Standard Input Data Research Articles

The self-organising map learning algorithm with inactive and relative winning frequency of active neurons

The self-organizing map (SOM) is applied to data clustering, image analysis, dimension reduction and so forth. During the study of conventional SOM, we identified active and inactive neurons on the map. But the conventional SOM treats all the neurons on the map as active neurons and does learning accordingly. Also, the conventional SOM does not consider the relative winning frequency of active neurons. In this paper, a modified SOM is being proposed, which divides the neurons into active and inactive groups and different learning processes are used for active and inactive neurons. The modified SOM considers the relative winning frequency of active neurons also. The learning efficiency is measured using three well-known parameters. The modified SOM is applied on various standard input data sets. The learning results of the modified SOM are better than that of the conventional SOM. It is observed that the modified SOM is able to obtain the effective map reflecting the distribution of the input data.

A Comparison of Wind Flow Models for Wind Resource Assessment in Wind Energy Applications

The objective of this work was to assess the accuracy of various coupled mesoscale-microscale wind flow modeling methodologies for wind energy applications. This is achieved by examining and comparing mean wind speeds from several wind flow modeling methodologies with observational measurements from several 50 m met towers distributed across the study area. At the mesoscale level, with a 5 km resolution, two scenarios are examined based on the Mesoscale Compressible Community Model (MC2) model: the Canadian Wind Energy Atlas (CWEA) scenario, which is based on standard input data, and the CWEA High Definition (CWEAHD) scenario where high resolution land cover input data is used. A downscaling of the obtained mesoscale wind climate to the microscale level is then performed, where two linear microscale models, i.e., MsMicro and the Wind Atlas Analysis and Application Program (WAsP), are evaluated following three downscaling scenarios: CWEA-WAsP, CWEA-MsMicro and CWEAHD-MsMicro. Results show that, for the territory studied, with a modeling approach based on the MC2 and MsMicro models, also known as Wind Energy Simulation Toolkit (WEST), the use of high resolution land cover and topography data at the mesoscale level helps reduce modeling errors for both the mesoscale and microscale models, albeit only marginally. At the microscale level, results show that the MC2-WAsP modeling approach gave substantially better results than both MC2 and MsMicro modeling approaches due to tweaked meso-micro coupling.

Evaluation of evaporation estimation methods for a covered reservoir in a semi-arid climate (south-eastern Spain)

Summary The main purpose of this study was to evaluate different methods of evaporation estimation for covered water reservoirs. A reservoir equipped with a suspended cover was fully monitored to register the evaporation rate and microclimate below the cover. The datasets were used to evaluate the performance of commonly used evaporation methods, namely energy budget, mass-transfer, combination (Penman and FAO-56 Penman–Monteith) and floating class-A pan. The mass-transfer formula based on the Sherwood number proposed for free convection conditions, which were observed to prevail below the cover, supplied reasonably good estimates of covered reservoir evaporation and it is a good option from a practical point of view, with low input data requirements. Detailed input data and modifications in the calculation of energy fluxes are required to get good evaporation estimations of covered surfaces with the energy budget and FAO-56 Penman–Monteith methods. Besides, some of the standard meteorological input data (such as wind speed at 2 m height) cannot be registered below the cover. Penman equation presented a poor performance related to the overestimation of the advective component for free convection conditions. The pan evaporation was found to be substantially higher than the reservoir evaporation, due to the particular characteristics of the tank, that increased surface temperature and hence evaporation rate. A simplified empirical mass-transfer formula was also proposed to estimate evaporation of covered water bodies from the only knowledge of the surface-to-air mixing ratio gradient.

Effects of climatic data low-pass filtering on the ICBM temperature- and moisture-based soil biological activity factors in a cool and humid climate

