Acceptable Error Limits Research Articles

Assessment of flood damage behaviour in connection with large‐scale climate indices

AbstractFlood damage assessment is a necessary tool in the planning of flood‐prone areas. There are several factors affecting the flood damages. It is not easy to detect these effective factors by classical methods. In this study, correlation coefficient and cross wavelet analysis are used to look for a possible connection between flood losses and large‐scale climate indices. Some strong connections suggest that sea surface temperature anomalies influence the general characteristic of flood damage distribution across the United States. Time‐series analyses of flood damage data reveal that there is an upward trend in the flood losses. This apparent trend can be related to increase in population. Also, an autoregressive model and a regression model are proposed on the predictability of flood damages. It is shown that model errors stay within the acceptable error limits.

Correlations for flow boiling heat transfer in minichannels with various orientations

Abstract The paper presents the results of using known correlations for boiling heat transfer in a minichannel 1 mm deep, 40 mm wide and 360 mm long, with three spatial orientations: vertical, position 90° and two horizontal orientations: positions 0° and 180°. The heating element for cooling liquid flowing laminarly in the minichannel is a single-sided microstructured foil. Liquid crystal thermography was used for measuring the temperature distribution on the plain side of the heating surface. The observations of the flow structures were carried out on the microstructured side of the foil contacting fluid in the minichannel. 12 selected correlations for boiling heat transfer have been used in calculations. It was found that the majority of correlations enabled the predicting of heat transfer coefficient within an acceptable error limit (±30%) only in a specific orientation of the channel. For the horizontal channel, position 0°, the highest compliance occurred when Mikielewicz et al. correlation was applied, for the vertical channel – when Liu and Winterton correlation was used and for horizontal channel, position 180° – by the application of Cooper correlation. The own correlation, with taken account for the microstructured heating wall, was proposed in two forms: for saturated boiling and for boiling incipience and subcooled boiling. Most experimental data show congruence with theoretical correlations with the tolerance ±35%.

ADSORPTION CHARACTERISTICS AND HEAT OF ADSORPTION MEASUREMENTS OF R-134a ON GRANULAR ACTIVATED CARBON

The objective of this study is to investigate the adsorption characteristics of granular activated carbon GAC/R-134a pair in the temperature range of 20–60°C and pressure up to 10 bars. The Dubinin–Astakhov adsorption equilibrium model is fit to experimental data with acceptable error limit. The pressure–temperature–concentration (P–T–X) diagram of the pair is also presented. The isosteric heat of adsorption of R-134a on AC has been calculated using the Clausius–Clapeyron equation as a function of adsorption capacity. The maximum adsorption capacity was found to be 1.92 kgR134a/kgcarbon at 20°C after 1200 s. The experimental results also shows that the increase of heat transfer area improves the adsorption capacity per kg of adsorber, which lead to the design of a finned tubes heat exchanger adsorption unit.

Application of artificial neural network for performance evaluation of vertical axis wind turbine rotor

In the present paper, artificial neural network (ANN) modelling has been performed for evaluating power coefficient (Cp) and torque coefficient (Ct) of a combined three-bucket-Savonius and three-bladed-Darrieus vertical axis wind turbine rotor, which has got potential for power generation in a small-scale manner, especially in low wind speed conditions. However, detailed experimental work on the rotor for evaluating its performance parameters is either scarce or too costly and time consuming to carry out. In this work, a new ANN modelling method is adopted to map the input–output parameters using very small training data sets, selected from past experimental results of the rotor. The trained ANN models are used to predict the performance data, which are obtained within acceptable error limits. Furthermore, to evaluate the fit values and estimate the variance of the predicted data by the ANN models, linear regression equations are fitted to the experimental and predicted results, which shows that R-squared (R2) values are obtained close to unity meaning good fitting of the data. Moreover, the results of ANN modelling are also compared with that of radial basis function (RBF) networks, which also show a good agreement between ANN predicted data and RBF network data. The present ANN models can be exploited to extract more performance data within a given range of input data.

Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in paediatric liver transplant recipients

The objectives of this study were to develop a population pharmacokinetic (PopPK) model for tacrolimus in paediatric liver transplant patients and determine optimal sampling strategies to estimate tacrolimus exposure accurately. Twelve hour intensive pharmacokinetic profiles from 30 patients (age 0.4-18.4 years) receiving tacrolimus orally were analysed. The PopPK model explored the following covariates: weight, age, sex, type of transplant, age of liver donor, liver function tests, albumin, haematocrit, drug interactions, drug formulation and time post-transplantation. Optimal sampling strategies were developed and validated with jackknife. A two-compartment model with first-order absorption and elimination and lag time described the data. Weight was included on all pharmacokinetic parameters. Typical apparent clearance and central volume of distribution were 12.1 l h(-1) and 31.3 l, respectively. The PopPK approach led to the development of optimal sampling strategies, which allowed estimation of tacrolimus pharmacokinetics and area under the concentration–time curve (AUC) on the basis of practical sampling schedules (three or four sampling times within 4 h) with clinically acceptable prediction error limit. The mean bias and precision of the Bayesian vs. reference (trapezoidal) AUCs ranged from -2.8 to -1.9% and from 7.4 to 12.5%, respectively. The PopPK of tacrolimus and empirical Bayesian estimates represent an accurate and convenient method to predict tacrolimus AUC(0-12) in paediatric liver transplant recipients, despite high between-subject variability in pharmacokinetics and patient demographics. The developed optimal sampling strategies will allow the undertaking of prospective trials to define the tacrolimus AUC-based therapeutic window and dosing guidelines in this population.

Application of heat transfer correlations for FC-72 flow boiling heat transfer in minichannels with various orientations

The paper presents the results of using known correlations for boiling heat transfer in a minichannel 1 mm deep, 40 mm wide and 360 mm long, with different spatial orientations. The heating element for FC-72 flowing laminarly in the minichannel is a single-sided microstructured foil. Liquid crystal thermography was used for measuring the temperature distribution on the plain side of the foil. The observations of the flow structures were carried out on the microstructured side of the foil contacting fluid in the minichannel. A number of correlations for boiling heat transfer have been used in calculations. It was found that the majority of correlations enabled the predicting of heat transfer coefficient within an acceptable error limit (±30%) only in a specific orientation of the channel. For the horizontal channel, position 0 o , the highest compliance occurred when Mikielewicz et al. correlation was applied, for the vertical channel - when Liu and Winterton correlation was used and for horizontal channel, position 180 o - by the application of Cooper correlation. The own correlation, with taken account for the microstructured heating wall, was proposed in two forms: for saturated boiling and for boiling incipience and subcooled boiling. Most experimental data show congruence with theoretical correlations with the tolerance 35%.

Experimental Investigation of Granular Activated Carbon/R-134a Pair for Adsorption Cooling System Applications

The objective of this study is to investigate the adsorption characteristics of granular activated carbon GAC/R-134a pair in the temperature range of 20℃ - 60℃ and pressure up to 10 bars. The Dubinin-Astakhov adsorption equilibrium model is fit to experimental data with acceptable error limit. The pressure-temperature-concentration (P-T-X) diagram of the pair is also presented. The isosteric heat of adsorption of R-134a on activated carbon has been calculated using the Clausius-Clapeyron equation as a function of adsorption capacity. The maximum adsorption capacity was found to be 1.92 kgR134a/kg carbon at 20℃ after 1200 s. The experimental results also show that the increase of heat transfer area improves the adsorption capacity per kg of adsorber, which leads to the design of a finned tubes heat exchanger adsorption unit.

A Review of Selected Inorganic Surface Water Quality-Monitoring Practices: Are We Really Measuring What We Think, and If So, Are We Doing It Right?

Successful environmental/water quality-monitoring programs usually require a balance between analytical capabilities, the collection and preservation of representative samples, and available financial/personnel resources. Due to current economic conditions, monitoring programs are under increasing pressure to do more with less. Hence, a review of current sampling and analytical methodologies, and some of the underlying assumptions that form the bases for these programs seems appropriate, to see if they are achieving their intended objectives within acceptable error limits and/or measurement uncertainty, in a cost-effective manner. That evaluation appears to indicate that several common sampling/processing/analytical procedures (e.g., dip (point) samples/measurements, nitrogen determinations, total recoverable analytical procedures) are generating biased or nonrepresentative data, and that some of the underlying assumptions relative to current programs, such as calendar-based sampling and stationarity are no longer defensible. The extensive use of statistical models as well as surrogates (e.g., turbidity) also needs to be re-examined because the hydrologic interrelationships that support their use tend to be dynamic rather than static. As a result, a number of monitoring programs may need redesigning, some sampling and analytical procedures may need to be updated, and model/surrogate interrelationships may require recalibration.

