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The effect of prestress force magnitude and eccentricity on the natural bending frequencies of uncracked prestressed concrete beams

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JOURNAL OF SOUND AND VIBRATION 2016年 365卷 22-44页

作者： Noble, Darragh Nogal, Maria O'Connor, Alan Pakrashi, Vikram Trinity Coll Dublin Dept Civil Struct & Environm Engn Dublin 2 Ireland Natl Univ Ireland Univ Coll Cork Dynam Syst & Risk Lab Civil & Environm Engn Sch Engn Cork Ireland

This paper describes the outcome of static 3-point bending testing and output-only experimental modal analysis on 9 post-tensioned concrete beams. Static 3-point bending testing and dynamic impact testing were conducted on each of the 9 beams at different levels of post-tensioning force. The Fast Fourier Transform (FFT) was implemented on the dynamic accelerometer impact data, and the fundamental frequencies of the simply supported post-tensioned concrete beams were determined by a peak-picking algorithm at each post-tensioning load level. The tests were repeated 10 times at each impact location to ensure repeatability of the experiment. There were 3 impact locations per post-tensioning load level, and there were 11 post-tensioning load levels at which the beams were tested. A first-order linear regression model was then applied to the measured fundamental bending frequencies with increasing post-tensioning load. Statistical significance tests were subsequently conducted on the recorded data to determine if any statistically significant changes in fundamental bending frequency with increasing post-tensioning load was observed, for both static and dynamic results. The results obtained for the static 3-point bending tests were then compared and contrasted with the results obtained from dynamic testing. No statistically significant relationship between natural frequency and post-tensioning load level was found for these uncracked concrete beams. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Output-only Experimental modal analysis Post-tensioned concrete linear regression modelling Fundamental bending frequency 3-point bending tests

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Comparison of nongradient methods with hybrid Taguchi-based epsilon constraint method for multiobjective optimization of cylindrical fin heat sink

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2012年第9-12期63卷 1081-1094页

作者： Devi, S. Prasanna Manivannan, S. Rao, K. Suryaprakasa Apollo Engn Coll Dept Comp Sci & Engn Chennai Tamil Nadu India Dr MGR Educ & Res Inst Univ Dept Elect & Instrumentat Engn Chennai Tamil Nadu India Anna Univ Dept Ind Engn Chennai 600025 Tamil Nadu India

The primary aim of the paper is to compare the different nongradient methods of multiobjective optimization for optimizing the geometry parameters of a cylindrical fin heat sink. The methods studied for comparison are Taguchi-based grey relational analysis, epsilon (epsilon) constraint method and genetic algorithm. The various responses that have been studied are electromagnetic emitted radiations, thermal resistance and mass of the heat sink. Since the responses are obtained using complex simulation softwares (HFSS-Ansoft for emitted radiations and CFD-Flotherm for thermal resistance), there is no way of calculating the derivates of the objective functions. Hence, the Taguchi design of experiments design is used to derive the linear regression equations for the responses studied, which are then taken as the objective functions to be optimized. A new hybrid method known as Taguchi-based epsilon constraint method has been proposed in this paper for obtaining nondominated Pareto solution set. The results obtained using the proposed method show that the Pareto optimal set is competitive in terms of diversity of the solutions obtained. It is not likely that there exists a solution, which simultaneously minimizes all the objectives using any of the multiobjective techniques implemented. The value path analysis has been done to compare the trade-off among the design alternatives for the chosen multiple objective parameter optimization problem.

关键词： Multiobjective design optimization Heat sink linear regression modelling Taguchi design of experiments epsilon-Constraint method Grey relational analysis Genetic algorithm Taguchi-based epsilon (epsilon) constraint method

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Exploratory Data Analysis for Data Center Energy Management 13

Exploratory Data Analysis for Data Center Energy Management

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13th ACM International Conference on Future Energy Systems (E-Energy)

作者： Khan, Wania De Chiara, Davide Kor, Ah-Lian Chinnici, Marta Leeds Beckett Univ Leeds W Yorkshire England ENEA CR Portici Piazzale Enrico Fermi 1 I-80055 Naples Italy ENEA CR Casaccia Via Anguillarese 301 I-00123 Rome Italy

ISBN: (纸本)9781450393973

The continuous improvement in energy efficiency of existing data centers would help reduce their environmental footprints. Greening of Data Centers could be attained using renewable energy sources or more energy efficient compute systems and effective cooling systems. A reliable cooling system is necessary to generate a persistent flow of cold air to cool servers that are subjected to increasing computational load demand. As a matter of fact, servers' dissipated heat effects a strain on the cooling systems and consequently, on electricity consumption. Generated heat in the data center is categorized into different granularity levels namely: server level, rack level, room level, and data center level. Several datasets are collected at ENEA Portici Data Center from CRESCO 6 cluster - a High-Performance Computing Cluster. The cooling and environmental aspects of the data center is also considered for data analysis. This research aims to conduct a rigorous exploratory data analysis on each dataset separately and collectively followed in various stages. This work presents descriptive and inferential analyses for feature selection and extraction process. Furthermore, a supervised Machine learning modelling and correlation estimation is performed on all the datasets to abstract relevant features. that would have an impact on energy efficiency in data centers.

