Measurement network design including traveltime determinations to minimize model prediction uncertainty

Traveltime determinations have found increasing application in the characterization of groundwater systems. No algorithms are available, however, to optimally design sampling strategies including this information type. We propose a first-order methodology to include groundwater age or tracer arrival time determinations in measurement network design and apply the methodology in an illustrative example in which the network design is directed at contaminant breakthrough uncertainty minimization. We calculate linearized covariances between potential measurements and the goal variables of which we want to reduce the uncertainty: the groundwater age at the control plane and the breakthrough locations of the contaminant. We assume the traveltime to be lognormally distributed and therefore logtransform the age determinations in compliance with the adopted Bayesian framework. Accordingly, we derive expressions for the linearized covariances between the transformed age determinations and the parameters and states. In our synthetic numerical example, the derived expressions are shown to provide good first-order predictions of the variance of the natural logarithm of groundwater age if the variance of the natural logarithm of the conductivity is less than 3.0. The calculated covariances can be used to predict the posterior breakthrough variance belonging to a candidate network before samples are taken. A Genetic Algorithm is used to efficiently search, among all candidate networks, for a near-optimal one. We show that, in our numerical example, an age estimation network outperforms (in terms of breakthrough uncertainty reduction) equally sized head measurement networks and conductivity measurement networks even if the age estimations are highly uncertain

Advanced recovery systems wind tunnel test report

Pioneer Aerospace Corporation (PAC) conducted parafoil wind tunnel testing in the NASA-Ames 80 by 120 test sections of the National Full-Scale Aerodynamic Complex, Moffett Field, CA. The investigation was conducted to determine the aerodynamic characteristics of two scale ram air wings in support of air drop testing and full scale development of Advanced Recovery Systems for the Next Generation Space Transportation System. Two models were tested during this investigation. Both the primary test article, a 1/9 geometric scale model with wing area of 1200 square feet and secondary test article, a 1/36 geometric scale model with wing area of 300 square feet, had an aspect ratio of 3. The test results show that both models were statically stable about a model reference point at angles of attack from 2 to 10 degrees. The maximum lift-drag ratio varied between 2.9 and 2.4 for increasing wing loading

Economic efficiency and wealth prospects in the global network of countries

openIn recent years, the integration of physics into the economic field has proven to supply a deeper understanding of the complex web of interactions between the countries and the global markets, leading to a substantial development of the Econophysics branch of research. This work provides a contribution in this context through the characterization of the quantitative nexus which links the economic growth of the countries to the evolution over time of their trades and to the overall diversification of their commercial activity. The global trade system is effectively represented by a bipartite network, whose properties are investigated by means of a dynamic model consisting in a set of coupled stochastic differential equations and of a set of complexity measures derived from the celebrated Shannon's entropy function. The unification of these two methods of analysis provides a measure of the economic efficiency of the countries and leads to the realization of meaningful assessments of their wealth prospects. From the practical point of view, the theoretical models are implemented through proper Python and C++ codes.In recent years, the integration of physics into the economic field has proven to supply a deeper understanding of the complex web of interactions between the countries and the global markets, leading to a substantial development of the Econophysics branch of research. This work provides a contribution in this context through the characterization of the quantitative nexus which links the economic growth of the countries to the evolution over time of their trades and to the overall diversification of their commercial activity. The global trade system is effectively represented by a bipartite network, whose properties are investigated by means of a dynamic model consisting in a set of coupled stochastic differential equations and of a set of complexity measures derived from the celebrated Shannon's entropy function. The unification of these two methods of analysis provides a measure of the economic efficiency of the countries and leads to the realization of meaningful assessments of their wealth prospects. From the practical point of view, the theoretical models are implemented through proper Python and C++ codes

Faster Development of AUTOSAR compliant ECUs through simulation

International audienceVirtualization allows the simulation of automotive ECUs on a Windows PC executing in a closed-loop with a vehicle simulation model. This approach enables moving many development tasks from road or test rigs and HiL (Hardware in the loop) to PCs, where they can often be performed faster and cheaper. Technical challenge: How to port ECU tasks and basic software to Windows PC with reasonable effort, so that key development tasks can be performed on a PC, without the need of accessing real hardware such as vehicle prototypes, test rigs or HiL facilities. This paper presents a new solution for the use case of ECUs developed within the emerging AUTOSAR standard: First, the AUTOSAR authoring tool AUTOSAR Builder (Dassault Systèmes) is used to design the application software and system aspects of a single ECU or an distributed embedded system which is then stored as AUTOSAR XML descriptions. The application code can either be developed in the AUTOSAR Builder environment or auto-generated by tools such as Embedded Coder (MathWorks), TargetLink (dSPACE) or Ascet (ETAS). Once tested in AUTOSAR Builder, selected software components or compositions can be exported including an AUTOSAR OS (Operating System) and RTE (Run- Time Environment) as an FMU (Functional Mockup Unit). FMU [4] is a new exchange format for models that has been developed in the EU-funded MODELISAR project (2008 - 2011) and since then gained considerable acceptance across multiple industries and tools. The FMU can then be imported into the virtual ECU tool Silver (QTronic), where it can be co-simulated with vehicle models originating from a wide range of simulation tools, including Dymola, SimulationX, MapleSim and AMESim. Vehicle models are again provided as FMUs, or via proprietary binary export formats, typically Windows DLLs. Tools for measurement and calibration such as CANape (Vector Informatik) or INCA (ETAS) can then be connected to the virtual ECU running on PC, to directly measure or tune its parameters, like an engineer would do in a real car. Virtual ECUs are also used to move testing activities from test rigs and HiLs to Windows PC

