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empirical modeling of force and temperature in drilling bone-simulating hybrid composites

JOURNAL OF COMPOSITE MATERIALS 2023年第17期57卷 2789-2808页

作者： Abusrea, Mahmoud Ahmadi, Keivan Sadek, Ahmad Cairo Univ Higher Coll Technol Mech Engn Engn Technol & Sci Abu Dhabi U Arab Emirates Univ Victoria Victoria BC Canada Natl Res Council Canada Montreal PQ Canada Higher Coll Technol Mech Engn Dept Engn Technol & Sci Abu Dhabi Men Campus Abu Dhabi U Arab Emirates

Hybrid polymer composites are utilized in biomechanical design and orthopedic surgery training to imitate the thermomechanical behavior of human bones. Despite extensive research on the mechanics of hybrid composites in biomechanical design, information on their thermomechanical response during orthopedic drilling operations is scarce. This paper presents a new experimental study to characterize the force and temperature generated during the drilling of hybrid composites that simulate human bones. To simulate the hybrid multi-layer structure of bones, the studied composite comprises a Polyurethane core sandwiched between Glass-Fiber Reinforced Polymer (GFRP) layers-the former resembling the cancellous part of the bone and the latter cortical layers. This study also identifies an empirical relationship between thrust force, temperature, drilling feed and speed, and composite composition. empirical models are developed using multivariate polynomial regression (MPR) and artificial neural network (ANN) to predict the force and temperature during drilling. The models have a correlation coefficient of above 0.9 between predicted and measured results and can be used to improve orthopedic drilling design and control.

关键词： Polymer composites biopolymers thermal properties empirical modeling bone drilling

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empirical modeling of olive oil mill wastewater treatment using loofa-immobilized Phanerochaete chrysosporium

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PROCESS BIOCHEMISTRY 2006年第5期41卷 1148-1154页

作者： Ahmadi, M Vahabzadeh, F Bonakdarpour, B Mehranian, M Amirkabir Univ Technol Tehran Polytech Dept Chem Engn Food Proc Engn & Biotechnol Res Ctr Tehran Iran

Central composite design (CCD) technique was used to develop an empirical model for the treatment of olive oil mill wastewater (OMW) by loofa-immobilized Phanerochaete chtysosporitan. The concentration of OMW (A) (i.e., 20%, 30% and 40%), concentration of ammonium sulfate as a source of nitrogen (B) (i.e., 0.25, 0.5 and 0.75 g/1) and glucose as a carbon source (C) (i.e. 3, 5 and 7 g/1), both of which used for the fungus growth, were considered as independent variables. The influence of these three regressors on the four dependent variables, i.e., chemical oxygen demand (COD), total phenols (TP), color and aromaticity removals was evaluated using second-order polynomial multiple regression model. Analysis of variance (ANOVA) showed a high coefficient of determination (R) value of 0.912-0.982, thus ensuring a satisfactory adjustment of the regression model with the experimental data. The positive sign for the coefficient of OMW concentration in the model, indicated that the COD, color and aromaticity removals increased with increased levels of this factor. While TP removal decreased with the increased concentration of OMW. The negative effect of nitrogen source concentration on the COD and color removals indicated that the response levels decreased as B increased. The positive sign for the coefficient of the interaction between two factors A and B on the removal of TP and color, indicated that a simultaneous increase in the OMW and the nitrogen source concentrations led to an increase in those responses. Although simultaneous increase in the concentrations of nitrogen source and glucose, decreased COD removal. Quadratic models were predicted for the response variables, i.e., pollutant removals, and the maximum values predicted were 64%, 88%, 48% and 39% for COD, TP, color and aromaticity, respectively. Optimum conditions for this wastewater treatment were obtained based on the performance of the loofa-immobilized P. chrysosporium in the experiment where OMW concentrat

关键词： central composite designs empirical modeling loofa immobilization olive oil mill wastewater Phanerochaete chrysosporium

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empirical modeling of chlorine dioxide delignification of oxygen-delignified hardwood kraft pulp

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JOURNAL OF WOOD SCIENCE 2004年第6期50卷 524-529页

作者： Yoon, BH Wang, LJ Lee, MK Kangwon Natl Univ Dept Paper Sci & Engn Chunchon 200701 South Korea Sungchang Fine Chem Co Inst Res & Dev Shihung 425470 South Korea