The air temperature ( T air ), total precipitation (TP) and potential evapotranspiration (PET) are standard input data for soil carbon dynamic models, i.e., for calculating temperature and moisture effects on soil biological activity. The resolution needed depends on objectives, the complexity of models and inbuilt pedotransfer functions. The Introductory Carbon Balance Model (ICBM) soil climate front end model calculates a multiplicative soil-temperature ( r e_temp ) and -moisture ( r e_wat ) factor with a daily time-step to estimate soil biological activity, i.e., r e_crop = r e_temp × r e_wat . Our objective was to determine how much r e_temp , r e_wat and r e_crop are affected by low-pass filtering of the climatic input data for a cool, humid temperate region. To achieve this we conducted spectral analysis on T air , TP, PET and r e_crop in the frequency domain. Thereafter we applied Fourier low-pass filters of 5, 15, 30, 60 and 180 days on T air , TP, PET and tracked their effects through the soil climate model's state variables and outputs. This was done using a sandy and a heavy clay soil and an 89-year daily time-series from a meteorological station in Quebec (Canada). The Fourier spectra showed that the variance for T air , PET and r e_crop was dominated by an annual cycle, as could be expected. There was no yearly cycle for TP. The variation in r e_temp explained most of the variance in r e_crop . The soil climate module outputs were not sensitive to low-pass filtering of PET. A daily time-step was needed to avoid overestimating r e_crop for the sandy soil. Using a weekly time-step for TP and T air allowed us to explain about 80% of the variance in r e_crop for the heavy clay soil. This study also indicates that the standard leaf (and green) area index functions for calculating transpiration should receive more attention, since they have significant effects on the state and output variables.

A data envelopment analysis model with discretionary and non-discretionary factors in fuzzy environments

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision-making units (DMUs) that use multiple inputs to produce multiple outputs. The standard DEA models assume that all inputs and outputs are crisp and can be changed at the discretion of management. While crisp input and output data are fundamentally indispensable in the standard DEA evaluation process, input and output data in real-world problems are often imprecise or ambiguous. In addition, real-world problems may also include non-discretionary factors that are beyond the control of a DMU's management. Fuzzy logic and fuzzy sets are widely used to represent ambiguous, uncertain or imprecise data in DEA by formalising the inaccuracies inherent in human decision-making. In this paper, we show that considering bounded factors in DEA models results in a disregard to the concept of relative efficiency since the efficiency of the DMUs are calculated by comparing the DMUs with their lower and/or upper bounds. In addition, we present a fuzzy DEA model with discretionary and non-discretionary factors in both the input and output-oriented CCR models. A numerical example is used to demonstrate the applicability and the efficacy of the proposed models.

Modeled sensitivity of upper thermocline properties to tropical cyclone winds and possible feedbacks on the Hadley circulation

The sensitivity of upper thermocline properties, and global climate, to tropical cyclone (TC) winds is examined using global ocean and atmosphere general circulation models. We combine seven years of global, satellite‐based TC wind records with a standard surface wind input data set derived from reanalysis, and we apply idealized factors to TC winds in order to model the ocean's equilibrium response to increases in TC intensities. We find TC‐induced vertical ocean mixing impacts upper thermocline properties, such as temperature and mixed layer depth, and the effects are amplified for increasing intensities. The model's ocean heat transport is also affected, but only when TC winds are increased substantially compared to present‐day values. Atmospheric model simulations show altered ocean temperature can lead to changes in the mean Hadley circulation. Results suggest increased TC activity may affect global climate by altering the ocean's thermal structure, which could be important for large scale ocean‐atmosphere feedbacks.

Standard input data for FEM–MBS coupling: importing alternative model reduction methods into SIMPACK

Various research areas in the field of vehicle modelling, structural mechanics, engine dynamics, microelectromechanical systems (MEMS), etc. require the utilization of both multibody system formalism (MBS) and finite element method (FEM) in order to sufficiently capture the model's dynamics. The FEM–MBS coupling is accomplished by reducing the dimension of the FE-modelled part and then importing it into an MBS-code for further simulation. When using commercial FEM (Nastran, ANSYS, etc.) as well as MBS (SIMPACK) software packages the necessary standard input data (SID) file is needed for the coupling procedure (FEMBS interface). A problem arises by the restriction that both commercial FEM and MBS codes support only two condensation methods (Guyan reduction and component mode synthesis (CMS)), thus disabling the direct application of any other reduction approach (e.g. from the field of control theory) that actually could be better. In this article, the theoretical background of an implemented FEM–MBS interface (MORPACK) is presented allowing the application of any kind of reduction method for FE-modelled structures and furthermore their import (Ritz approximation) into SIMPACK via the SID file generation. A benchmark problem (UIC60-rail) is used in order to capture in SIMPACK the discrepancy between the standardized CMS and the Krylov subspace method (KSM), as one of the alternatives offered by the interface.

