"Surrogate infill criteria for operational fatigue reliability analysis" presented at IALCCE2018 by Rui Teixeira
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Analysis of Offshore Wind Turbine (OWT) fatigue damage is an intense, resource demanding task. While the current methodologies to design OWT to fatigue are quite limited in the way and amount of uncertainty they can account for, they still represent a relevant share of the total effort needed in the OWT design process. The robustness achieved in the design process is usually limited. To enable OWT to be more robust, an innovative methodology that tackles current limitations using a balanced amount of designing effort was developed. It consists of generating a short-term fatigue damage (DSH ) using a Kriging surrogate model that accurately accounts for uncertainty using an adaptive approach. The current paper discusses the application of a reinterpolation convergence to build a Kriging surrogate model that replicates DSH in OWT tower components. Different variables involved in the convergence are discussed. The discussion extends then to how the design could be improved by using different convergence scenarios for the Kriging surface. Cross-validation is used to train and validate the surrogate surface. The main goal is to give the designer a rationale on the trade-off between computational time and accuracy using the mentioned approach to design robust OWT towers. Results show that on a design basis two levels of approach may be efficient. In the first, if a very high computational cost is expected, a trade-off between accuracy and computational time must be considered and then, if the intention is to check how robust the current design is, a full convergence of the surface should be pursued.
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Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Unit 4 GPS infinitesimal strain analysis presentation
The document discusses using GPS data from three non-collinear sites to investigate crustal strain. It describes defining a triangle between the sites, calculating total site velocities, and subtracting a translation vector to isolate the strain signal associated with changes in the shape of the triangle over time. The major and minor axes of the resulting strain ellipse indicate the orientation and magnitude of extensional and compressional crustal strain.
Performance_and_Cost_Evaluation
The success of the Cloud computing paradigm, together with the increase of Cloud providers and optimized Infrastructure-as-a-Service (IaaS) offerings have contributed to a raise in the number of research and industry communities that are strong supporters of migrating and running their applications in the Cloud. Focusing on eScience simulation-based applications, scientific workflows have been widely adopted in the last years, and the scientific workflow management systems have become strong candidates for being migrated to the Cloud. In this research work we aim at empirically evaluating multiple Cloud providers and their corresponding optimized and non-optimized IaaS offerings with respect to their offered performance, and its impact on the incurred monetary costs when migrating and executing a workflow-based simulation environment. The experiments show significant performance improvements and reduced monetary costs when executing the simulation environment in off-premise Clouds.
PORTFOLIO
The document discusses several projects involving GIS and utility network design. It describes designing a water utility network for Abu Dhabi using AutoCAD Map 3D, which allows for GIS analysis. It also mentions creating a digital elevation model for a project in Hunza Lake from contour lines, river data, and elevation points to calculate solar radiation values. Finally, it discusses a final school project that developed a servlet to calculate solar radiation at points by considering factors like view shed, DEM, and sun angles.
Determination of wind energy potential of campus area of siirt university
In this study, wind energy potential of Siirt
University campus area is statistically examined by using the mean hourly wind speed data between 2014
and 2015 years which are measured by Vantage Pro2 device, located at the roof of the Engineering Faculty building with 6 m altitude. Weibull distribution
function and Rayleigh distribution function are used
as statistical approach to evaluate the wind data. Weibull distribution function is examined by using two different methods that are maximum likelihood estimation and Rayleigh method. The determination
coefficient (R2) and Root Mean Square Error (RMSE) values of these methods are compared. According the error analysis, it is indicated that the Rayleigh method
gives better results. Wind speed and wind power density are calculated in pursuance of Weibull distribution parameters. The results are evaluated as
monthly and annually. Hence, this preliminary study is made to determine the wind energy potential of Siirt University campus area.
Matching base shear in Etabs 2016
Base shear is the maximum expected lateral force at the base of a structure due to seismic activity. It depends on soil conditions, proximity to faults, structure properties, and total weight. ETABS compares the dynamic base shear from response spectrum analysis to 85% of the static base shear. If dynamic is less than 85% of static, the scale factor is adjusted so that dynamic equals 85% of static and analysis is rerun. The document provides steps to match base shear in ETABS by modifying the scale factor if needed.