Due to the complexity of delignification, it is still not accurate enough to describe the whole chlorine dioxide delignification system with mechanistic models such as kinetic studies. The simple aim of predicting and optimizing the process requires the use of economical empirical models, few of which are in the literature. In this study. principal component analysis was used to classify various bleaching response variables, including end pH, kappa number, viscosity, and optical properties such as brightness, into different categories. Statistical methods, including factorial design, multiple regression, and response surface methodology, were then used successfully to screen the importance of bleaching factors and their interactions. Models to control, predicate, and optimize the bleaching responses were established. In most cases, the results of empirical modeling coincided well with those from conventional research methods, but the empirical methodology was more economic or less laborious. The empirical models are robust enough to predicate and optimize the bleaching responses to chlorine dioxide delignification of oxygen-delionified hardwood kraft pulp.

关键词： delignification chlorine dioxide empirical modeling mechanistic modeling bleaching

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empirical modeling of Heating Element Power for the Czochralski Crystallization Process

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modeling IDENTIFICATION AND CONTROL 2010年第1期31卷 19-34页

作者： Komperod, M. Lie, B. Ostfold Univ Coll Fac Engn N-1757 Halden Norway Telemark Univ Coll Fac Technol N-3901 Porsgrunn Norway

The Czochralski (CZ) crystallization process is used to produce monocrystalline silicon. Monocrystalline silicon is used in solar cell wafers and in computers and electronics. The CZ process is a batch process, where multicrystalline silicon is melted in a crucible and later solidifies on a monocrystalline seed crystal. The crucible is heated using a heating element where the power is manipulated using a triode for alternating current (TRIAC). As the electric resistance of the heating element increases by increased temperature, there are significant dynamics from the TRIAC input signal (control system output) to the actual (measured) heating element power. The present paper focuses on empirical modeling of these dynamics. The modeling is based on a dataset logged from a real-life CZ process. Initially the dataset is preprocessed by detrending and handling outliers. Next, linear ARX, ARMAX, and output error (OE) models are identified. As the linear models do not fully explain the process' behavior, nonlinear system identification is applied. The Hammerstein-Wiener (HW) model structure is chosen. The final model identified is a Hammerstein model, i.e. a HW model with nonlinearity at the input, but not at the output. This model has only one more identified parameter than the linear OE model, but still improves the optimization criterion (mean squared ballistic simulation errors) by a factor of six. As there is no nonlinearity at the output, the dynamics from the prediction error to the model output are linear, which allows a noise model to be added. Comparison of a Hammerstein model with noise model and the linear ARMAX model, both optimized for mean squared one-step-ahead prediction errors, shows that this optimization criterion is 42% lower for the Hammerstein model. Minimizing the number of parameters to be identified has been an important consideration throughout the modeling work.

关键词： Czochralski Crystallization Process empirical modeling Hammerstein-Wiener Model Heating Element Nonlinear System Identification

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empirical modeling of plasma clouds produced by the Metal Oxide Space Clouds experiment

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RADIO SCIENCE 2017年第5期52卷 578-596页

作者： Pedersen, Todd R. Caton, Ronald G. Miller, Daniel Holmes, Jeffrey M. Groves, Keith M. Sutton, Eric Air Force Res Lab Space Vehicles Directorate Albuquerque NM 87131 USA Los Angeles AFB Space & Missile Syst Ctr Remote Sensing Syst Directorate Los Angeles CA USA Boston Coll Inst Sci Res Chestnut Hill MA 02167 USA

The Advanced Research Project Agency (ARPA) Long-Range Tracking And Instrumentation Radar (ALTAIR) radar at Kwajalein Atoll was used in incoherent scatter mode to measure plasma densities within two artificial clouds created by the Air Force Research Laboratory (AFRL) Metal Oxide Space Clouds (MOSC) experiment in May 2013. Optical imager, ionosonde, and ALTAIR measurements were combined to create 3-D empirical descriptions of the plasma clouds as a function of time, which match the radar measurements to within 15%. The plasma clouds closely track the location of the optical clouds, and the best fit plasma cloud widths are generally consistent with isotropic neutral diffusion. Cloud plasma densities decreased as a power of time, with exponents between -0.5 and -1.0, or much more slowly than the -1.5 predicted by diffusion. These exponents and estimates of total ion number from integration through the model volume are consistent with a scenario of slow ionization and a gradually increasing total number of ions with time, reaching a net ionization fraction of 20% after approximately half an hour. These robust representations of the plasma density are being used to study impacts of the artificial clouds on the dynamics of the background ionosphere and on RF propagation.