Towards a Noninvasive Intracranial Tumor Irradiation Using 3D Optical Imaging and Multimodal Data Registration

Conformal radiotherapy (CRT) results in high-precision tumor volume irradiation. In fractioned radiotherapy (FRT), lesions are irradiated in several sessions so that healthy neighbouring tissues are better preserved than when treatment is carried out in one fraction. In the case of intracranial tumors, classical methods of patient positioning in the irradiation machine coordinate system are invasive and only allow for CRT in one irradiation session. This contribution presents a noninvasive positioning method representing a first step towards the combination of CRT and FRT. The 3D data used for the positioning is point clouds spread over the patient's head (CT-data usually acquired during treatment) and points distributed over the patient's face which are acquired with a structured light sensor fixed in the therapy room. The geometrical transformation linking the coordinate systems of the diagnosis device (CT-modality) and the 3D sensor of the therapy room (visible light modality) is obtained by registering the surfaces represented by the two 3D point sets. The geometrical relationship between the coordinate systems of the 3D sensor and the irradiation machine is given by a calibration of the sensor position in the therapy room. The global transformation, computed with the two previous transformations, is sufficient to predict the tumor position in the irradiation machine coordinate system with only the corresponding position in the CT-coordinate system. Results obtained for a phantom show that the mean positioning error of tumors on the treatment machine isocentre is 0.4 mm. Tests performed with human data proved that the registration algorithm is accurate (0.1 mm mean distance between homologous points) and robust even for facial expression changes

Sketch-To-Solution: An Exploration of Viscous CFD with Automatic Grids

Numerical simulation of the Reynolds-averaged NavierStokes (RANS) equations has become a critical tool for the design of aerospace vehicles. However, the issues that affect the grid convergence of three dimensional RANS solutions are not completely understood, as documented in the AIAA Drag Prediction Workshop series. Grid adaption methods have the potential for increasing the automation and discretization error control of RANS solutions to impact the aerospace design and certification process. The realization of the CFD Vision 2030 Study includes automated management of errors and uncertainties of physics-based, predictive modeling that can set the stage for ensuring a vehicle is in compliance with a regulation or specification by using analysis without demonstration in flight test (i.e., certification or qualification by analysis). For example, the Cart3D inviscid analysis package has automated Cartesian cut-cell gridding with output-based error control. Fueled by recent advances in the fields of anisotropic grid adaptation, error estimation, and geometry modeling, a similar work flow is explored for viscous CFD simulations; where a CFD application engineer provides geometry, boundary conditions, and flow parameters, and the sketch-to-solution process yields a CFD simulation through automatic, error-based, grid adaptation

Agricultural Experiment Station News May 1989

CONTENTS: MARION O\u27LEARY HEADS BIOCHEMISTRY GLENN HOFFMAN LEADS AG ENGINEERING ARD DEFINITION OF INTERDISCIPLINARY VS MULTIDISCIPLINARY RESEARCH NOTES FROM THE ARD ADVISORY COUNCIL INDIRECT COSTS-WHERE DO THEY GO? STATEMENT OF ACCOMPLISHMENTS ARDC-MEAD ENVIRONMENTAL SITUATION RESEARCH GRANTS AND CONTRACTS RECEIVED FEBRUARY & MARCH 1989 NEW AND REVISED PROJECT

Proceedings of the 8th International Junior Researcher and Engineer Workshop on Hydraulic Structures

Full proceedings for the 8th International Junior Researcher and Engineer Workshop on Hydraulic Structures

Stochastic forward and inverse groundwater flow and solute transport modeling

Keywords: calibration, inverse modeling, stochastic modeling, nonlinear biodegradation, stochastic-convective, advective-dispersive, travel time, network design, non-Gaussian distribution, multimodal distribution, representers This thesis offers three new approaches that contribute to the ability of groundwater modelers to better account for heterogeneity in physically-based, fully distributed groundwater models. In both forward and inverse settings, this thesis tackles major issues with respect to handling heterogeneity and uncertainty in various situations, and thus extends the ability to correctly and/or effectively deal with heterogeneity to these particular situations. The first method presented in the thesis uses the recently developed advective-dispersive streamtube approach in combination with a one-dimensional traveling wave solution for nonlinear bioreactive transport, to study the interplay between physical heterogeneity, local-scale dispersion and nonlinear biodegradation and gain insight in the long-term asymptotic behavior of solute fronts, in order to deduce (the validity of) upscaling equations. Using the method in synthetic small-scale numerical experiments, it is shown that asymptotic front shapes are neither Fickian nor constant, which raises questions about the current practice of upscaling bioreactive transport. The second method presented in the thesis enhances the management of heterogeneity by extending inverse theory (specifically, the representer-based inverse method) to determinations of groundwater age/travel time. A first-order methodology is proposed to include groundwater age or tracer arrival time determinations in measurement network design. Using the method, it is shown that, in the applied synthetic numerical example, an age estimation network outperforms equally sized head measurement networks and conductivity measurement networks, even if the age estimations are highly uncertain. The study thus suggests a high potential of travel time/groundwater age data to constrain groundwater models. Finally, the thesis extends the applicability of inverse methods to multimodal parameter distributions. Multimodal distributions arise when multiple statistical populations exist within one parameter field, each having different means and/or variances of the parameter of concern. No inverse methods exist that can calibrate multimodal parameter distributions while preserving the geostatistical properties of the various statistical populations. The thesis proposes a method that resolves the difficulties existing inverse methods have with the multimodal distribution. The method is successfully applied to both synthetic and real-world cases. </p