2014 PV Performance Modeling Workshop: Optimizing PV Designs with HelioScope:...
2014 PV Performance Modeling Workshop: Optimizing PV Designs with HelioScope:...Sandia National Laboratories: Energy & Climate: Renewables
2014 PV Performance Modeling Workshop: Optimizing PV Designs with HelioScope: Paul Gibbs, Folsom Labs25 pvpmc workshop(u iowa)
The document summarizes research presented at a workshop on modeling bifacial PV performance using ray tracing. It discusses how installation parameters like tilt angle, height, and albedo impact energy yield and bifacial gain. System size was also found to impact performance, with the middle module in a multi-row array generating around 7% less energy than a single module. Simulation of an array at Sandia showed good agreement with field measurements. Future work will include additional validation under different weather conditions and analyzing shading impacts over time.
IRJET- Study of Real Time Kinematica Survey with Differential Global Position...
1) The document discusses using real time kinematic (RTK) surveying with differential global positioning systems (DGPS) to improve surveying accuracy from 15 meters to 10 centimeters.
2) RTK uses a fixed base station that transmits correction data to a rover to reduce positioning errors. Accuracy is improved up to 20km from the base station.
3) The study involved taking 27 point readings using RTK surveying in Tippani and creating an AutoCAD plan from the DGPS data to compare accuracy and efficiency to traditional surveying methods. DGPS was found to be faster, reduce human error, and only require open sky versus line of sight for total stations.
33 freeman modelling_energy_losses_due_to_snow_on_pv_systems
33 freeman modelling_energy_losses_due_to_snow_on_pv_systemsSandia National Laboratories: Energy & Climate: Renewables
The document discusses modeling energy losses from snow on photovoltaic (PV) systems using the System Advisor Model (SAM). It describes a snow loss model implemented in SAM that estimates snow coverage over PV modules based on factors like system tilt, irradiance, temperature and snow depth. The model was validated against measurements from two PV systems, showing much better accuracy when including snow losses. National modeling for the U.S. estimated average snow losses by region and their correlation with total snow depth. Future work may consider snow losses for tracking systems or improving accuracy at shorter timescales.Earned schedule - concept and technique
The relatively new concept of #EarnedSchedule explained by Whizible PMP as a part of the #projectmanagementtraining series. Useful for #projectmanagers and PMO. Also useful for PMP exam as per PMBOK version 6
2015 NWA poster
This document summarizes a study that expanded on previous research to develop statistical models for ultra short-term forecasting of temperature and wind speed using data from 23 weather stations. The models used stepwise regression to select the most powerful predictors at different lead times. Results showed the statistical forecasting system had a small but positive skill score compared to persistence for forecasts up to 30 minutes for both temperature and wind speed, demonstrating the value of past observations for ultra short-term forecasting, though skill dropped off after 30 minutes.
TH3.TO4.3.ppt
The document describes a new algorithm for producing hemispherical snow water equivalent (SWE) products that assimilates weather station snow depth observations and spaceborne microwave data. The algorithm integrates snow clearance data and auxiliary forest coverage data to improve upon traditional methods. Over a 30-year time series, the assimilation of different data sources provides more accurate SWE estimates than interpolation alone, especially in areas with sparse weather station data. Validation shows the new product typically increases SWE accuracy compared to background kriging interpolation fields. The resulting 30-year SWE dataset for the Northern Hemisphere is available online.
24 mavromatakis vignola_spectral_corrections_for_pv_performance_modelling
24 mavromatakis vignola_spectral_corrections_for_pv_performance_modellingSandia National Laboratories: Energy & Climate: Renewables
This document discusses using spectral corrections to better model PV performance. It presents an overview of how the spectral distribution of sunlight changes over the day and affects PV module performance. Models that account for the spectral response of modules and changing spectral irradiance can provide more accurate estimates of performance metrics like current and power output. The document shares results of analyzing spectral data that demonstrate variations in average module response under direct normal, diffuse horizontal, and global irradiance over the course of a day due to these spectral effects. Future work aims to refine estimates of air mass effects and integrate spectral modeling into broader PV modeling.What's hot (20)
63 matthiss comparison_of_pv_system_and_irradiation_models
63 matthiss comparison_of_pv_system_and_irradiation_models
25 ben duck_improved_prediction_of_site_spectral_impact
25 ben duck_improved_prediction_of_site_spectral_impact
Optimal combinaison of CFD modeling and statistical learning for short-term w...