关键词： chemical release empirical modeling chemionization samarium artificial plasma clouds incoherent scatter radar

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empirical modeling of chlorophyll a from MODIS satellite imagery for trophic status monitoring of Lake Victoria in East Africa

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JOURNAL OF GREAT LAKES RESEARCH 2021年第4期47卷 1209-1218页

作者： Gidudu, Anthony Letaru, Lydia Kulabako, Robinah N. Makerere Univ Dept Geomat & Land Management POB 7062 Kampala Uganda Makerere Univ Dept Civil & Environm Engn POB 7062 Kampala Uganda

We detail our attempts at empirical modeling of MODIS derived Chlorophyll a (Chl a) distribution on Lake Victoria in East Africa and consequently its trophic status. This was motivated by the need for Lake Victoria specific algorithms, as the current satellite based standard algorithms overestimate derived Chl a. In situ Chl a data was hence collected in three field campaigns in November 2014, March 2015 and July 2015. In situ reflectances were collected during the July campaign only. We first developed models from in situ reflectances and in situ Chl a, which when applied to MODIS bands performed dismally (R-2 = 0.03). We then proceeded to derive empirical models by directly comparing MODIS bands with in situ Chl a based on data collected in November 2014 and July 2015. The March 2015 dataset couldn't be used due to cloud cover hence no matchups could be obtained. The best model derived (R-2 = 0.88) was based on the ratio 488 nm/645 nm, and was then used to determine the trophic status of Lake Victoria using Carlson's Chl a Trophic State Index (TSI). The results show that large areas of the lake are mesotrophic with eutrophic displays closer to the shores. The modeled TSI was then validated against in situ TSI derived from the March dataset and posted an 80% matchup. One of the main challenges, however is the prevalence of cloud cover, which hinders synoptic mapping of the lake. That notwithstanding, the study demonstrates the potential of earth observation in providing accurate TSI information for improved management of Lake Victoria. (C) 2021 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved.

关键词： Chlorophyll_a empirical modeling Lake Victoria MODIS

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empirical modeling of ionospheric F2 layer critical frequency over Wakkanai under geomagnetic quiet and disturbed conditions

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Science China(Technological Sciences) 2012年第5期55卷 1169-1177页

作者： LIU Jing LIU LiBo ZHAO BiQiang WAN WeiXing CHEN YiDing Beijing National Observatory of Space Environment Institute of Geology and GeophysicsChinese Academy of Sciences Beijing 100029China Graduate University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Space Weather Center for Space Science and Applied ResearchChinese Academy of SciencesBeijing 100190China

The hourly values of the ionospheric F2 layer critical frequency, foF2, recorded at Wakkanai ionosonde station （45.4°N, 141.7°E） have been collected to construct a middle-latitude single-station model for forecasting foF2 under geomagnetic quiet and disturbed conditions. The module for the geomagnetic quiet conditions incorporates local time, seasonal, and solar vari- ability of climatological foF2 and its upper and lower quartiles. It is the first attempt to predict the upper and lower quartiles of foF2 to account for the notable day-to-day variability in ionospheric foF2. The validation statistically verifies that the model captures the climatological variations of foF2 with higher accuracy than IRI does. The storm-time module is built to capture the geomagnetic storm induced relative deviations of foF2 from the quiet time references. In the geomagnetically disturbed module, the storm-induced deviations are described by diumal and semidiumal waves, which are modulated by a modified magnetic activity index, the Kf index, reflecting the delayed responses of foF2 to geomagnetic activity forcing. The coeffi- cients of the model in each month are determined by fitting the model formula to the observation in a least-squares way. We provide two options for the geomagnetic disturbed module, including or not including Kalman filter algorithm. The Kalman filter algorithm is introduced to optimize these coefficients in real time. Our results demonstrate that the introduction of the Kalman filter algorithm in the storm time module is promising for improving the accuracy of predication. In addition, comparisons indicate that the IRI model prediction of the F2 layer can be improved to provide better performances over this region.

