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Pavement sustainability index for highway infrastructures： A case study of Maryland

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Frontiers of Structural and Civil Engineering 2018年第2期12卷 192-200页

作者： Stella o. oBAZEE-igbinedion oludare oWoLABI Montgomery County Department of Transportation 100 Edison Park Drive Gaithersburg MD 20878 USA Department of Civil Engineering Morgan State University 1700 East Cold Spring Lane Baltimore MD 21251 USA

Pavement deterioration creates conditions that undermine their performances, which gives rise to the need for maintenance and rehabilitation. This paper develops a mathematical multi-linear regression analysis （MLRA） model to determine a pavement sustainability index （PSTI） as dependent variable for flexible pavements in Maryland. Four categories of pavement performance evaluation indicators are subdivided into seven pavement condition indices and analyzed as independent variables for each section of pavement. Data are collected from five different roadways using field evaluations and existing database. Results indicate that coefficient of determination （R^2） is correlated and significant, R^2 = 0.959. of the seven independent variables, present serviceability index （PSI） is the most significant with a coefficient value of 0.032, present serviceability rating （PSR） coefficient value=0.028, and international roughness index （IRI） coefficient value = -0.001. Increasing each unit value of coefficients for PSI and PSR would increase the value of PSTI; thereby providing a more sustainable pavement infrastructure; which explains the significance of the model and why IR/ will most likely impact environmental, economic and social values.

关键词： pavement indices sustainability pavement performance flexible pavements

Predicting the effects of selected reservoir petrophysical properties on bottomhole pressure via three computational intelligence techniques

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Petroleum Research 2023年第1期8卷 118-129页

作者： Emmanuel E.okoro samuel E.Sanni Tamunotonjo obomanu Paul igbinedion Department of Petroleum Engineering University of Port HarcourtRivers StateNigeria Department of Chemical Engineering Covenant UniversityOtaNigeria Department of Petroleum Engineering Federal Polytechnic of Oil and GasBonny IslandNigeria Department of Petroleum Engineering Covenant UniversityOtaNigeria

This study investigates the effects of selected petrophysical properties on predicting flowing well bottomhole *** efficiently situate the essence of this investigation,genetic,imperialist competitive and whale optimization algorithms were used in predicting the bottomhole pressure of a reservoir using production data and some selected petrophysical properties as independent input variables.A total of 15,633 data sets were collected from Volvo field in Norway,and after screening the data,a total of 9161 data sets were used to develop apt computational intelligence *** data were randomly divided into three different groups:training,validation,and testing *** case scenarios were considered in this *** first scenario involved the prediction of flowing bottomhole pressure using only eleven independent variables,while the second scenario bothered on the prediction of the same flowing bottomhole pressure using the same independent variables and two selected petrophysical properties(porosity and permeability).Each of the two scenarios involved as implied in the first scenario,the use of three(3)heuristic search optimizers to determine optimal model *** optimizers were allowed to choose the optimal number of layers(between 1 and 10),the optimal number of nodal points(between 10 and 100)for each layer and the optimal learning rate required per task/*** results,showed that the models were able to learn the problems well with the learning rate fixed from 0.001 to 0.0001,although this became successively slower as the leaning rate *** the chosen model configuration,the results suggest that a moderate learning rate of 0.0001 results in good model performance on the trained and tested data *** the three heuristic search optimizers based on minimum MSE,RMSE,MAE and highest coefficient of determination(R^(2))for the actual and predicted values,shows that the imperialist competitive algorithm optimizer predicted

关键词： Computational intelligence Bottomhole pressure Petrophysical properties Heuristic search optimizer Volvo field data

Application of artificial intelligence in predicting the dynamics of bottom hole pressure for under-balanced drilling:Extra tree compared with feed forward neural network model

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Petroleum 2022年第2期8卷 227-236页

作者： Emmanuel E.okoro Tamunotonjo obomanu samuel E.Sanni David I.olatunji Paul igbinedion Petroleum Engineering Department Covenant UniversityOtaNigeria Petroleum Engineering Department Federal Polytechnic of Oil and GasBonnyNigeria Chemical Engineering Department Covenant UniversityOtaNigeria

This study used six fields data alongside correlation heat map to evaluate the field parameters that affect the accuracy of bottom hole pressure(BHP)*** six oil field data were acquired using measurement while drilling device to collect surface measurements of the downhole pressure data while *** the two case studies,measured field data of the wellbore filled with gasified mud system was utilized,and the wellbores were drilled using rotary jointed drill *** Randomized Tree and feed forward neural network algorithms were used to develop models that can predict with high accuracy,BHP from measured field *** modeling purpose,an extensive data from six fields was used,and the proposed model was further validated with two data from two new *** gathered data encompasses a variety of well data,general information/data,depths,hole size,and *** developed model was compared with data obtained from two new fields based on its capability,stability and *** result and model’s performance from the error analysis revealed that the two proposed Extra Tree and Feed Forward models replicate the bottom hole pressure data with R2 greater than *** high values of R^(2) for the two models suggest the relative reliability of the modelling *** magnitudes of mean squared error and mean absolute percentage error for the predicted BHPs from both models range from 0.33 to 0.34 and 2.02%-2.14%,for the Extra tree model and 0.40-0.41 and 3.90%e3.99%for Feed Forward model respectively;the least errors were recorded for the Extra Tree ***,the mean absolute error of the Extra Tree model for both fields(9.13-10.39 psi)are lower than that of the Feed Forward model(10.98-11 psi),thus showing the higher precision of the Extra Tree model relative to the Feed Forward *** has shown that underbalanced operation does not guarantee the improvement of horizontal well’s extension ability,because it mainly depends on t

关键词： Artificial intelligence Bottom hole pressure Extra tree Predictive model oil and gas Feed forward algorithms

Evaluation of influential parameters for supersonic dehydration of natural gas: Machine learning approach

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Petroleum Research 2022年第3期7卷 372-383页

作者： Emmanuel E.okoro Uyiosa igbinedion Victor Aimikhe samuel E.Sanni okorie E.Agwu Department of Petroleum and Gas Engineering University of Port HarcourtNigeria Department of Petroleum Engineering.Covenant University OtaNigeria Department of Chemical Engineering Covenant UniversityOtaNigeria Department of Petroleum Enginering University of UyoNigeria

The supersonic dehydration of natural gas is gaining more attention due to its numerous advantages over the conventional natural gas dehydration ***,supersonic separators have seen minimal field applications despite the multiple benefits over other gas dehydration *** has been mostly attributed to the uncertainty in ascertaining the design and operating parameters that should be monitored to ensure optimum dehydration of the supersonic separation *** this study,the decision tree machine learning model is employed in investigating the effects of design and operating parameters(inlet and outlet pressures,nozzle length,throat diameter,and pressure loss ratio)on the supersonic separator performance during dehydration of natural *** model results show that the significant parameters influencing the shock wave location are the pressure loss ratio and nozzle *** former was found to have the most significant effect on the dew point *** dehydration efficiency is mainly dependent on the pressure loss ratio,nozzle throat diameter,and the nozzle *** the machine learning model-accuracy with a 1-D iterative model,the machine learning model outperformed the 1-D iterative model with a lower mean average percentage error(MAPE)of 5.98 relative to 15.44 as obtained for the 1-D model.

关键词： Supersonic separator Machine learning model Natural gas dehydration Separation efficiency

Thermodynamic analysis for a third grade fluid through a vertical channel with internal heat generation

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Journal of Hydrodynamics 2015年第2期27卷 264-272页

作者： ADESANYA samuel o. MAKINDE oluwole D. Department of Mathematical Sciences Redeemer's University Faculty of Military Science Stellenbosch University

This paper makes the thermodynamic analysis in forced convective flow of a third grade fluid through a vertical channel. Due to the reactive nature of the fluid, the effect of internal heat generation is considered and assumed to be a linear function of temperature. The coupled nonlinear dimensionless ordinary differential equations governing the fluid flow are solved by using the Adomian decomposition method（ADM）. The effects of various physical parameters such as third grade material parameter, buoyancy parameter and heat generation parameter on the thermal structure of flow are presented and discussed.

关键词： energy conservation vertical channel third grade fluid internal heat generation Adomian decomposition method(ADM)

Neurotrophic fragments as therapeutic alternatives to ameliorate brain aging

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Neural Regeneration Research 2023年第1期18卷 51-56页

作者： Itzel ortiz Flores samuel Treviño Alfonso Díaz Department of Health Sciences School of MedicineUniversity of the Americas PueblaPueblaMexico Faculty of Chemical Sciences Benemerita Autonomous University of PueblaPueblaMexico

Aging is a global phenomenon and a complex biological process of all living beings that introduces various *** this physiological process,the brain is the most affected organ due to changes in its structural and chemical functions,such as changes in plasticity and decrease in the number,diameter,length,and branching of dendrites and dendritic ***,it presents a great reduction in volume resulting from the contraction of the gray ***,aging can affect not only cognitive functions,including learning and memory,but also the quality of life of older *** a result of the phenomena,various molecules with notable neuroprotective capacity have been proposed,which provide a therapeutic alternative for people under conditions of aging or some neurodegenerative *** is important to indicate that in recent years the use of molecules with neurotrophic activity has shown interesting results when evaluated in in vivo *** review aims to describe the neurotrophic potential of molecules such as resveratrol(3,5,4′-trihydroxystilbene),neurotrophins(brain-derived neurotrophic factor),and neurotrophic-type compounds such as the terminal carboxyl domain of the heavy chain of tetanus toxin,cerebrolysin,neuropeptide-12,and *** of these molecules have been evaluated by our research *** suggest that these molecules exert an important therapeutic potential,restoring brain function in aging conditions or models of neurodegenerative ***,our interest is in describing the current scientific evidence that supports the therapeutic potential of these molecules with active neurotrophic.

关键词： Alzheimer’s disease brain cerebral cortex cognitive function dendritic spines HC-TeTx hippocampus neurodegeneration neuronal survival neurotrophins

Acute and chronic toxicity studies of hydromethanol leaf extract of Helianthus annuus *** rats

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Asian Pacific Journal of Tropical Medicine 2018年第9期11卷 534-539页

作者： samuel o.onoja samuel C.Udem Aruh o.Anaga Isaac U.Asuzu Department of Veterinary Physiology and Pharmacology Michael Okpara University of AgricultureUmudike Department of Veterinary Physiology and Pharmacology Faculty of Veterinary MedicineUniversity of Nigeria

objective:To investigate the safety levels of hydromethanol leaf extract of Helianthus annuus Linn.(***) in ***:Acute oral toxicity test of hydromethanol leaf extract of *** was conducted through up and down method at 2.00 g/kg dose limit in *** chronic toxicity study was conducted by administering different concentrations(0.25,0.50 and 1.00 g/kg) of hydromethanol extract of *** in feed,for 90 consecutive *** days 30,60 and 90,blood samples were collected from the retro-orbital plexus of the rats for determination of serum biochemical *** examination of the pancreas,livers,kidneys and testis were also ***:The LD_(50) of the hydromethanol extract of *** greater than 2.00 g/kg and it significantly(P of hydromethanol extract of *** groups were elevated when compared with the control *** were fibrosis in the kidneys and livers;degeneration and necrosis in the testis and significant dose-dependent increases in number and size of pancreatic islet of ***:The findings suggest that hydromethanol extract of *** is tolerated in short term administration,but long term(up to 90 days) administration at high doses,may elicit hepatic,testicular and nephrotic disorder.

关键词： Helianthus annuus Toxicity Histopathology Serum biochemistry

Predictive models for mild cognitive impairment to Alzheimer's disease conversion

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Neural Regeneration Research 2021年第9期16卷 1766-1767页

作者： Konstantina Skolariki Graciella Muniz Terrera samuel o.Danso Bioinformatics and Human Electrophysiology Laboratory Ionian UniversityCorfuGreece Centre for Dementia Prevention University of EdinburghUK Division of Neuroimaging Centre for Clinical Brain Sciences and Edinburgh ImagingUniversity of EdinburghScotlandUK

Alzheimer's disease(AD) is an irreversible and progressive neurodegenerative disease as well as the most common form of dementia. It usually affects the older population, but early onset AD is still possible(Ritchie e... 详细信息

关键词： Alzheimer al. impairment

CFD evaluation of pressure drop across a 3-D filter housing for industrial gas turbine plants

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Frontiers in Energy 2016年第2期10卷 192-202页

作者： Fidelis I. ABAM samuel o. EFFIoM olayinka S. oHUNAKIN Department of Mechanical Engineering Michael Okpara University ofAgriculture Umudike Umuahia 02155 Nigeria Department of Mechanical Engineering Cross River University ofTechnology Calabar 540252 Nigeria Department of Mechanical Engneering Covenant Universiy Ota 11 O01Nigeria

This paper investigated the flow distribution and total pressure drop across a designed 3-D filter housing integrated with a 3-stage filtration system using computa- tional fluid dynamics （CFD）. The filter housing model was proposed for a heavy-duty industrial gas turbine plant operating at an average ambient temperature of 20℃.The pressure drops across the classes of filters were 652.8 Pa, 2692.2 Pa, 887.8 Pa, 776.2 Pa and 2304.2 Pa for I-GB, GB-GA, GA-FA, FA-HA, and HA-o, respectively. The results obtained indicated an acceptable total pressure drop of 7.2% for the entire filter housing before filter clean-up. Although the CFD simulation result shows that small outlet flow velocity and transonic flows exist at the outlet of the filter housing, the designed filter housing was proved compatible with the studied GT, for inlet flow conditions between 600≤ Wair≤610 kg/s and 60≤Vair≤70 m/s for the air flow rate and velocity, respectively. Furthermore, the designed filter housing could be adopted for the studied GT and locations of Usan and Maiduguri in Nigeria, and other locations with similar environmental conditions.

关键词： computational fluid dynamics (CFD) pressure drop flow distribution filter housing gas turbine