Output-based Aid for Sustainable Sanitation

A review of the experience to date in applying output-based and other results-oriented financing aid formats to the delivery of sanitation services and goods in developing countries. The paper looks at the theoretical underpinnings which justify output-based subsidies in sanitation, reviews a selection of output-based aid projects and then proposes some new approaches which could help to make financing in sanitation more effective and accountable

Estimating Model Error Using Observation Residuals

This presentation discusses an approach to estimate model error using observation residuals. Based on the sequential fixed-lag smoother; we introduce a diagnostic procedure to allow estimating model error over a dense observing system. Optimality considerations are examined in light of the sequential results. The procedure is re-interpreted in the language of variational assimilation, such as 4d-Var. Illustrations of the approach are given by studying both identical-twin and fraternal-twin experimental settings for a system governed by Lorenz-type dynamics. Preliminary results by looking at observation residual statistics for the ECMWF data assimilation system are also shown. The presentation will be part of a series of discussions on issues related to four-dimensional data assimilation under weak-constraint and methodologies to estimate model error

Processus de conception multidisciplinaire dédié aux configurations Blended Wing Body

The Blended Wing Body (BWB) configuration seems to be one of the most promising concepts to replace the current passenger transport aircrafts with substantial improvement of their performance and reduction of their environmental footprint. However the expected gains still need to be precisely evaluated with airplanes to design. BWB concept is a highly coupled system because every sizing discipline is connected to a single system: the wing. This paper presents the multidisciplinary design analysis and optimization process of a blended wing body and its application to a long-haul commercial transport mission

Magnetic Reversal Time in Open Long Range Systems

Topological phase space disconnection has been recently found to be a general phenomenon in isolated anisotropic spin systems. It sets a general framework to understand the emergence of ferromagnetism in finite magnetic systems starting from microscopic models without phenomenological on-site barriers. Here we study its relevance for finite systems with long range interacting potential in contact with a thermal bath. We show that, even in this case, the induced magnetic reversal time is exponentially large in the number of spins, thus determining {\it stable} (to any experimental observation time) ferromagnetic behavior. Moreover, the explicit temperature dependence of the magnetic reversal time obtained from the microcanonical results, is found to be in good agreement with numerical simulations. Also, a simple and suggestive expression, indicating the Topological Energy Threshold at which the disconnection occurs, as a real energy barrier for many body systems, is obtained analytically for low temperature

On Variational Data Assimilation in Continuous Time

Variational data assimilation in continuous time is revisited. The central techniques applied in this paper are in part adopted from the theory of optimal nonlinear control. Alternatively, the investigated approach can be considered as a continuous time generalisation of what is known as weakly constrained four dimensional variational assimilation (WC--4DVAR) in the geosciences. The technique allows to assimilate trajectories in the case of partial observations and in the presence of model error. Several mathematical aspects of the approach are studied. Computationally, it amounts to solving a two point boundary value problem. For imperfect models, the trade off between small dynamical error (i.e. the trajectory obeys the model dynamics) and small observational error (i.e. the trajectory closely follows the observations) is investigated. For (nearly) perfect models, this trade off turns out to be (nearly) trivial in some sense, yet allowing for some dynamical error is shown to have positive effects even in this situation. The presented formalism is dynamical in character; no assumptions need to be made about the presence (or absence) of dynamical or observational noise, let alone about their statistics.Comment: 28 Pages, 12 Figure

A weak-constraint 4DEnsembleVar. Part II: experiments with larger models

In recent years, hybrid data assimilation methods which avoid computation of tangent linear and adjoint models by using ensemble 4-dimensional cross-time covariances have become a popular topic in Numerical Weather Prediction. 4DEnsembleVar is one such method. In spite of its capabilities, its application can sometimes become problematic due to the not-trivial task of localising cross-time covariances. In this work we propose a formulation that helps to alleviate such issues by exploiting the presence of model error, i.e a weak-constraint 4DEnsembleVar. We compare the weak-constraint 4DEnsenbleVar to that of other data assimilation methods. This is part II of a two-part paper. In part I, we describe the 4DEnsembleVar framework and problems with localised temporal cross-covariances associated with this method are discussed and illustrated on the Korteweg de Vries model. We also introduce our Weak-Constraint 4DEnsembleVar formulation and show how it can alleviate --at least partially-- the problem of having low-quality time cross-covariances. The second part of this paper deals with experiments on larger and more complicated models, namely the Lorenz 1996 model and a modified shallow water model with simulated convection, both of them under the presence of model error. We investigate the performance of weak-constraint 4DEnsembleVar against strong-constraint 4DEnsembleVar (both with and without localisation) and other traditional methods (4DVar and the Local Ensemble Transform Kalman Smoother). Using the analysis root mean square error (RMSE) as a metric, these methods have been compared considering observation density (in time and space), observation period, ensemble sizes and assimilation window length. In this part we also explain how to perform outer loops in the EnVar methods. We show that their use can be counter-productive if the presence of model error is ignored by the assimilation method. We show that the addition of a weak-constraint generally improves the RMSE of 4DEnVar in cases where model error has time to develop, especially in cases with long assimilation windows and infrequent observations. We have assumed good knowledge of the statistics of this model error