Intraoral Digital Radiography for Adult Age Estimation: A Reliable Technique

Aims and objectives: This study aimed at estimating the age of an individual from mandibular premolars using the pulp to tooth area ratio (AR) measured from the digital intraoral radiographic images or radiovisuographic images (RVGs). Materials and methods: The study comprised of 120 patients divided into two subsets of 30 test subjects and 90 study subjects. The RVG images of mandibular premolars were acquired and the pulp to tooth area ratio was measured using the software Jenoptic ProgRess Version 2.7. Pearson’s correlation test and regression analysis was employed. Intraobserver variation was evaluated with paired t-test. Results: The AR was a significant (p-value <0.001) predictor of age with a mean absolute error (MAE) of 5.38 years using the formula, Age = 89.778-379.020 (AR). This equation when applied on the test subset revealed no statistically significant difference (p = 0. 256) between estimated and chronological ages with no gender differences. The age estimated from the RVG images were more accurate in 36 to 50 year patients. Conclusion: Considering that the acceptable error limits for forensic age estimation is being less than ±10 years, this method of age estimation provides a fairly accurate and reliable noninvasive method.

Adult forensic age estimation using mandibular first molar radiographs: A novel technique

Objective:To develop an independent procedure for estimating age for Indian individuals using radiographs of multi-rooted posterior teeth with accuracy needed in forensic age prediction.Materials and Methods:Orthopantomography (OPG) was obtained for 88 subjects. The subjects were divided into two sub sets; study subset (n = 60) which were used to find regression formula to calculate the age from pulp chamber height and test subset (n = 28) which were used to test the accuracy of this formula.Results:There was a statistically significant strong correlation between chronological age and pulp chamber crown root trunk height ratio (r = −0.56; P = 0.000). The regression equation for estimating the age, derived from the study subset was estimated age = −100.920 (PCTHR) +55.415. (PCTHR is the pulp chamber crown root trunk height ratio). This equation was applied on the test subset and there was no significant difference between estimated ages and chronological ages (P = 0.639). The mean absolute error (MAE) was 6.96 years, which was within acceptable error limits for forensic age estimation (<±10 years).Conclusion:The procedure developed to estimate the age using height reduction in pulp chamber was found to be fairly accurate to perform forensic age prediction in Indian individuals.

Artificial neural network based computational model for the prediction of direct solar radiation in Indian zone

In this paper, a computational model for the prediction of direct solar radiation based on neural network analysis of atmospheric clearness is developed. It considers that the major portion of direct solar radiation reaching the earth's surface is governed by Sun-Earth geometry and atmospheric transmittance factors which are exactly calculable by clear day model. Additional variations are due to climate and weather phenomena characterized by relative humidity, mean duration of sunshine per hour, and rainfall, etc., in the atmosphere. These variations are taken into account with the help of a composite parameter referred to as atmospheric clearness index (CI) which is determined using artificial neural network analysis. The contour maps of CI as a function of latitude, time of the day, and month of the year are then prepared using the meteorological data of eleven stations. Model simulation and test results of the trained network for two typical locations (not used in training the network) are presented and compared with measured values. The deviations are well within acceptable error limits [percentage root mean square error values for Ahmedabad and Nagpur are 3.34 and 2.06, respectively]. The methodology, for predicting the direct solar radiation at an arbitrary location using the well known parameters such as altitude, latitude, time of the day, day of the year, and CI values derived from the contour maps, is discussed. The outcome of the present ANN model for four arbitrary locations is compared with NASA SSE data sets.

DESIGN AND IMPLEMENTATION OF A WEARABLE, MULTIPARAMETER PHYSIOLOGICAL MONITORING SYSTEM FOR THE STUDY OF HUMAN HEAT STRESS, COLD STRESS, AND THERMAL COMFORT