Automated thermotectonostratigraphic basin reconstruction: Viking Graben case study

We present a generic algorithm for automating sedimentary basin reconstruction. Automation is achieved through the coupling of a two-dimensional thermotectonostratigraphic forward model to an inverse scheme that updates the model parameters until the input stratigraphy is fitted to a desired accuracy. The forward model solves for lithospheric thinning, flexural isostasy, sediment deposition, and transient heat flow. The inverse model updates the crustal- and mantle-thinning factors and paleowater depth. Both models combined allow for automated forward modeling of the structural and thermal evolution of extensional sedimentary basins. The potential and robustness of this method is demonstrated through a reconstruction case study of the northern Viking Graben in the North Sea. This reconstruction fits present stratigraphy, borehole temperatures, vitrinite reflectance data, and paleowater depth. The predictive power of the model is illustrated through the successful identification of possible targets along the transect, where the principal source rocks are in the oil and gas windows. These locations coincide well with known oil and gas occurrences. The key benefits of the presented algorithm are as follows: (1) only standard input data are required, (2) crustal- and mantle-thinning factors and paleowater depth are automatically computed, and (3) sedimentary basin reconstruction is greatly facilitated and can thus be more easily integrated into basin analysis and exploration risk assessment.

Model FORRUS: Exploratory interactive analysis of spatio‐temporal forecasting data for evaluation forest biodiversity

This work attempts to bridge the gap between the research work done on developing the framework for measuring the sustainability of forest management and the lack of similar work on developing criteria and indicators (C&I) as a formal part of the planning system. We combine the forest ecosystem model FORRUS‐S and an analytical module for interactive visualization to analyze the spatial and temporal forecasting data and to examine those forest parameters that are related to the evaluation of forest biodiversity. The computer program package FORRUS‐S (Chumachenko et al., 2003), which has been developed for the simulation modeling of forest ecosystems dynamics, consists of a model of the natural development of a multi‐species, uneven‐aged stand, a model of exogenous influence (including silvi‐cultural activities) and a set of accessory programs (standard GIS, reference databases, modules recording input and output information, analytical module, 3D visualization module, etc.). The model utilizes the standard input data that have traditionally been used in Russian forestry research/management (Ed‐ confirm which is more accurate and delete the other) and that are available for virtually the entire Russian territory. The paper describes the results of computational experiments under different forest management scenarios (natural development, legal forestry, and forest practice with infringements) over 100 years. We discuss the results of forecast using a sample forest stand located in the Moscow region. The case study shows that FORRUS‐S, in combination with visualization and analysis of forecasting data, is an effective tool both for selecting sets of forest biodiversity indicators at the local level and for their eventual prioritization. This modelling approach is highly transparent, easy to understand, and offers a convenient environment for participatory decision making by forest managers.

A combined CFD–HAM approach for wind-driven rain on building facades

Numerical heat–air–moisture (HAM) transfer models are increasingly being used to study the hygrothermal performance and the durability of building facades. One of the most important boundary conditions for HAM simulations is wind-driven rain (WDR). Due to the complexity of WDR, however, the current HAM models generally incorporate it in a very simplified way. Recent research has shown that CFD can provide quite accurate estimates of the spatial and temporal distribution of WDR on building facades. Therefore, in this paper, a combined CFD–HAM approach is presented. It consists of implementing catch-ratio charts resulting from CFD simulations into the HAM model. Within the model, these charts are used to convert the standard meteorological input data (wind speed, wind direction and horizontal rainfall intensity) into WDR distribution records that are used as boundary condition for the actual HAM simulations. The combined approach is demonstrated for a simplified wall model. It is shown that the accuracy of the HAM-simulation results is to a large extent determined by the time resolution of the meteorological input data and by the data-averaging technique used for these data. Some important guidelines for accurate HAM analyses with WDR are provided.