关键词： Data Center HPC Data Mining Big Data Thermal Hotspot Cooling Thermal Management Descriptive Analysis Inferential Statistics linear regression modelling Data Analysis

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Long-Term Seasonal and Annual Rainfall Trend Analysis of Giridih District, Jharkhand, India

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ASIAN JOURNAL OF WATER ENVIRONMENT AND POLLUTION 2024年第4期21卷 73-81页

作者： Gupta, Bashabi Aggarwal, Seema Jose, Milu Maria Univ Delhi Dept Geog Miranda House Delhi India Univ Delhi Dept Comp Sci Miranda House Delhi India Univ Delhi North East Reg Res & Resource Ctr Miranda House Delhi India

District Giridih is primarily rain dependent on its 95 per cent net cultivable land under summer-monsoon crops. It is classified as a mono-cropping area as it lacks irrigation facilities, essential for winter crops. In the last few years, the district experienced water stress due to the shortage of monsoon rainfall. We study long term seasonal and annual rainfall trend analyses for the Giridih district of Jharkhand in India using linear regression modelling. The last 100 years of data were taken for the study and were divided into two-time phases of 50 years each to analyse the changing pattern of rainfall trends. We found a decreasing trend in monsoon rainfall from 1 mm y(-1) to 3 mm y(-1) between the initial (1921-1971) and final (1972-2021) phase of the study period. Similarly, the return period of droughts (rainfall deficit years) has also reduced from 11 years to 5 years. The study has shown that the rainfall pattern has changed, with the winter months showing a decrease and the pre-monsoon months an increase in their relative contributions to the annual rainfalls. The study may help in the formulation of water resource conservation-oriented decision-making to cope-up with the rainfall uncertainties and meet the future water demand.

关键词： Giridih climate change trend analysis linear regression modelling

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OUTPUT ONLY INVESTIGATION OF THE EFFECT OF POST-TENSIONING FORCE ON NATURAL FREQUENCIES OF POST-TENSIONED CONCRETE BEAMS 6

OUTPUT ONLY INVESTIGATION OF THE EFFECT OF POST-TENSIONING F...

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6th International Operational Modal Analysis Conference (IOMAC)

作者： Noble, Darragh Nogal, Maria O'Connor, Alan John Pakrashi, Vikram Univ Dublin Trinity Coll Dept Civil Struct & Environm Engn Dublin Ireland Natl Univ Ireland Univ Coll Cork Dept Civil & Environm Engn Cork Ireland

ISBN: (纸本)9788416046805

This paper describes the outcome of output only experimental modal analysis on 9No. post-tensioned concrete beams. Dynamic impact testing was conducted on each of the 9No. beams at different levels of post-tensioning force. The Fast Fourier Transform (FFT) was implemented on accelerometer impact data, and the fundamental frequencies of the simply supported post-tensioned concrete beams were determined by a peak-picking algorithm at each post-tensioning load level. The tests were repeated 10 times at each impact location to ensure repeatability of the experiment. There were 3 impact locations per post-tensioning load level, and there were 11 post-tensioning load levels at which the beams were tested. A first-order linear regression model was then applied to the measured fundamental bending frequencies with increasing post-tensioning load. Statistical significance tests were then conducted on the recorded data to determine if any statistically significant changes in fundamental bending frequency with increasing post-tensioning load was observed. This problem is particularly important in the field of prestressed concrete bridge girders and more recently for pre-cast post-tensioned concrete wind turbine towers, both of which are structures that may be susceptible to extreme dynamic loading over their design life. Structural engineers should thus be able to monitor or estimate changes in the dynamic properties of PSC structures over the course of their design life to ensure their safety and serviceability.

关键词： Output-only Experimental modal analysis Post-tensioned concrete linear regression modelling Fundamental bending frequency

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Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data

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REMOTE SENSING 2019年第18期11卷 2105-2105页

作者： Berninger, Anna Lohberger, Sandra Zhang, Devin Siegert, Florian Remote Sensing Solut GmbH Dingolfinger Str 9 D-81673 Munich Germany Ludwig Maximilians Univ Munchen Dept Biol Grasshaderner Str 2 D-82152 Planegg Martinsried Germany AUG Signals Ltd AUG 73 Richmond St WestSuite 103 Toronto ON M5H 4E8 Canada

