Flush air data system calibration using numerical simulation

The use of computational fluid dynamics simulations for calibrating a flush air data system is described, In particular, the flush air data system of the HYFLEX hypersonic vehicle is used as a case study. The HYFLEX air data system consists of nine pressure ports located flush with the vehicle nose surface, connected to onboard pressure transducers, After appropriate processing, surface pressure measurements can he converted into useful air data parameters. The processing algorithm requires an accurate pressure model, which relates air data parameters to the measured pressures. In the past, such pressure models have been calibrated using combinations of flight data, ground-based experimental results, and numerical simulation. We perform a calibration of the HYFLEX flush air data system using computational fluid dynamics simulations exclusively, The simulations are used to build an empirical pressure model that accurately describes the HYFLEX nose pressure distribution ol cr a range of flight conditions. We believe that computational fluid dynamics provides a quick and inexpensive way to calibrate the air data system and is applicable to a broad range of flight conditions, When tested with HYFLEX flight data, the calibrated system is found to work well. It predicts vehicle angle of attack and angle of sideslip to accuracy levels that generally satisfy flight control requirements. Dynamic pressure is predicted to within the resolution of the onboard inertial measurement unit. We find that wind-tunnel experiments and flight data are not necessary to accurately calibrate the HYFLEX flush air data system for hypersonic flight.

Image calibration to like-values in mapping shallow water quality from multitemporal data

The applicability of image calibration to like-values in mapping water quality parameters from multitemporal images is explored, Six sets of water samples were collected at satellite overpasses over Moreton Bay, Brisbane, Australia. Analysis of these samples reveals that waters in this shallow bay are mostly TSS-dominated, even though they are occasionally dominated by chlorophyll as well. Three of the images were calibrated to a reference image based on invariant targets. Predictive models constructed from the reference image were applied to estimating total suspended sediment (TSS) and Secchi depth from another image at a discrepancy of around 35 percent. Application of the predictive model for TSS concentration to another image acquired at a time of different water types resulted in a discrepancy of 152 percent. Therefore, image calibration to like-values could be used to reliably map certain water quality parameters from multitemporal TM images so long as the water type under study remains unchanged. This method is limited in that the mapped results could be rather inaccurate if the water type under study has changed considerably. Thus, the approach needs to be refined in shallow water from multitemporal satellite imagery.

Ar-40/-Ar-39 geochronology at the Instituto de Geociencias, USP: instrumentation, analytical procedures, and calibration

Laser heating Ar-40/Ar-39 geochronology provides high analytical precision and accuracy, mum-scale spatial resolution. and statistically significant data sets for the study of geological and planetary processes, A newly commissioned Ar-40/Ar-39 laboratory at CPGeo/USP, Sao Paulo, Brazil, equips the Brazilian scientific community with a new powerful tool applicable to the study of geological and cosmochemical processes. Detailed information about laboratory layout, environmental conditions, and instrumentation provides the necessary parameters for the evaluation of the CPGeo/USp Ar-40/Ar-39 suitability to a diverse range of applications. Details about analytical procedures, including mineral separation, irradiation at the IPEN/CNEN reactor at USP, and mass spectrometric analysis enable potential researchers to design the necessary sampling and sample preparation program suitable to the objectives of their study. Finally, the results of calibration tests using Ca and K salts and glasses, international mineral standards, and in-house mineral standards show that the accuracy and precision obtained at the Ar-40/Ar-39 laboratory at CPGeo/USP are comparable to results obtained in the most respected laboratories internationally. The extensive calibration and standardization procedures under-taken ensure that the results of analytical studies carried out in our laboratories will gain immediate international credibility, enabling Brazilian students and scientists to conduct forefront research in earth and planetary sciences.

Methodologies for calibration and predictive analysis of a watershed model

The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.

Ground water model calibration using pilot points and regularization

Use of nonlinear parameter estimation techniques is now commonplace in ground water model calibration. However, there is still ample room for further development of these techniques in order to enable them to extract more information from calibration datasets, to more thoroughly explore the uncertainty associated with model predictions, and to make them easier to implement in various modeling contexts. This paper describes the use of pilot points as a methodology for spatial hydraulic property characterization. When used in conjunction with nonlinear parameter estimation software that incorporates advanced regularization functionality (such as PEST), use of pilot points can add a great deal of flexibility to the calibration process at the same time as it makes this process easier to implement. Pilot points can be used either as a substitute for zones of piecewise parameter uniformity, or in conjunction with such zones. In either case, they allow the disposition of areas of high and low hydraulic property value to be inferred through the calibration process, without the need for the modeler to guess the geometry of such areas prior to estimating the parameters that pertain to them. Pilot points and regularization can also be used as an adjunct to geostatistically based stochastic parameterization methods. Using the techniques described herein, a series of hydraulic property fields can be generated, all of which recognize the stochastic characterization of an area at the same time that they satisfy the constraints imposed on hydraulic property values by the need to ensure that model outputs match field measurements. Model predictions can then be made using all of these fields as a mechanism for exploring predictive uncertainty.

An advanced regularization methodology for use in watershed model calibration

A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.

The cost of uniqueness in groundwater model calibration

Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a Solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained. The cost of uniqueness is this: no matter which regularization methodology is employed, the inevitable consequence of its use is a loss of detail in the calibrated field. This, ill turn, can lead to erroneous predictions made by a model that is ostensibly well calibrated. Information made available as a by-product of the regularized inversion process allows the reasons for this loss of detail to be better understood. In particular, it is easily demonstrated that the estimated value for an hydraulic property at any point within a model domain is, in fact, a weighted average of the true hydraulic property over a much larger area. This averaging process causes loss of resolution in the estimated field. Where hydraulic conductivity is the hydraulic property being estimated, high averaging weights exist in areas that are strategically disposed with respect to measurement wells, while other areas may contribute very little to the estimated hydraulic conductivity at any point within the model domain, this possibly making the detection of hydraulic conductivity anomalies in these latter areas almost impossible. A study of the post-calibration parameter field covariance matrix allows further insights into the loss of system detail incurred through the calibration process to be gained. A comparison of pre- and post-calibration parameter covariance matrices shows that the latter often possess a much smaller spectral bandwidth than the former. It is also demonstrated that, as all inevitable consequence of the fact that a calibrated model cannot replicate every detail of the true system, model-to-measurement residuals can show a high degree of spatial correlation, a fact which must be taken into account when assessing these residuals either qualitatively, or quantitatively in the exploration of model predictive uncertainty. These principles are demonstrated using a synthetic case in which spatial parameter definition is based oil pilot points, and calibration is Implemented using both zones of piecewise constancy and constrained minimization regularization. (C) 2005 Elsevier Ltd. All rights reserved.

New calibration technique for multiple-component stress wave force balances

Force measurement in hypervelocity expansion tubes is not possible using conventional techniques. The stress wave force balance technique can be applied in expansion tubes to measure forces despite the short test times involved. This paper presents a new calibration technique for multiple-component stress wave force balances where an impulse response created using a load distribution is required and no orthogonal surfaces on the model exist.. This new technique relies on the tensorial superposition of single-component impulse responses analogous to the vectorial superposition of the calibration loads. The example presented here is that of a scale model of the Mars Pathfinder, but the technique is applicable to any geometry and may be useful for cases where orthogonal loads cannot be applied.

Improving wheat simulation capabilities in Australia from a cropping systems perspective - III. The integrated wheat model (I_WHEAT)

Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.

The relationship between plasma lactate parameters, W-peak and 1-h cycling performance in women

Purpose: The relationship between six descriptors of lactate increase, peak (V) over dot O-2,W-peak, and 1-h cycling performance were compared in 24 trained, female cyclists (peak (V) over dot O-2 = 48.11 +/- 6.32 mL . kg(-1) . min(-1)). Methods: The six descriptors of lactate increase were: 1) lactate threshold (LT; the power output at which plasma lactate concentration begins to increase above the resting level during an incremental exercise test), 2) LT1 (the power output at which plasma lactate increases by 1 mM or more), 3) LTD (the lactate threshold calculated by the D-max method), 4) LTMOD (the lactate threshold calculated by a modified D-max method), 5) L4 (the power output at which plasma lactate reaches a concentration of 4 mmol-L-1), and 6) LTLOG (the power output at which plasma lactate concentration begins to increase when the log([La-]) is plotted against the log (power output)). Subjects first completed a peak (V) over dot O-2 test on a cycle ergometer. Finger-tip capillary blood was sampled within 30 s of the end of each 3-min stage for analysis of plasma lactate. Endurance performance was assessed 7 d later using a 1-h cycle test (OHT) in which subjects were directed to achieve the highest possible average power output. Results: The mean power output (W) for the OHT (+/- SD) was 183.01 +/- 18.88, and for each lactate variable was: LT (138.54 +/- 46.61), LT1 (179.17 +/- 27.25), LTLOG (143.97 +/- 45.74), L4 (198.09 +/- 33.84), LTD (178.79 +/- 24.07), LTMOD (212.28 +/- 31.75). Average power output during the OHT was more strongly correlated with all plasma lactate parameters (0.61 < r < 0.84) and W-peak (r = 0.81) than with peak (V) over dot O-2 (r = 0.55). The six lactate parameters were strongly correlated with each other (0.54 < r < 0.91) and of the six lactate parameters, LTD correlated best with endurance performance (r = 0.84). Conclusions: It was concluded that plasma lactate parameters and W-peak provide better indices of endurance performance than peak (V) over dot O-2 and that, of the six descriptors of lactate increase measured in this study, LTD is most strongly related to 1-h cycling performance in trained, female cyclists.

Decoherence and fidelity in ion traps with fluctuating trap parameters

We consider two different kinds of fluctuations in an ion trap potential: external fluctuating electrical fields, which cause statistical movement (wobbling) of the ion relative to the center of the trap, and fluctuations of the spring constant, which an due to fluctuations of the ac component of the potential applied in the Paul trap for ions. We write down master equations for both cases and, averaging out the noise, obtain expressions for the heating of the ion. We compare our results to previous results for far-off resonance optical traps and heating in ion traps. The effect of fluctuating external electrical fields for a quantum gate operation (controlled-NOT) is determined and the fidelity for that operation derived. [S1050-2947(99)06005-9].

CXTANNEAL: an improved program for estimating solute transport parameters

CXTANNEAL is a program for analysing contaminant transport in soils. The code, written in Fortran 77, is a modified version of CXTFIT, a commonly used package for estimating solute transport parameters in soils. The improvement of the present code is that it includes simulated annealing as the optimization technique for curve fitting. Tests with hypothetical data show that CXTANNEAL performs better than the original code in searching for optimal parameter estimates. To reduce the computational time, a parallel version of CXTANNEAL (CXTANNEAL_P) was also developed. (C) 1999 Elsevier Science Ltd. All rights reserved.

The HI Parkes All Sky Survey: southern observations, calibration and robust imaging

The acquisition of HI Parkes All Shy Survey (HIPASS) southern sky data commenced at the Australia Telescope National Facility's Parkes 64-m telescope in 1997 February, and was completed in 2000 March. HIPASS is the deepest HI survey yet of the sky south of declination +2 degrees, and is sensitive to emission out to 170 h(75)(-1) Mpc. The characteristic root mean square noise in the survey images is 13.3 mJy. This paper describes the survey observations, which comprise 23 020 eight-degree scans of 9-min duration, and details the techniques used to calibrate and image the data. The processing algorithms are successfully designed to be statistically robust to the presence of interference signals, and are particular to imaging point (or nearly point) sources. Specifically, a major improvement in image quality is obtained by designing a median-gridding algorithm which uses the median estimator in place of the mean estimator.

Physiologic parameters that affect pulse transit time difference between the upper and lower limbs in children

Pulse wave velocity (PWV) is a known parameter that is related to arterial distensibility. However, its potential is hampered by the absence of appropriate techniques to estimate it noninvasively. PWV can be used as an assessment of increased arterial stiffness that is linked to systolic hypertension, excess cardiovascular morbidity and mortality.(1,2)