Optimal combinaison of CFD modeling and statistical learning for short-term w...
1 1 kankiewicz_sandia_epri_pv_perf_wrk_shp_presentation_2016
1 1 kankiewicz_sandia_epri_pv_perf_wrk_shp_presentation_2016
Scalable verification of a generic end around-carry adder for floating-point ...
Scalable verification of a generic end around-carry adder for floating-point ...
Unit 4 GPS infinitesimal strain analysis presentation
Unit 4 GPS infinitesimal strain analysis presentation
Determination of wind energy potential of campus area of siirt university
Determination of wind energy potential of campus area of siirt university
2014 PV Performance Modeling Workshop: Optimizing PV Designs with HelioScope:...
2014 PV Performance Modeling Workshop: Optimizing PV Designs with HelioScope:...
IRJET- Study of Real Time Kinematica Survey with Differential Global Position...
IRJET- Study of Real Time Kinematica Survey with Differential Global Position...
33 freeman modelling_energy_losses_due_to_snow_on_pv_systems
33 freeman modelling_energy_losses_due_to_snow_on_pv_systems
24 mavromatakis vignola_spectral_corrections_for_pv_performance_modelling
24 mavromatakis vignola_spectral_corrections_for_pv_performance_modelling
Similar to "Surrogate infill criteria for operational fatigue reliability analysis" presented at IALCCE2018 by Rui Teixeira
Reliability Constrained Unit Commitment Considering the Effect of DG and DR P...
Due to increase in energy prices at peak periods and increase in fuel cost, involving Distributed Generation (DG) and consumption management by Demand Response (DR) will be unavoidable options for optimal system operations. Also, with high penetration of DGs and DR programs into power system operation, the reliability criterion is taken into account as one of the most important concerns of system operators in management of power system. In this paper, a Reliability Constrained Unit Commitment (RCUC) at presence of time-based DR program and DGs integrated with conventional units is proposed and executed to reach a reliable and economic operation. Designated cost function has been minimized considering reliability constraint in prevailing UC formulation. The UC scheduling is accomplished in short-term so that the reliability is maintained in acceptable level. Because of complex nature of RCUC problem and full AC load flow constraints, the hybrid algorithm included Simulated Annealing (SA) and Binary Particle Swarm Optimization (BPSO) has been proposed to optimize the problem. Numerical results demonstrate the effectiveness of the proposed method and considerable efficacy of the time-based DR program in reducing operational costs by implementing it on IEEE-RTS79.
Decomposition coordinating method for the solution of a multi-area power syst...
The use of renewable energy sources such as wind can reduce the emission of atmospheric gases and fuel consumption (Wang & Singh, 2008). The integration of wind turbines to the existing thermal generating units can also introduce challenges in balancing of the power system generation.
Wind energy can reduce tremendously the life span of thermal generators while these units play a vital role by functioning as reserves in compensation of the wind uncertainties.Power system generations areas interconnect because interconnected areas are more reliable and they can be operated at minimum cost than isolated areas.
IRJET- Optimum Design of Fan, Queen and Pratt Trusses
The document discusses the optimum design of various truss configurations including fan, queen, and Pratt trusses. The author formulates the design of these trusses as an optimization problem to minimize weight. The problem considers stress, buckling, and deflection constraints with cross-sectional area as the design variable. A sequential linear programming technique is used to solve the optimization problem. Parametric studies are performed to understand the effect of truss geometry including span, purlin spacing, truss spacing, and height on selecting the best design. The results of optimizing double fan, triple fan, modified queen, double Pratt, and triple Pratt trusses are presented and discussed.
40220140507005
This paper presents a novel approach for static transmission expansion planning and
allocation of the associated expansion costs to individual market entities in a restructured power
system. The approach seeks the optimal addition of transmission lines among the possible candidate
transmission lines minimizing the overall system costs and at the same time satisfying the system
operational and security constraints. Novelty of the approach lies in applying a widely known
technique used for overload security analysis to an area such as Transmission expansion planning.