Simulation modelling of long-term stand dynamics at different scenarios of forest management for coniferous–broad-leaved forests

The computer program package FORRUS-S (FORest of RUSsia—Stand) has been developed for simulation modelling of forest ecosystems dynamics. The program package FORRUS-S consists of the model of natural development of multispecies uneven-aged stand, the model of exogenous influence (including sylvicultural activities) and a set of accessory programs (standard GIS, reference databases, modules recoding input and output information, etc.). The available to date set of reference databases allows forecasting of stand dynamics in the zone of mixed coniferous–broad-leaved forests in European Russia. Since within this zone photosynthetic active radiation (PAR) is the main limiting factor, it is recalculated at each step while other factors as soil richness and humidity are considered constant throughout the modelling cycle. Modelling is performed for each cohort separately, i.e. a group of individuals of same species and ontogenetic state. Each cohort is described by a set of biological parameters stored in specially compiled reference databases (biometrics of tree crown, demand for light, gaps in the canopy, crown transparency to light, seed dispersal distance, sprouting ability, growth tables, potential stand quality index, etc.). Growth increment, thinning and natural regeneration are modelled with the step equal to 5 years. The model utilizes the principle of subdivision of the space into discrete three-dimensional elements. This approach makes it possible to consider the available PAR in the zone of active growth in a tree crown, and also to take into account spatial heterogeneity of growth conditions such as relief and soil characteristics. Modelling area can be up to several thousands of hectares. A number of external modules simulating sylvicultural measures can be enabled or disabled at any modelling step. FORRUS-S allows modelling of various scenarios of sylvicultural activity including: (1) natural stand development, (2) complete cycles of sylvicultural measures according to the current regulations and specifications of Russian Forest Service, (3) with infringement of technology specifications (heavy upper thinning and removing the best trees, clear cutting with destroying natural regeneration without planting). A set of tools was developed for analysis of various output databases and forecasted maps produced by means of GIS-technology. Model utilizes the standard input data have traditionally been using in forestry of the Russian Federation (taxation site descriptions, forest stand maps) and available for virtually all Russian territory. Paper describes the results of computational experiments at three scenarios of forest management using sample forest stand in the south of Moscow region.

The effect of axial restraint on the fire resistance of steel columns

The paper represents the outcomes of a joint research between the University of Ulster and the University of Sheffield into the performance of axially restrained steel columns during fire. The Ulster experimental program incorporates 37 high temperature tests that investigate three parameters: slenderness ratio (λ=49,75,98), degree of axial restraint (αk=0, 0.1,0.2,0.3) and loading ratio (αL=0,0.2,0.4,0.6). A unique test rig which allows the application of both axial restraint and loads, either separately or at the same time has been especially designed for the experimental program. Typical results from the fire tests are presented, which illustrates characteristic response of the columns to the imposition of axial restraint, coupled with the temperature increase. In addition, trend graphs charting generic response are discussed. An associated computational study by Sheffield provides satisfactory accurate computer simulations of fire tests, using standard materiel property input data. The computer modelling exercises has been extended to parametric studies, to include the effects of many more levels of axial restrain. The linked experimental and computational study has thus validated a computational model, which can be used to provide the basis design guidance of the behaviour of restrained columns in fire situations.

Standardization of Flexible Body Modeling in Multibody System Codes, Part I: Definition of Standard Input Data*

ABSTRACT To facilitate the use of data that describe finite element or continuum models for the simulation of flexible members in multibody codes, standard input data (SID) is defined. The SID are based on a modal representation of small body deformations. Therefore, integrals appearing in the multibody system equations can be pre-calculated by pre-processors and stored in the SID file before simulation. The SID structure is organized using an object-oriented class description.

How well do physical oceanographic (P.O.) models and routine P.O. measurements help predict acoustic propagation in shallow water?

In trying to answer the question posed in this title, the following outline is followed. First, the dominant oceanographic processes that effect shallow water (coastal) acoustic propagation in the 50-Hz to 2-kHz band is identified. Next, how well these ocean processes are understood and modeled, and how the models are constrained by standard input data is investigated. The limits of predictability of the ocean field (spatially and temporally) are then examined. The issue of the sensitivity of the acoustic field to the particular ocean processes is investigated, followed by the predictability of the acoustic field propagating through the ocean processes. The various measures of the acoustic field (proploss, coherence, etc.) one uses to quantify the ocean/acoustic interaction are considered, reflecting the needs of various acoustics applications. Which acoustics models are appropriate for describing propagation through particular oceanographic fields is also addressed. Finally, the impact of this forward modeling study on possible inverse problem studies for the oceanography is discussed.

Rapid Recharge in a Limestone Aquifer

ABSTRACTThe introduction of an infiltration mechanism called rapid recharge assists in the mathematical modelling of large seasonal variations in the response of the confined portion of a limestone aquifer. Such modelling employs the technique of using an interactive analogue‐digital computer, together with a new method of utilising standard hydrological input data.