This article describes the design and implementation of a wearable, multiparameter physiological monitoring system called the Sensing Belt system, which consists of multiple sensors integrated into fabric that communicates with a physiological data acquisition unit (PDAU) that in turn transmits these data to a remote monitoring center (RMC) for analysis. A number of vital signs can be acquired by the system, including electrocardiography (ECG), respiratory inductance plethysmograph (RIP), posture/activity, multipoint skin temperature (TSK), and rectal temperature (TRC). The physiological data can be stored on a MicroSD card or transmitted to the RMC, where specialized analysis will be provided to extract parameters such as heart rate (HR), respiratory rate (RR), respiratory sinus arrhythmia (RSA), and human energy expenditure. The RMC can receive physiological data from up to 16 Sensing Belt users simultaneously. A medical validation test was carried out to compare the accuracy of the physiological data obtained from the Sensing Belt system with data obtained concurrently from traditional, calibrated laboratory physiological monitoring instruments. The results showed that most of the variables measured by the Sensing Belt are within acceptable error limits. The mean temperature on two trials (walking and running) showed significantly higher mean differences than on other trials, but the correlation coefficient (r) remained high (0.985 and 0.989, respectively). This study demonstrates the accuracy of the Sensing Belt system for the monitoring of these physiological parameters and suggests that it could be used to provide a complete human physiological monitoring platform for the study of human heat stress, cold stress, and thermal comfort.

Design and Development of High-Velocity Slurry Erosion Test Rig Using CFD

Slurry erosion (SE) is commonly observed in almost all kinds of components and machineries involved in fluid (liquid) transfer and delivery. During design and development phase of these components, test rigs are usually required to evaluate their performance; however, only few detailed designs of test rigs are available for SE investigations. Among the existing designs of SE test rigs, most of them belong to rotary type. In the present study, design of a new type of SE test rig has been proposed, which is simpler in construction and working. This newly designed test rig could possibly eliminate some of the limitations (velocity-concentration interdependence and lack of acceleration distance) found in the existing set-ups. Calibration of the test rig was done for jet velocity and erodent concentration. Commissioning of the rig was undertaken by evaluating the effect of operating parameters (concentration and impingement angle) on the erosion rates of aluminum and cast iron. Results show that the rig was able to capture the traditional responses of ductile and brittle erosion behaviors being observed for these materials. Repeatability of the test rig was ensured, and the results were found to be within the acceptable error limits.

QoS Routing in Mobile Ad-hoc Networks using Agents

Quality of Service (QoS) provisioning in a Mobile Ad-hoc Network (MANETs) routing for multimedia traffic is a challenging task due to dynamic topology of such networks. Fuzzy Logic (FL) were used for QoS prediction from current uncertain QoS constraints in the network for particular applications, from these uncertain constraints there is an error at the QoS prediction. To overcome this error, we proposed an intelligent system called ”Neuro-Fuzzy” (NF) system. Our proposed scheme optimizes the uncertain weights before QoS prediction using Error Back Propagation (EBP) algorithm, this optimization is done till to get acceptable error limit. From these optimized weights we can predict more accurately and hence, we can provide the well quality of service to the user. And also to provide real-time communication in MANETs, we used software agents.

Estimation of relative humidity based on artificial neural network approach in the Aegean Region of Turkey

The aim of this study is to estimate the monthly mean relative humidity (MRH) values in the Aegean Region of Turkey with the help of the topographical and meteorological parameters based on artificial neural network (ANN) approach. The monthly MRH values were calculated from the measurement in the meteorological observing stations established in Izmir, Mugla, Aydin, Denizli, Usak, Manisa, Kutahya and Afyonkarahisar provinces between 2000 and 2006. Latitude, longitude, altitude, precipitation and months of the year were used in the input layer of the ANN network, while the MRH was used in output layer of the network. The ANN model was developed using MATLAB software, and then actual values were compared with those obtained by ANN and multi-linear regression methods. It seemed that the obtained values were in the acceptable error limits. It is concluded that the determination of relative humidity values is possible at any target point of the region where the measurement cannot be performed.

Adsorption properties of a natural zeolite–water pair for use in adsorption cooling cycles

The equilibrium adsorption capacity of water on a natural zeolite has been experimentally determined at different zeolite temperatures and water vapor pressures for use in an adsorption cooling system. The Dubinin–Astakhov adsorption equilibrium model is fitted to experimental data with an acceptable error limit. Separate correlations are obtained for adsorption and desorption processes as well as a single correlation to model both processes. The isosteric heat of adsorption of water on zeolite has been calculated using the Clausius–Clapeyron equation as a function of adsorption capacity. The cyclic adsorption capacity swing for different condenser, evaporator and adsorbent temperatures is compared with that for the following adsorbent–refrigerant pairs: activated carbon–methanol; silica gel–water; and, zeolite 13X–water. Experimental results show that the maximum adsorption capacity of natural zeolite is nearly 0.12 kg w /kg ad for zeolite temperatures and water vapor pressures in the range 40–150 °C and 0.87–7.38 kPa.