Indonesia's landscape is strongly characterized by degradation and deforestation, which results in carbon release. This makes Indonesia one of the largest carbon sources worldwide. The study at hand, investigates monitoring of canopy height and above-ground biomass (AGB) from space in Indonesian tropical forests. Using data from 2015, the canopy height and AGB were modelled in Kalimantan based on quad-pol Pol-InSAR data from RADARSAT-2 (RS-2) and dual-pol Pol-InSAR data from TerraSAR-X (TS-X). Novel algorithms utilizing the Random Volume over Ground (RVoG) interferometric model and the Random Motion over Ground (RMoG) interferometric model were tested to obtain a more accurate and robust forest parameter estimation during dry weather conditions. As a reference for modelling canopy height and AGB, extensive field inventory as well as LiDAR and drone data collected in Kalimantan were used. The RMoG model-based height inversion algorithm led to more accurate results for canopy height than the RVoG model. Using RS-2 imagery, the independent validation displayed a coefficient of determination (R-2) of 0.63 and a slight overestimation for the modelled canopy height. The modelled canopy height from TS-X data achieved an R-2 of up to 0.66 and resulted in underestimated modelled canopy height. The resulting AGB estimation based on the modelled canopy height resulted in an R-2 of 0.83 for RS-2 data and 0.84 for TS-X data. The results of the different tested images varied since the acquisition parameters and the weather conditions changed during acquisitions. It can be concluded, that not all RS-2 and TS-X data is suitable for modelling canopy height from coherence. The parameters that most affect the canopy height model were identified as the baselines (temporal and perpendicular), HoA (height of ambiguity), incident angle and moist weather conditions, as well as the wavelength. Ascending and descending flight directions did not display influence. Globally available high-reso

关键词： TerraSAR-X RADARSAT-2 carbon Pol-InSAR Random Volume over Ground (RVoG) Random Motion over Ground (RMoG) linear regression modelling Indonesia peat swamp forest

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Machine learning as new approach for predicting of maxillary sinus volume, a sexual dimorphic study

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JOURNAL OF RADIATION RESEARCH AND APPLIED SCIENCES 2023年第2期16卷

作者： Hamd, Zuhal Y. Aljuaid, Hanan Alorainy, Amal., I Osman, Eyas G. Abuzaid, Mohamed Elshami, Wiam Elhussein, Nagwan Gareeballah, Awadia Pathan, Refat Khan Naseer, K. A. Khandaker, Mayeen Uddin Ahmed, Wegdan Princess Nourah Bint Abdulrahman Univ Coll Hlth & Rehabil Sci Radiol Sci Dept POB 84428 Riyadh 11671 Saudi Arabia Princess Nourah Bint Abdulrahman Univ PNU Coll Comp & Informat Sci Comp Sci Dept POB 84428 Riyadh 11671 Saudi Arabia Shaqra Univ Appl Coll Shaqra 11961 Saudi Arabia Univ Sharjah Coll Hlth Sci Med Diagnost Imaging Sharjah U Arab Emirates Univ Hail Coll Appl Med Sci Dept Diagnost Radiol Hail Saudi Arabia Taibah Univ Fac Appl Med Sci Dept Diagnost Radiol Technol Al Madinah Al Munawara Saudi Arabia Sunway Univ Sch Engn & Technol Dept Comp & Informat Syst Bandar Sunway 47500 Selangor Malaysia Farook Coll Autonomous Dept Phys Kozhikode 673632 India Sun Way Univ Ctr Appl Phys & Radiat Technol Sch Engn & Technol Bandar 47500 Selangor Malaysia Daffodil Int Univ Fac Sci & Informat Technol Dept Gen Educ Dev DIU Rd Dhaka 1341 Bangladesh Alzaiem Alazhari Univ Fac Radiol Sci & Med Imaging Khartoum Sudan Natl Univ Coll Med Dept Anat Khartoum Sudan

The maxillary sinus is the most prominent in humans. Maxillary Sinus Volume (MSV) has grown in popularity as a tool to predict the success of various dental procedures and oral surgeries and determine a person's gender in cases such as forensic investigations when only partial skulls are available. Because it is an irregularly shaped cavity that may be difficult to measure manually, robust imaging techniques such as cone-beam computed to-mography (CBCT) used in conjunction with machine learning (ML) algorithms may offer quick and vigorous ways to make accurate predictions using sinus data. In this retrospective study, we used data from 150 patients with normal maxillary sinuses to train and evaluate a Python ML algorithm for its ability to predict MSV from basic patient demographics (age, gender) and sinus length measurements in three directions (anteroposterior, mediolateral, and superoinferior). The model found sinus length measurements had significantly higher pre-dictive values than either age or gender and could predict MSVs from these length measurements with almost linear accuracy indicated by R-squared values ranging from 0.97 to 0.98% for the right and left sinuses.

关键词： Sexual dimorphism Maxillary sinus linear regression modelling Machine learning

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