关键词： empirical modeling Kalman f'dter ionospheric storm

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empirical modeling Methodologies for Construction

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JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT-ASCE 2010年第1期136卷 36-48页

作者： Flood, Ian Issa, Raja R. A. Univ Florida Rinker Sch Coll Design Construct & Planning Gainesville FL 32611 USA

The paper provides a review of empirical modeling and its application within construction engineering and management. The scope of application and trends in use of this approach are first assessed, and the potential for its further development is identified. This is followed by an examination of the key components of empirical modeling, namely: the structure and operation of the model and the scheme used in its development. The paper then provides a rigorous methodology that must be followed to ensure the validity and value of the end model, covering the steps: strategizing;data collation and assessment;model development;model evaluation and final selection;final validation;and implementation. The methodology is designed to cater for all forms of empirical modeling including the procedurally more demanding development algorithms that have become available in recent years, such as simulated evolution. Overall, the paper is designed to provide researchers embarking on an empirical modeling study with an overview of when it is appropriate to use this approach, what type of system to adopt, and how to ensure development of a successful end product.

关键词： empirical modeling Structured model Static model Dynamic model Development algorithm Data collection Data analysis Model validation

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empirical modeling of antibiotic fermentation process using neural networks and genetic algorithms

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MATHEMATICS AND COMPUTERS IN SIMULATION 1999年第4-5期49卷 363-379页

作者： Potocnik, P Grabec, I Univ Ljubljana Fac Mech Engn SI-1000 Ljubljana Slovenia

empirical modeling of the industrial antibiotic fed-batch fermentation process is discussed in this paper. Several methods including neural networks, genetic algorithms and feature selection are combined with prior knowledge in the research methodology. A linear model, a radial basis function neural network and a hybrid linear-neural network model are applied for the model formation. Two approaches to modeling of antibiotic fermentation process are presented: a dynamic modeling of the process and a modeling in the fermentation sample space. The first approach is focused on the current state of the fermentation process and forecasts the future product concentration. The second approach treats the fermentation batch as one sample which is characterized by the set of extracted features. Based on these features, the fermentation efficiency is predicted. modeling in the fermentation sample space integrates the prior knowledge of experts with empirical information and can represent a basis for the control of the fermentation process. (C) 1999 IMACS/Elsevier Science B.V. All rights reserved.

关键词： empirical modeling fermentation process neural networks genetic algorithms hybrid modeling feature extraction feature selection

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empirical modeling of drying kinetics and microwave assisted extraction of bioactive compounds from Adathoda vasica and Cymbopogon citratus

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ALEXANDRIA ENGINEERING JOURNAL 2016年第1期55卷 141-150页

作者： Simha, Prithvi Mathew, Melvin Ganesapillai, Mahesh Univ Manchester SEAES Oxford Rd Manchester M13 9PL Lancs England Cent European Univ Dept Environm Sci & Policy Nador Utca 9 H-1051 Budapest Hungary Arizona State Univ Div Chem Engn SEMTE Ira A Fulton Sch Engn Tempe AZ 85287 USA VIT Univ Sch Mech & Bldg Sci Div Chem Engn Mass Transfer Grp Vellore 632014 Tamil Nadu India

To highlight the shortcomings in conventional methods of extraction, this study investigates the efficacy of Microwave Assisted Extraction (MAE) toward bioactive compound recovery from pharmaceutically-significant medicinal plants, Adathoda vasica and Cymbopogon citratus. Initially, the microwave (MW) drying behavior of the plant leaves was investigated at different sample loadings, MW power and drying time. Kinetics was analyzed through empirical modeling of drying data against 10 conventional thin-layer drying equations that were further improvised through the incorporation of Arrhenius, exponential and linear-type expressions. 81 semi-empirical Midilli equations were derived and subjected to non-linear regression to arrive at the characteristic drying equations. Bioactive compounds recovery from the leaves was examined under various parameters through a comparative approach that studied MAE against Soxhlet extraction. MAE of A. vasica reported similar yields although drastic reduction in extraction time (210 s) as against the average time of 10 h in the Soxhlet apparatus. Extract yield for MAE of C. citratus was higher than the conventional process with optimal parameters determined to be 20 g sample load, 1:20 sample/solvent ratio, extraction time of 150 s and 300 Woutput power. Scanning Electron Microscopy and Fourier Transform Infrared Spectroscopy were performed to depict changes in internal leaf morphology. (C) 2015 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).

关键词： Microwave assisted extraction Drying kinetics empirical modeling Extraction Food Medicinal plants

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