Experimental and kinetic study of NO oxidation on model Pt catalysts

Modeling and experimental studies on model Pt/Al 2O 3 and Pt/BaO/Al 2O 3 catalysts are performed to elucidate the kinetics of NO oxidation, which is a key step during the lean phase of NO x trap operation. Experiments show that a steady-state is never truly achieved during NO oxidation; a continuous decrease in the reaction rate with time is observed on both the catalysts. This decrease is distinct from and beyond the prompt inhibition of the NO oxidation reaction observed with NO 2 in the feed or product. NO oxidation carried out after catalyst pretreatments with H 2, O 2, and NO 2 indicates that NO 2 is responsible for the deactivation while NO 2 storage plays a negligible role. Experiments with NO 2 as the feed elucidate its role in the production of NO, either by storage or by decomposition, for a wide range of temperatures. The highly oxidizing nature of NO 2 suggests that the Pt surface could be covered with oxygen, either as chemisorbed O or as Pt oxides, which results in slow poisoning of the catalyst. Microkinetic analysis of the NO oxidation reaction shows O 2 adsorption as the rate-determining step and predominant surface species to be adsorbed NO and O. Based on the microkinetic studies, a global kinetic model is proposed which includes the inhibiting effect of NO 2 on the NO oxidation reaction. The importance of including coverage of NO in the global model at low temperatures is shown, which is neglected in the current literature global models. The model predicts the experimental observations for a wide range of temperatures within acceptable error limits. However, prediction of the transient data requires modeling of NO 2 storage, decomposition and the complex NO 2 inhibition chemistry in addition to other surface reactions.

Estimation of diffusion parameters in fluidized bed drying

The present work is an attempt to assess the drying kinetics of green pepper in a fluidized bed in a temperature range of 65–105 °C. The drying kinetics is modeled using several semi empirical models to estimate the kinetic parameters. Although the semi empirical model could fit the experimental data well within acceptable experimental error limits, the two parameter models such as Henderson Pabis model and Page Model are identified to predict the drying kinetics with lesser error. The kinetic parameter ( k) is found to increase with the temperature for all the models. The activation energy ( E) estimated using Arrhenius equation is found to be 30.3 kJ/mol, while the Arrhenius constant ( k o) is found to be 0.09 s −1. The effective diffusivity coefficient is evaluated using Fick’s diffusion equation which is found increase with increase in temperature of the heating medium and to vary from 1.95 × 10 −11 to 7 × 10 −11 m 2/s.

Thermal decomposition of natural fibers: Global kinetic modeling with nonisothermal thermogravimetric analysis

AbstractThe modeling of thermal decomposition process of ten natural fibers commonly used in polymer composite industry was performed by assuming a global model occurring within the entire degradation range with consideration of fiber as one pseudocomponent. Málek method with activation energy values previously obtained was applied to the modeling process. Careful calculation and evaluation indicated that, within an acceptable error limit of 5%, RO(n &gt; 1) model can be used to describe the degradation process of most selected fibers well. The other kinetic parameters used include activation energy range of 160–170 kJ/mol; parameter n in RO(n &gt; 1) = (1 − α)n of 3–4; and ln A between 35 and 42 ln s−1. Some condition limitations of the obtained model were also discussed. The model has practical significance in predicting fiber weight loss when the fiber is used in combination with engineering thermoplastics. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009

Seismic diffraction tomography technique using very fast simulated annealing method for delineating small subsurface features

Diffraction, once considered noise rather than signal in seismic tomography, has recently been successfully used for delineating smaller objects whose size is comparable to or less than the wavelength of the incident seismic wave. But Most of the seismic diffraction tomography works are based on Born's and Rytov's approximation of weak scattering to linearize the expression for the scattered field due to an object and this is the basis of Fourier Diffraction Theorem. However, In this paper, we used the amplitude of the total scattered wave field without considering any approximation of weak scattering to obtain the synthetic scattered field data for forward modeling. These synthetic data are then inversed by Very Fast Simulated Annealing method which is a nonlinear inversion technique to obtain the unknown model parameters. This algorithm is applicable to both weak as well as strong scatterers. The simulated results give fairly good estimate for unknown model parameters of the scattering object within acceptable error limits.