Transmission expansion costs are allocated using distribution factors to the individual entities in a
fair and transparent manner. The results for modified Garver Test system demonstrate that the
approach with the advantage of its simplicity can be applied to transmission expansion planning and
cost allocation in restructured power system
40220140507005
This document summarizes an article from the International Journal of Electrical Engineering and Technology (IJEET) that presents a novel approach for transmission expansion planning and cost allocation in deregulated power systems. The approach seeks to optimally add transmission lines to minimize costs while satisfying operational and security constraints. It applies an overload security analysis technique to transmission expansion planning. Transmission expansion costs are allocated to individual market participants using distribution factors in a fair manner. The approach is demonstrated on the modified Garver test system and is shown to be effective for transmission expansion planning and cost allocation in restructured power systems.
Review of Steady-state Building Heat Transfer Algorithms Developed for Climat...
This document discusses steady-state heat transfer algorithms developed for calculating the Overall Thermal Transmittance Value (OTTV) in building envelopes for different climate zones in India. It provides an overview of the different approaches used to develop OTTV algorithms, including energy simulation, parametric studies, and regression analysis. The paper reviews several OTTV algorithms incorporated in the building energy codes of countries like Singapore, Malaysia, Hong Kong, Pakistan, Sri Lanka, and Jamaica. While OTTV methods have limitations and do not fully capture dynamic thermal behavior, they remain important for building energy codes in developing countries due to their simplicity, low computational requirements, and ease of use.
Siad el quliti economic scheduling the construction of electric transmission
This document discusses using dynamic programming to schedule construction of electric transmission/distribution substations in Jeddah City over a 10-year period to minimize total costs. Electric load was forecasted using regression and neural networks. A dynamic model was formulated with the objective of minimizing investment and operating costs given budget constraints. Parametric analysis showed the optimal solution of 3 substations per year was robust except for extreme changes in costs. Future research areas include incorporating time value of money and simultaneous parameter changes.
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...
This Paper is an attempt to develop the expansion-planning algorithm using meta heuristics algorithms. Expansion Planning is always needed as the power demand is increasing every now and then. Thus for a better expansion planning the meta heuristic methods are needed. The cost efficient Expansion planning is desired in the proposed work. Recently distributed generation is widely researched to implement in future energy needs as it is pollution free and capability of installing it in rural places. In this paper, optimal distributed generation expansion planning with Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) for identifying the location, size and type of distributed generator for future demand is predicted with lowest cost as the constraints. Here the objective function is to minimize the total cost including installation and operating cost of the renewable DGs. MATLAB based `simulation using M-file program is used for the implementation and Indian distribution system is used for testing the results.
Determining the Pareto front of distributed generator and static VAR compens...
The integration of distributed generators (DGs), which are based on renewable energy sources, energy storage systems, and static VAR compensators (SVCs), requires considering more challenging operational cases due to the variability of DG production contributed by different characteristics for different time sequences. The size, quantity, technology, and location of DG units have major effects on the system to benefit from the integration. All these aspects create a multi-objective scope; therefore, it is considered a multi-objective mixed-integer optimization problem. This paper presents an improved multi-objective salp swarm optimization algorithm (MOSSA) to obtain multiple Pareto efficient solutions for the optimal number, location, and capacity of DGs and the controlling strategy of SVC a radial distribution system. MOSSA is a bio-inspired optimizer based on swarm intelligence techniques and it is used in finding the optimal solution for a global optimization problem. Two sets of objective functions have been formulated minimizing DGs and SVC cost, voltage violation, energy losses, and system emission cost. The usefulness of the proposed MOSSA has been tested with the 33-bus and 141-bus radial distribution systems and the qualitative comparisons against two well-known algorithms, multiple objective evolutionary algorithms based on decomposition (MOEA/D), and multiple objective particle swarm optimization (MOPSO) algorithm.
Optimal Siting of Distributed Generators in a Distribution Network using Arti...
Distributed generation (DG) sources are being installed in distribution networks worldwide due to their numerous advantages over the conventional sources which include operational and economical benefits. Random placement of DG sources in a distribution network will result in adverse effects such as increased power loss, loss of voltage stability and reliability, increase in operational costs, power quality issues etc. This paper presents a methodology to obtain the optimal location for the placement of multiple DG sources in a distribution network from a technical perspective. Optimal location is obtained by evaluating a global multi-objective technical index (MOTI) using a weighted sum method. Clonal selection based artificial immune system (AIS) is used along with optimal power flow (OPF) technique to obtain the solution. The proposed method is executed on a standard IEEE-33 bus radial distribution system. The results justify the choice of AIS and the use of MOTI in optimal siting of DG sources which improves the distribution system efficiency to a great extent in terms of reduced real and reactive power losses, improved voltage profile and voltage stability. Solutions obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm optimization (PSO) solutions for the same objective function.
sensors-23-04512-v3.pdf
This document discusses a study that uses a hybrid CNN-LSTM attention model with quantile regression to predict faults in electrical machines by analyzing time series sensor data. The model aims to better manage uncertainties in the data compared to traditional models. Researchers collected vibration data from sensors on a real electrical machine measuring variations in three axes. They preprocessed the data using empirical wavelet transform and Savitzky-Golay filtering to extract relevant features and reduce noise. The hybrid deep learning model was trained on this data and used with quantile regression and anomaly detection algorithms to predict faults and provide probability levels to machine operators. The study aims to help optimize maintenance scheduling and improve electrical machine performance.
eni_Rossi Gianmarco - Energy Management System for the Optimization of the Up...
The document discusses developing an energy efficiency monitoring system for upstream oil and gas plants. It involves creating an energy system model using production data to estimate energy requirements and key performance indicators. Scenarios are developed like "business as usual" and "clean but not sparkling" to examine different strategies' impacts on energy intensity and emissions. The model shows potential savings from initiatives like compressor optimization, thermal energy recovery, and on-site electricity generation. Overall the analysis aims to finalize an innovative monitoring and optimization system to help achieve sustainability targets and reduce energy use.
Towards Exascale Engine Simulations with NEK5000
In this deck from the HPC User Forum in Detroit, Muhsin Ameen from Argonne National Laboratory presents: Towards Exascale Engine Simulations with NEK5000.
"High-order methods have the potential to overcome the current limitations of standard CFD solvers. For this reason, we have been developing and improving the spectral element code NEK5000 for more than 30 years now. It features state-of-the-art, scalable algorithms that are fast and efficient on platforms ranging from laptops to the world’s fastest computers. Applications span a wide range of fields, including fluid flow, thermal convection, combustion and magnetohydrodynamics. Our user community includes over 400+ scientists and engineers in academia, laboratories and industry."
Watch the video: https://wp.me/p3RLHQ-j7R
Learn more: https://nek5000.mcs.anl.gov/
and
http://hpcuserforum.com
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
A COMPARATIVE STUDY ON DYNAMIC ANALYSIS OF MULTI- STORIED BUILDING (G+24) WIT...
This document compares the dynamic analysis of a 24-story building with vertical plan irregularities using STAAD Pro and ETABS software. The building models are created in both software using the response spectrum method. Results for maximum displacement, peak story shear, and frequencies are obtained and compared. Both software produce similar results for displacement and story shear. There is negligible variation in calculated frequencies. The document concludes that ETABS is more user-friendly and time-saving for modeling and dynamic analysis of multi-story buildings.
IRJET- Wind Energy Storage Prediction using Machine Learning
The document discusses using machine learning to predict hourly wind power generation at 7 wind farms based on historical wind speed and direction data. It aims to help utilities better incorporate variable wind power generation into grid operations. It first introduces the challenges of integrating intermittent wind power and the need for accurate forecasts. It then describes the dataset and various data cleaning/preprocessing steps. Finally, it proposes using machine learning algorithms like SVR and kNN regression to generate hourly forecasts based on historical wind farm output and meteorological data from nearby turbines. The models will be evaluated based on their root mean square error.
Seismic Analysis of Reinforced Concrete Building Using Fluid Viscous Damper
The document analyzes the seismic performance of reinforced concrete buildings with and without fluid viscous dampers through modeling 4 building models in ETABS and conducting time history and response spectrum analyses. The results show that the model with dampers placed at the 3rd story performed the best in reducing response quantities like base shear and story displacements compared to the bare frame building and buildings with dampers at other story locations. Placing dampers at the 3rd story was found to be the optimal location for minimizing seismic response of the building.
Energy efficient clustering and routing optimization model for maximizing lif...
Recently, the wide adoption of WSNs (Wireless-Sensor-Networks) is been seen for provision non-real time and real-time application services such as intelligent transportation and health care monitoring, intelligent transportation etc. Provisioning these services requires energy-efficient WSN. The clustering technique is an efficient mechanism that plays a main role in reducing the energy consumption of WSN. However, the existing model is designed considering reducing energy- consumption of the sensor-device for the homogenous network. However, it incurs energy-overhead (EO) between cluster-head (CH). Further, maximizing coverage time is not considered by the existing clustering approach considering heterogeneous networks affecting lifetime performance. In order to overcome these research challenges, this work presents an energy efficient clustering and routing optimization (EECRO) model adopting cross-layer design for heterogeneous networks. The EECRO uses channel gain information from the physical layer and TDMA based communication is adopted for communication among both intra-cluster and inter-cluster communication. Further, clustering and routing optimization are presented to bring a good trade-off among minimizing the energy of CH, enhancing coverage time and maximizing the lifetime of sensor-network (SN). The experiments are conducted to estimate the performance of EECRO over the existing model. The significantperformance is attained by EECRO over the existing model in terms of minimizing routing and communication overhead and maximizing the lifetime of WSNs.
Demand forecast of PV integrated bioclimatic buildings using ensemble framework
Smart building
Ensemble predictors
Neural network
Particle swarm optimization
Bayesian model averaging
Wavelet transform
Limitations in representing innovation in energy systems models
The document discusses challenges in modeling experience curves for energy technologies. It describes the IEA's work on experience curves, including conceptual work and using experience curves exogenously in modeling. It notes challenges including separate learning curves for technology components, determining learning rates with limited data, and global versus local learning. The document also discusses modeling experience curves endogenously using piecewise linear approximations of cumulative costs.
Optimal Integration of the Renewable Energy to the Grid by Considering Small ...
In recent decades, one of the main management’s concerns of professional engineers is the optimal integration of various types of renewable energy to the grid. This paper discusses the optimal allocation of one type of renewable energy i.e. wind turbine to the grid for enhancing network’s performance. A multi-objective function is used as indexes of the system’s performance, such as increasing system loadability and minimizing the loss of real power transmission line by considering security and stability of systems’ constraints viz.: voltage and line margins, and eigenvalues as well which is representing as small signal stability. To solve the optimization problems, a new method has been developed using a novel variant of the Genetic Algorithm (GA), specifically known as Non-dominated Sorting Genetic Algorithm II (NSGAII). Whereas the Fuzzy-based mechanism is used to support the decision makers prefer the best compromise solution from the Pareto front. The effectiveness of the developed method has been established on a modified IEEE 14-bus system with wind turbine system, and their simulation results showed that the dynamic performance of the power system can be effectively improved by considering the stability and security of the system.
Similar to "Surrogate infill criteria for operational fatigue reliability analysis" presented at IALCCE2018 by Rui Teixeira (20)
Reliability Constrained Unit Commitment Considering the Effect of DG and DR P...
Reliability Constrained Unit Commitment Considering the Effect of DG and DR P...
Decomposition coordinating method for the solution of a multi-area power syst...
Decomposition coordinating method for the solution of a multi-area power syst...
IRJET- Optimum Design of Fan, Queen and Pratt Trusses
IRJET- Optimum Design of Fan, Queen and Pratt Trusses
Review of Steady-state Building Heat Transfer Algorithms Developed for Climat...
Review of Steady-state Building Heat Transfer Algorithms Developed for Climat...
Siad el quliti economic scheduling the construction of electric transmission
Siad el quliti economic scheduling the construction of electric transmission
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...
Cost Aware Expansion Planning with Renewable DGs using Particle Swarm Optimiz...
Determining the Pareto front of distributed generator and static VAR compens...
Determining the Pareto front of distributed generator and static VAR compens...
Optimal Siting of Distributed Generators in a Distribution Network using Arti...
Optimal Siting of Distributed Generators in a Distribution Network using Arti...
eni_Rossi Gianmarco - