Assess Model Accuracy Research Articles

Application of Vacuum–Insulated Tubing to Mitigate Annular Pressure Buildup

Summary Vacuum-insulated tubing (VIT) has been used successfully to mitigate the potentially harmful effects of annular pressure buildup (APB). In a recent deepwater installation, the subject well had lost alternate APB mitigation capability through a series of events. VIT was then chosen as the only viable technology. A common design companion of VIT is gelled brine, chosen to decrease annular natural convection driven by heat loss around the VIT connections. There are, however, several drawbacks to the indiscriminate use of gelled brine: Tight clearances around the tubing hanger running tool, creating the potential for debris plugging and/or tool-recovery issues from the subsea wellhead. Limitations imposed by VIT collapse and hydrostatic packer setting pressures. Unknown temperature/viscosity response and associated quality-control requirements for displacement through a subsea wellhead. A need to reduce operational time and cost. These issues led to the consideration of alternative means of controlling natural convection, and an effort was made to understand, improve, and deploy external coupling insulators. An in-ground vertical experiment with two connected joints of VIT was conducted with and without coupling insulators. Temperatures were monitored at multiple locations. Test results confirm the effectiveness of external coupling insulators. Several theoretical models using different numerical techniques (finite difference, lumped mass/resistance, finite element, and computational fluid dynamics) were found to be consistent with experimental results. These were compared with critical APB temperatures calculated with a commercial wellbore simulator. The net result of these studies was to adopt the external insulators. This paper reviews the experimental data and presents several models of a vertically aligned VIT in a deepwater completion. A comparison of thermally effective APB solutions is presented, together with a critical assessment of modeling and experimental accuracy.

Natural Landscape and Stream Segment Attributes Influencing the Distribution and Relative Abundance of Riverine Smallmouth Bass in Missouri

AbstractProtecting and restoring fish populations on a regional basis are most effective if the multiscale factors responsible for the relative quality of a fishery are known. We spatially linked Missouri's statewide historical fish collections to environmental features in a geographic information system, which was used as a basis for modeling the importance of landscape and stream segment features in supporting a population of smallmouth bass Micropterus dolomieu. Decision tree analyses were used to develop probability‐based models to predict statewide occurrence and within‐range relative abundances. We were able to identify the range of smallmouth bass throughout Missouri and the probability of occurrence within that range by using a few broad landscape variables: the percentage of coarse‐textured soils in the watershed, watershed relief, and the percentage of soils with low permeability in the watershed. The within‐range relative abundance model included both landscape and stream segment variables. As with the statewide probability of occurrence model, soil permeability was particularly significant. The predicted relative abundance of smallmouth bass in stream segments containing low percentages of permeable soils was further influenced by channel gradient, stream size, spring‐flow volume, and local slope. Assessment of model accuracy with an independent data set showed good concordance. A conceptual framework involving naturally occurring factors that affect smallmouth bass potential is presented as a comparative model for assessing transferability to other geographic areas and for studying potential land use and biotic effects. We also identify the benefits, caveats, and data requirements necessary to improve predictions and promote ecological understanding.

On the effectiveness of assessing model accuracy at design points for radial basis functions

AbstractA study is performed on the effectiveness of assessing accuracies of radial basis functions (RBFs) at design (or sampling) points. The RBF has been shown to be appropriate for creating approximation functions for linear, quadratic, and higher‐order nonlinear responses even with a relatively small size of design samples. One favourable feature of RBFs is that all RBF models pass exactly through design points; therefore, an RBF model has no error at design points. However, this feature prevents the use of statistical parameters, which are commonly used in polynomial‐regression approximations, to obtain model accuracy based on evaluations at design points. Since obtaining additional samples for many complex engineering applications is expensive, it is desirable to have some knowledge of the model accuracy based on evaluations at design points so that the best RBF model(s) can be selected. In this study, the effectiveness of using statistical parameter R2 for prediction (R) is evaluated for two highly accurate RBFs using mathematical functions and real engineering applications. The results show that R is inappropriate for RBF models, and should be used cautiously for highly nonlinear responses with a small number of sampling points and/or a large number of design variables. Copyright © 2006 John Wiley & Sons, Ltd.

Spatio‐temporal co‐occurrence of cougars (Felis concolor), wolves (Canis lupus) and their prey during winter: a comparison of two analytical methods

AbstractAims To examine the spatio‐temporal co‐occurrence of cougars (Felis concolor), wolves (Canis lupus), and their prey during winter using monthly (November–March) species–environment relationship models. In addition, to contrast predictions across two methods: logistic regression and Geographic Information System (GIS) image correlation.Location The eastern front ranges of the Canadian Rocky Mountains (south‐central Alberta), approximately 100 km west of Calgary, including portions of Banff National Park and Kananaskis Country.Methods Snow‐tracking data were collected simultaneously for cougars, wolves, elk (Cervus elaphus), and deer (Odocoileus virginianus and O. hemionus) between November and March, 1997–2000. Track data were synthesized in a GIS. Logistic regression and Akaike's information criterion (AIC) were used to select optimal environmental relationship models for each species. We first examined co‐occurrence by iteratively using each species as a dependent variable (presence/absence) in a logistic regression analysis and using all other species track‐density estimates as independent variables. We built predictive surfaces in a GIS using the exponent form of the logistic regression models, and assessed model accuracy with a receiver operating characteristic curve. We then re‐examined co‐occurrence using pairwise correlations of species probability surfaces by month. The correlation results were compared with logistic regression results to illuminate mechanisms of co‐occurrence and to investigate predictive consistency across the two methods.Results Cougars showed a trend in distribution from higher elevation and less rugged terrain in December, to lower elevation and more rugged terrain in March. This trend differed from that for wolves, which showed a more stable affinity for low elevation and less rugged valley bottoms across all months. The logistic regression models indicated variable positive and negative associations of cougars with wolves by month, and changes in prey associations over time. Notably, there was a shift in co‐occurrence for both predators from elk to deer in March. We found high predictive accuracy for all probability surfaces, except for the month of January. Our image comparison showed that spatial co‐occurrence amongst all species increased over winter, except that wolves and cougars were negatively correlated in February. Combining the results of each approach we found that cougars and wolves converged spatially over winter at the landscape scale (i.e. the valley), while showing more discrete use of that space over time and by habitat attributes (e.g. forest cover, topographic complexity, and prey track density).Main conclusions In the Rocky Mountains, the spatial distributions of cougars and wolves converged into the valley floor as winter progressed. Cougars were distinct from wolves and prey in the intensity of this shift. We determined that a comparison of predictive surfaces alone fails to explain species co‐occurrence. The surfaces must be coupled with investigation of respective species–environment models to account for temporal changes in associations. We suggest that the two approaches represent different ecological scales: image comparison may be best for landscape‐ (valley) level analysis, while logistic regression is best for site‐level analysis. Ultimately, both approaches were critical to our analysis. Finally, the variability observed over time suggested that annual and seasonal models may obscure important ecological patterns and processes, especially for cougars.

Digital elevation model (DEM) generation and accuracy assessment from ASTER stereo data

Digital elevation models (DEM) are the indispensable quantitative environmental variable in most of the research studies in remote sensing. The improvement of sensor and satellite imaging technologies enabled the researchers to generate DEM using remotely sensed data. These data can be started to use as not only the two-dimensional (2-D) but also three-dimensional (3-D) information sources with usage of the DEM. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is one of the sensor systems capable of DEM generation and during the study, ASTER level 1A (L1A) data were used. Due to presence of many geological features and different landcover types, the test site is selected as the watershed of Asarsuyu River, located in north-western Anatolia in between Duzce and Bolu plains. The aim of this study is to check the best effort of 15 m spatial resolution DEM generation from ASTER L1A data by collecting different numbers of ground control points (GCP) (30, 45, and 60) and tie points (TP). During the study, three different techniques—spatial correlation, image differencing and profiling—were used for both planimetric and vertical accuracy assessment. The obtained results from both of the techniques show that the accuracy of the DEM increases by increasing the number of GCP. However, there is an only slight difference between the result of 45 GCPs and 60 GCPs.

Current practices in building project contract price forecasting in the UK

PurposeThe selection and use of the most appropriate building project contract price forecasting model contribute to the provision of strategic advice that clients can use to make value‐for‐money business decisions. This work seeks to provide a snapshot of current practice in model selection by practitioners based in large‐sized quantity surveying, project management and multi‐disciplinary practices based in the UK.Design/methodology/approachA quantitative research design was used to capture data from a sample of 300 such organisations in 2004. An initial and follow‐up administration of the postal survey generated an overall response of 54 per cent.FindingsThe findings of the study revealed that the traditional types of forecasting model continue to be in widespread use irrespective of organisational type. Lifecycle cost models and in‐house knowledge‐based systems were also found to be in use, but not on such a widespread scale. Newly developed models such as artificial neural nets, fuzzy logic nets, as well as environmental and sustainability cost models were found, as yet, to have only very limited application in practice. Practitioner assessment of model accuracy and value in‐use provided statistically insignificant levels of variance between the organisational types and the models found to be in use.Research limitations/implicationsThe work is limited due to the size of the sample frame and the measuring instrument used which could not uncover reasons for the selection of particular types of models.Originality/valueThe outcomes of the work provide benchmarks that can be used to evaluate organisational approach and future research. The paper contributes to the body of knowledge available on the process of building project contract price forecasting that is fundamental to the assessment of project value.

A novel hysteresis model in unsaturated soil

This study presents a novel hysteresis model based on van Genuchten's soil-moisture relationships. The proposed model yields a series of closed-form relationships in which two shape factors α and η are determined from the main drying and wetting curves. Experimental and literature-cited data were used to assess model accuracy. The proposed model was also compared with the Scott and KP models. Analytical results indicate that the present model is simple, accurate and effective in constructing the series of wetting and drying scanning curves. Notably, the proposed model outperforms the Scott and KP models in terms of model accuracy. Moreover, the novel model eliminates the pumping effect and has perfect closure at scanning curve reversal points. Copyright © 2004 John Wiley & Sons, Ltd.

Modelling culvert construction in artificially frozen ground using finite element analysis

This paper describes the development of a computer finite element method (FEM) model for simulating the temporary earthwork support technique, artificial ground freezing. Specifically, ice‐wall thickness growth and ground movement (due to frost heave and thaw settlement) were evaluated with the use of the finite element software package ABAQUS. Other parameters modelled were obtained from a combination of a priori research and invaluable practitioner experience. Simulation results were then compared with measurements obtained from a live field project to assess model accuracy. Output results obtained from the FEM analyses provided demonstrable evidence of the model’s inherent ability to simulate “realistically” the effects of ground freezing analysis process.

CONSTRAINTS ON THE ESTABLISHMENT OF PLANTS ALONG A FLUCTUATING WATER-DEPTH GRADIENT

We used simulation modeling to investigate the relative importance of current environmental conditions and factors affecting establishment of different plant species on the formation of vegetative zonation patterns. We compared the results from a series of six models that incorporated increasing amounts of information about key factors affecting species' ability to adjust to water-level fluctuations. We assessed model accuracy using aerial photographs taken of a 10-yr field experiment, in which 10 wetlands were flooded to 1 m above normal water level for 2 yr, drawn down for 1 or 2 yr, and reflooded for 5 yr to three different water levels (normal, +0.3 m, +0.6 m). We compared each model's ability to predict relative areal cover of five dominant emergent species and to recreate the spatial structure of the landscape as measured by mean area of monospecific stands of vegetation and the degree to which the species were intermixed. The simplest model predicted post-treatment species distributions using logistic regressions based on initial species distributions along the water-depth gradient in the experimental wetlands. Subsequent models were based on germination, rhizomatous dispersal, and mortality functions implemented in each cell of a spatial grid. We tested the effect on model accuracy of incrementally adding data on five factors that can alter the composition and distribution of vegetative zones following a shift in environmental conditions: (1) spatial relationships between areas of suitable habitat (landscape geometry), (2) initial spatial distribution of adults, (3) the presence of ruderal species in the seed bank, (4) the distribution of seed densities in the seed bank, and (5) differential seedling survivorship. Because replicated, long-term data are generally not available, the evaluation of these models represents the first experimental test, of which we are aware, of the ability of a cellular-automaton-type model to predict changes in plant species' distributions. Establishment constraints, such as recruitment from the seed bank, were most important during low-water periods and immediately following a change in water depth. Subsequent to a drop in water level, the most detailed models made the most accurate predictions. The accuracy of all the models converged in 1–2 years after an increase in water level, indicating that current environmental conditions became more important under stable conditions than the effects of historical recruitment events.

Constraints on the Establishment of Plants along a Fluctuating Water-Depth Gradient

We used simulation modeling to investigate the relative importance of current environmental conditions and factors affecting establishment of different plant species on the formation of vegetative zonation patterns. We compared the results from a series of six models that incorporated increasing amounts of information about key factors affecting species' ability to adjust to water-level fluctuations. We assessed model accuracy using aerial photographs taken of a 10-yr field experiment, in which 10 wetlands were flooded to 1 m above normal water level for 2 yr, drawn down for 1 or 2 yr, and reflooded for 5 yr to three different water levels (normal, +0.3 m, +0.6 m). We compared each model's ability to predict relative areal cover of five dominant emergent species and to recreate the spatial structure of the landscape as measured by mean area of monospecific stands of vegetation and the degree to which the species were intermixed. The simplest model predicted post-treatment species distributions using logistic regressions based on initial species distributions along the water-depth gradient in the experimental wetlands. Subsequent models were based on germination, rhizomatous dispersal, and mortality functions implemented in each cell of a spatial grid. We tested the effect on model accuracy of incrementally adding data on five factors that can alter the composition and distribution of vegetative zones following a shift in environmental conditions: (1) spatial relationships between areas of suitable habitat (landscape geometry), (2) initial spatial distribution of adults, (3) the presence of ruderal species in the seed bank, (4) the distribution of seed densities in the seed bank, and (5) differential seedling survivorship. Because replicated, long-term data are generally not available, the evaluation of these models represents the first experimental test, of which we are aware, of the ability of a cellular-automaton-type model to predict changes in plant species' distributions. Establishment constraints, such as recruitment from the seed bank, were most important during low-water periods and immediately following a change in water depth. Subsequent to a drop in water level, the most detailed models made the most accurate predictions. The accuracy of all the models converged in 1–2 years after an increase in water level, indicating that current environmental conditions became more important under stable conditions than the effects of historical recruitment events.

Soil moisture in a regional climate model: Simulation and projection

Regional climate simulations driven by three sets of initial and lateral boundary conditions—analyzed observations, GCM control climate, and GCM enhanced greenhouse‐gas scenario climate—are used to assess model accuracy in predicting soil moisture and to examine changes in soil moisture in the scenario climate. Simulated soil moisture does not show noticeable drift during the 10‐year simulations. Observed and simulated soil moisture for Illinois and Iowa correspond reasonably well for the top 10 cm soil layer but a consistent low bias is present in the top 1 m. Growing season depletion of soil water is simulated well but recharge after growing season is slower than observed, at least in part due to underprediction of precipitation in autumn. This suggests that improvements in simulating soil moisture depend greatly on improvements in simulating precipitation. The climate change scenario produces drier soil in the top 10 cm during winter but wetter top soil in warm seasons because of greater precipitation, while top l m soil is wetter in all seasons.

Performance of three infiltration models under surge irrigation

Three models were developed to predict infiltration under a surge-flow irrigation regime. One model (2P) utilized the Kostiakov-Lewis infiltration equation. The other two models (2PF and 3P) utilized the modified Kostiakov-Lewis infiltration equation. All three models combined continuous-flow furrow irrigation volume-balance hydraulic models presented by Reddell and Latortue (1986, 1988) with a numerical variation of the Cycle Ratio-Time Model (CRTM) for surge irrigation presented by Blair and Smerdon (1987). The volume–balance component of the models estimated the soil's continuous-flow furrow irrigation infiltration function using first surge-cycle advance data. The numerical CRTM component used the estimated infiltration function in conjunction with the surge-flow irrigation infiltration opportunity-time to predict infiltration. An assessment of overall model accuracy was based upon an infiltrated volume root mean square error (RMSE) statistic. Overall, the 2PF model returned the lowest RMSE values and the 3P model was the next most accurate. The 2P model was the least accurate. While the 2PF model was the most accurate, this model has limited applicability since it requires inflow and outflow measurements throughout an irrigation event to evaluate the soil's basic infiltration constant. Despite its good overall performance, anomalous results from the 3P model suggest that further testing is needed. Although the 2P model was the least accurate of the three models evaluated here, and although it consistently underpredicted infiltration, it appears to be the most stable and effective of the three models evaluated.

Accuracy of software quality models over multiple releases

Many evolving missiondcritical systems must have high software reliability. However, it is often difficult to identify faultdprone modules early enough in a development cycle to guide software enhancement efforts effectively and efficiently. Software quality models can yield timely predictions of membership in the faultdprone class on a moduledbydmodule basis, enabling one to target enhancement techniques. However, it is an open empirical question, “Can a software quality model remain useful over several releasesq” Most prior software quality studies have examined only one release of a system, evaluating the model with modules from the same release. We conducted a case study of a large legacy telecommunications system where measurements on one software release were used to build models, and three subsequent releases of the same system were used to evaluate model accuracy. This is a realistic assessment of model accuracy, closely simulating actual use of a software quality model. A module was considered faultdprone if any of its faults were discovered by customers. These faults are extremely expensive due to consequent loss of service and emergency repair efforts. We found that the model maintained useful accuracy over several releases. These findings are initial empirical evidence that software quality models can remain useful as a system is maintained by a stable software development process.

A numerical study of the composite surface model for ocean backscattering

A numerical study of 14-GHz backscattering from ocean-like surfaces, described by a Pierson-Moskowitz spectrum, is presented. Surfaces rough in one and two dimensions are investigated, with Monte Carlo simulations performed efficiently through the use of the canonical-grid expansion in an iterative method of moments. Backscattering cross sections are illustrated for perfectly conducting surfaces at angles from 0 to 60/spl deg/ from normal incidence, and the efficiency of the numerical model enables the composite surface theory to be studied in the microwave frequency range for realistic one-dimensional (1D) surface profiles at low wind speeds (3 m/s). Variations with surface spectrum low-frequency cutoff (ranging over spatial lengths from 21.9 to 4.29 cm) are investigated to obtain an assessment of composite surface model accuracy. The 1D surface results show an increase in hh backscatter returns as surface low-frequency content is increased for incidence angles larger than 30/spl deg/, while /spl nu//spl nu/ returns remain relatively constant, all as predicted by the composite surface model. Similar results are obtained for surfaces rough in two dimensions, although the increased computational complexity allows maximum surface sizes of only 1.37 m to be considered. In addition, cross-polarized cross sections are studied in the two-dimensional (2D) surface case and again found to increase as surface low-frequency content is increased. For both 1D and 2D surfaces, backscattering cross sections within 20/spl deg/ of normal incidence are found to be well matched by both Monte Carlo and analytical physical optics (PO) methods for all low-frequency cutoffs considered, and a comparison of analytical PO and geometrical optics (GO) results indicates an appropriate choice of the cutoff wavenumber in the composite surface model to insure an accurate slope variance for use in GO predictions. This choice of cutoff wavenumber is then applied in the composite surface theory for more realistic ocean spectra and compared with available experimental data.

Numerical Simulation of Widening and Bed Deformation of Straight Sand-Bed Rivers. II: Model Evaluation

In this paper the numerical model presented in the companion paper is tested and applied. Assessment of model accuracy was based on two approaches. First, predictions of evolution of a 13.5 km reach of the South Fork of the Forked Deer River, in west Tennessee, were compared to observations over a 24-yr period. Results suggest that although the model was able to qualitatively predict trends of widening and deepening, quantitative predictions were not reliable. Simulated widths and depths were within 15% of the corresponding observed values, but observed change in these parameters at the study sites were also close to these values. Simulated rates of depth adjustment were within 15% of observed rates, but observed rates of channel widening at the study sites were approximately three times those simulated by the model. In the second approach, the model was used to generate relationships between stable channel width and bank-full discharge. The model was able to successfully replicate the form of empirically...

Finite state aeroelastic model for use in rotor design optimization

In this article, a rotor aeroelastic model based on a newly developed finite state dynamic wake, coupled with blade finite element analysis, is described. The analysis is intended for application in rotor blade design optimization. A coupled simultaneous system of differential equations combining blade structural dynamics and aerodynamics is established in a formulation well-suited for design sensitivity computation. Each blade is assumed to be an elastic beam undergoing flap bending, lead-lag bending, elastic twist, and axial deflections. Aerodynamic loads are computed from unsteady blade element theory where the rotor three-dimensional unsteady wake is described by a generalized dynamic wake model. Correlation of results obtained from the analysis with flight test data is provided to assess model accuracy.

Assessment of modeling and discretization accuracy for high-speed afterbody flows

The accuracy of Reynolds-aver aged Navier-Stokes calculations of axisymmetric high-speed afterbody flows is investigated. An approximate truncation error analysis is used to identify specific regions where discretization errors are large, and grid refinement is used to evaluate global solution accuracy. Good alignment of grid lines with streamlines in the shear layer at the nozzle exit is found to be important for obtaining solutions at high nozzle pressure ratios. Solution-adapted grids are used, and solutions that are essentially grid-independent are obtained. Modifications to the k- model for Mach number and streamline curvature effects are presented and validated in flows unrelated to base flows. In base flow calculations, these model modifications produce changes hi base drag in excess of 20%. Computed solutions agree well with experiment for base pressure and flow structure.

Modeling folded dipoles and feedlines for radiation and scattering

Dipole-like antennas, suited for use as radiating elements in large phased arrays, are modeled for efficient analysis by decomposing the antenna into a radiating mode part and a transmission line mode part. All the essential features of folded dipoles, integrated balun feedlines, and feedline scattering are contained in the models. Feedline scattering, in particular, is an important consideration in analyzing phased arrays. The models are suited for moment-method analysis of arrays of such antennas, because the models entail simplified radiation mode parts. Extensive results of exercising the models were obtained for assessing model accuracy. Agreement between full-moment-method analyses and combined-mode analyses was reasonably good. >

Computer simulation in physical geography

Introduction: Getting Started: What is a Model in Physical Geography?, Writing a Computer Simulation Model Black Box Models: The Structure of Systems, Regression and Schematic Models Process Models: Prediction of Runoff, Ecological Models Mass and Energy Balance Models: Models with no Storage, Linear Multi-store Models Stochastic Models: Kinematic Waves for Gravel Bed-load, Channel Network Simulations, Other Examples Model Formulation and Construction: Defining an Algorithm, Flow Diagram, Input and Output Design Model Calibration and Verification: Assessing Model Accuracy, Data Requirements for Modelling Alternative Modelling Styles: Choice of System of Interest, More Complex Models.

Verification studies of entrained-flow gasification and combustion systems with the simmer-II code

A series of code verification studies on entrained-flow phenomena is described. Calculations of turbulent gas/particle flow in free jets and confined reactor geometries are compared to relevant experimental data and analytic solutions to assess model accuracy and to identify numerical limitations.