A Vitual-Force Based Swarm Algorithm for Balanced Circular Bin Packing Problems

Balanced circular bin packing problems consist in positioning a given number of weighted circles in order to minimize the radius of a circular container while satisfying equilibrium constraints. These problems are NP-hard, highly constrained and dimensional. This paper describes a swarm algorithm based on a virtual-force system in order to solve balanced circular bin packing problems. In the proposed approach, a system of forces is applied to each component allowing to take into account the constraints and minimizing the objective function using the fundamental principle of dynamics. The proposed algorithm is experimented and validated on benchmarks of various balanced circular bin packing problems with up to 300 circles. The reported results allow to assess the effectiveness of the proposed approach compared to existing results from the literature.Comment: 23 pages including reference

Progress Towards Integrating the Finite-Volume Cubed-Sphere (FV3) Dynamical Core Tangent Linear and Adjoint Models into JEDI

The Joint Effort for Data assimilation Integration (JEDI) -- led by the Joint Center for Satellite Data Assimilation (JCSDA) -- is an inter-organizational endeavor to develop a common framework for performing data assimilation. This extensive framework will ultimately provide solvers, observation operators, interpolation and model interfaces using object oriented modeling. Two partners involved in JEDI use or plan to use the Finite Volume Cubed-Sphere (FV3) dynamical core to produce weather forecasts; these are NASA's Global Modeling and Assimilation Office and NOAA's National Center for Environment Prediction. In this work we present an update on ongoing efforts to integrate the FV3 tangent linear and adjoint models into the prototype JEDI framework. We setup and run a simple cycled data assimilation experiment using 4DVAR on the cubed sphere grid and with the FV3 tangent linear and adjoint models. Development of the observation operators for JEDI is separately underway. Instead of using real observations a simplified set of simulated observations will be used. We discuss the steps required to bring the FV3 linearized model into the object oriented framework and consider what would be the computational requirements of running this configuration for an operational system. FV3 uses a small time-step to ensure that small scales are well resolved, however this presents design challenges when running 4DVAR with the adjoint. An approach to storing the FV3 model trajectory has been developed that maintains the flexibility of using automatic differentiation. We discuss how this approach is incorporated into the framework. Other important uses of adjoint models include computing observation impacts and singular vectors, we consider how these tools can be included in JEDI

Better use of capital to deliver sustainable water supply and sanitation services: Practical examples and suggested next steps

The costs of meeting the SDG WASH targets will be several times higher than investment levels during the MDG era (2000–15). The immense scale of the financing gap calls for innovative solutions. In addition to mobilizing more funding another approach is to deliver the needed infrastructure more efficiently and effectively and thus reduce the financing gap. Capital expenditure efficiency (CEE)—the efficient and effective use of capital—is less documented compared to operational efficiency. Although improving operating efficiency is frequently highlighted and readily evaluated, the scope for capital cost efficiencies is poorly understood, frequently overlooked, and difficult to evaluate, even though the scale of savings can be significant—in fact, capital and operating costs are equally important when considering full cost recovery. This study compiles case studies that show the "art of the possible" in CEE. The report is not encyclopedic—many more examples could surface from a comprehensive study. It also doesn’t quantify the savings possible through increasing CEE. However, almost all the examples show capital savings of 25 percent or more compared to traditional solutions. This alone this should give policy makers, donors, and utility managers pause for thought and encourage them to develop CEE in their sectors, projects, or utilities. A 25 percent improvement in CEE would allow existing investments to deliver a 33 percent increase in benefits

Metallic glass/PVDF magnetoelectric laminates for resonant sensors and actuators: a review

Among magnetoelectric (ME) heterostructures, ME laminates of the type Metglas-like / PVDF (magnetostrictive+piezoelectric constituents) have shown the highest induced ME voltages, usually detected at the magnetoelastic resonance of the magnetostrictive constituent. This ME coupling happens because of the high cross-correlation coupling between magnetostrictive and piezoelectric material, and is usually associated with a promising application scenario for sensors or actuators. In this work we detail the basis of the operation of such devices, as well as some arising questions (as size effects) concerning their best performance. Also, some examples of their use as very sensitive magnetic fields sensors or innovative energy harvesting devices will be reviewed. At the end, the challenges, future perspectives and technical difficulties that will determine the success of ME composites for sensor applications are discussed.J.G., A.L. and J.M.B. would like to thank the financial support from the Basque Government under ACTIMAT and MICRO4FAB projects (Etortek program) and Research Groups IT711-13 project. A. Lasheras wants to thank the Basque Government for financial support under FPI Grant. Technical and human support provided by SGIker (UPV/EHU, MICINN, GV/EJ, ESF) is gratefully acknowledged. P.M., N.P. and S. L.-M. thank the Portuguese Fundação para a Ciência e Tecnologia (FCT) for financial Sensors 2017, 13 19 support under Strategic Funding UID/FIS/04650/2013 and project PTDC/EEI-SII/5582/2014, including FEDER funds, UE. P. Martins acknowledges also support from FCT (SFRH/BPD/96227/2013 grant). Financial support from the Spanish Ministry of Economy and Competitiveness (MINECO) through the project MAT2016-76039-C4-3-R (AEI/FEDER, UE) (including the FEDER financial support) is also acknowledgedinfo:eu-repo/semantics/publishedVersio