minimum cut-set method. The identification of minimum cut-sets consists of four stages: (1) For source-demand pairs; (2) for individual demand nodes; (3) for a group of demand nodes; and (4) for all demand nodes in the system. By using the multiple-stage approach, the total number of simulations required in the analysis is greatly reduced. Computational efficiency of the minimum cut-set method is further enhanced by using a highly efficient embedded generalized network algorithm to solve the optimization model used in the simulations. The results from the reliability analysis can be used to locate crucial pipelines in the network whose failure will severely impair the source-demand connectivity. The developed methodology is applied to a large-scale regional water distribution network associated with the Metropolitan Water District of Southern California.

Stochastic simulation is applied in a reliability analysis of a regional water distribution network. To complement the connectivity-based reliability analysis presented in the companion paper, the proposed stochastic simulation is aimed at evaluating the impacts of component failures on meeting demand at a certain quantity level. Simulation is conducted in a manner such that a sampling experiment of the system performance is repeated a sufficient number of times and the results are analyzed to obtain the desired reliability index. Given the mean time to failure and repair time of links, a large number of synthetic system conditions are generated and operations of system under the different conditions are simulated. Stochastic simulation of the system is conducted with a highly efficient embedded generalized network flow model (EMNET) to determine the optimal system operations for each scenario. The proposed reliability analysis method is applied to the water distribution network of the Metropolitan Water District of Southern California (MWDSC).

Soil vapor extraction is a cost-effective technique for the removal of volatile organic compounds (VOCs) immobilized in the unsaturated zone. The design of soil vapor extraction system (SVES) requires determination of the number and locations of extraction wells and corresponding extraction rates. At present, few guidelines for design are available. Thus most designs are based on empirical assessments, simplified analytical approximations, or limited trial-and-error simulations. In this paper, three optimization-based design methodologies are introduced: (1) implicit enumeration, (2) systematic reduction, and (3) local search. These methodologies address the combinatorial nature of the design problem and properly evaluate the well interference effects in a multiwell system. Through a benchmark problem, a comparative evaluation of the three methodologies is made with regard to their solution accuracy, computational efficiency, optimality heuristic, and application limitations.

A framework of simulation models for including human exposure to contaminants in regional scale aquifer management problems is presented. The framework includes horizontal flow and transport of contaminant plumes in the aquifer and multiple-pathway human exposure. Well water from the aquifer simulation model is used as the source of contaminant in the human exposure model. The exposure pathways considered for regional analysis are ingestion of foods grown using well water as part of the irrigation supply; ingestion and dermal absorption of contaminants in tap water; and inhalation of vaporized contaminants while bathing. An environmental compartment model is used to track the contaminant in irrigation water into the soil layers in contact with food products. The simulation framework is demonstrated in a study of the sensitivity of exposure to various aquifer and water supply parameters. The region used is hypothetical; however, the parameters are typical of California.

Using a generalized network formulation, the nonlinear evaporation loss function of a reservoir is directly incorporated in a water-supply-optimization model. The nonlinear function is first piecewise-linearized and the resulting line segments are represented by a series of arcs. An appropriate arc-flow multiplier is used to reflect the slope in each line segment. A convex penalty function is then used to preserve the order of arc-flow fulfillment. The proposed formulation can be applied to model other forms of losses in a water-supply system and it eliminates iterative solutions as required by a pure network formulation. The overall management model is solved by an embedded generalized network algorithm (EMNET), which is designed to solve a linear-programming problem with an embedded generalized network substructure. Together with our previous study EMNET is proven to be an efficient tool in solving general water-supply-optimization problems.

In recent years, considerable progress has been made in the development of fast network flow algorithms aiming at solving linear programming problems with network substructures. Recognizing the fact that the basic structure of a water-supply system is a network, network algorithms have been used for system operation and management. However, to date, most algorithms are designed to solve transshipment problems in a pure network setting with total demand being equal to total supply. The non–network-type constraints and variables are precluded from the network models. Consequently, network models are used to perform optimization only for the network portion of the water-supply system under certain overall operational guidelines. In this study, an algorithm, EMNET, is introduced for solving the regional-water-supply-system optimization that corresponds to a generalized network problem with additional non–network-type constraints and non–network-type variables. The multiperiod, multiobjective optimization mode...

The expression patterns of a variety of cytoskeletal antigens were studied in normal human tissues (placenta, umbilical cord, myometrium, colon, mammary gland, testis, skeletal muscle, myocardium) as well as in abnormal human tissues (palmar fibromatosis, fibrocystic disease of the mammary gland, mammary carcinoma). The immunohistochemical binding patterns of the monoclonal antibody GB 42 were compared to those of commercial antibodies directed against vimentin, desmin, smooth muscle myosin, pan actin, alpha-smooth muscle actin and gamma-smooth muscle actin. Methods applied comprised immunohistochemistry on cryostat sections and paraffin sections. Immunogold immunocytochemistry was performed on Lowicryl sections. The patterns of GB 42-binding were confirmed biochemically by SDS-PAGE and Western-blotting, and quantitative amino acid analysis. Our data suggest that the monoclonal antibody GB 42 recognizes an actin isoform which is identical to, or closely related to, gamma-smooth muscle actin. Unlike the commercially available antibody against gamma-smooth muscle actin, GB 42 does not cross-react with alpha-skeletal or alpha-cardiac actins. The GB 42-antigen is expressed in smooth muscle cells, myoepithelial cells and in later stages of differentiation of myofibroblasts, in all the tissues investigated. Throughout the development of smooth muscle cells and myofibroblasts, the appearance of the GB 42-antigen occurs after the expression of vimentin, desmin and alpha-smooth muscle actin, but prior to the expression of smooth muscle myosin. GB 42 is a reliable marker for higher stages of differentiation of smooth muscle cells and myofibroblasts.

A water-supply-distribution-system planning model has been developed using a directed graph algorithm as its pre- and postprocessors and a linear programming (LP) procedure as an “intelligent” system operator at its core. The directed graph, as a preprocessor, is used to produce a mathematical representation of the distribution system in question, to check the consistency and correctness of the network topology before an input file is created for the LP procedure. In the postprocessing mode, the directed graph generates files for graphical displays of model results and performs graph analyses such as depth- and breadth-first traversals, cut set and connectivity for evaluating water-quality blending, tracking of source-to-demand contributions, system reliability, and lifeline objectives. Unlike the conventional formulation of a resource-allocation problem, the demand requirements, storage capacities, and other system constraints are removed from the constraint set and translated into a composite objective function. This methodology was successfully applied to the Metropolitan Water District of Southern California’s (MWD’s) distribution system. The results indicate that the combination of using an LP procedure and graph algorithm is a very versatile tool for solving large-scale water-distribution problems. This paper documents the concept used in developing the system-planning model and the results of its application to a simplified example as well as application to four case studies involving the entire MWD’s distribution system.

Complement is a major mediator of tissue injury in several types of glomerulonephritis. However, no therapeutic agents that inhibit complement activation are available for human use. sCR1 (TP10, BRL 55736) is a recombinant, soluble human complement receptor 1 (CR1) molecule lacking transmembrane and cytoplasmic domains that inhibits C3 and C5 convertase activity by preferentially binding C4b and C3b. To test the efficacy of sCR1 on complement-mediated glomerulonephritis, rats were pretreated with sCR1 (60 mg/kg per day) before and during the induction of three models of complement-dependent glomerulonephritis (concanavalin A and antithymocyte serum models of proliferative glomerulonephritis, passive Heyman nephritis). Daily sCR1 and complement hemolytic activity levels were measured, and renal histology and urine protein excretion were examined. Mean serum sCR1 levels of 100 to 200 micrograms/mL were maintained with a reduction in complement hemolytic activity to less than 15% in most animals. In the antithymocyte serum model, sCR1-treated animals had significant reductions in mesangiolysis, glomerular platelet and macrophage infiltrates, and proteinuria at 48 h. In the concanavalin A model, sCR1 significantly reduced glomerular C3 and fibrin deposits, platelet infiltrates, and proteinuria at 48 h. In passive Heymann nephritis, proteinuria was also significantly reduced (199 +/- 8.5 versus 125 +/- 16 mg/day, P0.002) at 5 days. It was concluded that sCR1 significantly reduces both morphologic and functional consequences of several different types of complement-mediated glomerulonephritis and deserves evaluation as a potential therapeutic agent in complement-mediated immune glomerular disease in humans.

A two-layered confined-unconfined numerical model for flow and mass transport is developed for the San Jacinto Basin. The model structure is determined by the geological structure of the Basin and model parameters are calibrated using 20 years of historical records. The total number of historical head observations used for the flow model calibration is 1,117 and the total number of the estimated parameters is 91. The two-layered transport model is also calibrated using historical water quality records. Sensitivity analysis of the flow model shows that only 68 parameters (out of a total of 91) are relatively sensitive and reliable. However, the unreliable parameters (23 of them) are found to be insensitive and thus not significant to the prediction and management of conjunctive use of surface water and ground water. The developed flow model has been used to study the two proposed artificial recharge scenarios for the San Jacinto Basin. We have found that during a relatively dry condition, an artificial recharge rate of 80 acre-ft/day can be achieved during the recharge period October through January. However, for a relatively wet condition, only 80 percent of the proposed rate can be effectively stored in the Basin during these months.

A new parameterization method for parameter identification is presented. This method allows us to incorporate all well log data and any other geological information into the inverse solution procedure for three-dimensional groundwater modeling. In the proposed method, unknown parameters, such as hydraulic conductivity and storage coefficient, are directly related to the geological materials. Existing well logs of an aquifer can provide information of local geological structures along the vertical direction. By using these data, as well as any other geological information available, the three-dimensional structure of the aquifer can be estimated by means of the geostatistical method. Then, art inverse problem can be formulated, leaving fewer unknown parameters to be identified. The advantages of the proposed method are the following: (1) all existing geological and hydrogeological information available is used for parameter identification, (2) the identified parameters are independent of the complexity of the simulation model, (3( the ill-posedness of the inverse solution is mitigated, and (4) the identified parameters are distributed and physically meaningful. In a hypothetical example, the three-dimensional distribution of hydraulic conductivity is easily identified using the proposed method. The results indicate that the identified distributed parameter vector is very close to the “true” distribution, and the inverse solution is highly stable with respect to observation errors. The proposed methodology has enabled us to determine the three-dimensional distribution of hydraulic conductivity and storativity in the Hemet basin, Riverside, California.

A three-dimensional finite element model (FEM) was developed to predict temperature and moisture distributions in food materials during microwave heating. The FEM was tested with analytical solutions and commercial software (TWODEPEP, ANSYS) calculated values. The FEM predictions compared favorably with analytical solutions (within 0.066% of maximum temperature) and values calculated from commercial softwares (within 0.14% of maximum temperature). The three-dimensional FEM was also verified using experimental data from microwave oven heated cylinder- and slab-shaped potato specimens. A fluoroptic temperature measurement system and the near infrared (NIR) technique were used to measure temperature and moisture distributions, respectively. The FEM predicted temperature in potato samples agreed with measured results. The absolute maximum difference for slab geometry after 60 s of heating was 8.1 °C (or relative difference of 15.5% from the measured value), whereas, for the cylindrical geometry, it was 8.7 °C (or relative difference of 11.4%). The absolute moisture differences after 60 s of heating between FEM predictions and measured values for potato slab and cylinder were within 1.97% wet basis (or relative difference of 2.4%) and 1.85% wet basis (or relative difference of 2.1%), respectively.

[1] The ability of a particular model to accurately predict how a system responds to forcing is predicated on various model parameters that must be appropriately identified. There are many algorithms whose purpose is to solve this inverse problem, which is often computationally intensive. In this study, we propose a new algorithm that significantly reduces the computational burden associated with parameter identification. The algorithm is an extension of the quasilinearization approach where the governing system of differential equations is linearized with respect to the parameters. The resulting inverse problem therefore becomes a linear regression or quadratic programming problem (QP) for minimizing the sum of squared residuals; the solution becomes an update on the parameter set. This process of linearization and regression is repeated until convergence takes place. This algorithm has not received much attention, as the QPs can become quite large, often infeasible for real-world systems. To alleviate this drawback, proper orthogonal decomposition is applied to reduce the size of the linearized model, thereby reducing the computational burden of solving each QP. In fact, this study shows that the snapshots need only be calculated once at the very beginning of the algorithm, after which no further calculations of the reduced-model subspace are required. The proposed algorithm therefore only requires one linearized full-model run per parameter at the first iteration followed by a series of reduced-order QPs. The method is applied to a groundwater model with about 30,000 computation nodes where as many as 15 zones of hydraulic conductivity are estimated.

There are many conflicts involved in the operation of a hydrothermal system mainly due to competitive uses of water. That is the case of Sao Francisco River located in the northeast region in Brazil. The hydro system in this region has an installed capacity of 10.7 GW and supports 13% of the Brazilian hydro electrical power. Due to the scarcity of water in this region the operation of this system has been questioned in the last few years. The competitive uses of water in this region are water supply, irrigation, animal raising and environmental protection. These demands can be attended by a proposed large water transfer system from Sao Francisco river to other watersheds in the region. The electrical sector is planning to review the reservoir operation rules in order to attend these demands. This paper presents results from a study conducted to evaluate the impacts of the hydro production caused by the multipurpose uses of water in the Sao Francisco River. The study was conducted by applying the HIDROTERM model, which is an optimization model that maximizes hydropower production and minimizes thermo production based on fossil fuels. A new objective function was added to the HIDROTERM model in order to evaluate the proposed water transfer system. The trade-offs among energy, water supply, irrigation and environment protection are presented, along with other relevant discussions.

[1] This paper develops alternative strategies for European call options for water purchase under hydrological uncertainties that can be used by water resources managers for decision making. Each alternative strategy maximizes its own objective over a selected sequence of future hydrology that is characterized by exceedance probability. Water trade provides flexibility and enhances water distribution system reliability. However, water trade between two parties in a regional water distribution system involves many issues, such as delivery network, reservoir operation rules, storage space, demand, water availability, uncertainty, and any existing contracts. An option is a security giving the right to buy or sell an asset; in our case, the asset is water. We extend a flow path-based water distribution model to include reservoir operation rules. The model simultaneously considers both the physical distribution network as well as the relationships between water sellers and buyers. We first test the model extension. Then we apply the proposed optimization model for European call options to the Tainan water distribution system in southern Taiwan. The formulation lends itself to a mixed integer linear programming model. We use the weighing method to formulate a composite function for a multiobjective problem. The proposed methodology provides water resources managers with an overall picture of water trade strategies and the consequence of each strategy. The results from the case study indicate that the strategy associated with a streamflow exceedence probability of 50% or smaller should be adopted as the reference strategy for the Tainan water distribution system.

This chapter summarizes recent progress in model calibration and model uncertainty assessment in groundwater modeling. The main focus is on parameter structure identification of hydraulic conductivity using the Bayesian maximum likelihood approach. In general, parameter structure identification seeks to identify the parameter dimension, parameter pattern, and associated parameter values. We discuss the importance of parameterization, which is used to define parameter structure and to formulate the inverse problem of parameter structure identification. We propose a generalized parameterization (GP) method for parameter structure identification. GP integrates the traditional zonation and interpolation methods (including kriging) and avoids the shortcomings of each individual method. It captures aquifer heterogeneity by a combination of zonal structure and continuous distribution. An indicator generalized parameterization (IGP) is further introduced to address the interpolation point selection problem, which is an important issue in parameterization. We introduce model selection, model discrimination, and statistical information criteria to select the best parameterization method. To resolve the nonuniqueness problem in parameterization due to lack of data and data uncertainty, we employ Bayesian model averaging (BMA) to consider multiple parameterization methods for parameter structure identification. Finally, based on several optimality criteria we offer the experimental design as the ultimate goal of collecting additional informative data to reduce estimation uncertainty.

[1] This study develops a groundwater management model for real-time operation of an aquifer system. A groundwater flow model is allied with a nudging data assimilation algorithm that reduces the forecast error, minimizes the risk of system failure, and improves management strategies. The nudging algorithm treats the unknown private pumping as an additional sink term in the groundwater flow equation and provides a consistently physical interpretation for the identification of pumping rates. The system response due to pumping and injection is represented by a response matrix that is generated by the influence coefficient method. The response matrix (with a much smaller dimension) is used as a reduced model and is embedded directly in the management model as a part of the constraint set. Additionally, the influence coefficient method is utilized to include the nudging effect in the reduced model. The management model optimizes the monthly operation for 12 months into the future and determines the optimal strategy using the information provided by nudging. The management model is updated at the beginning of each month when new head observations and pumping data become available. We also discuss the utility, accuracy, and efficiency of the proposed management model for real-time operation.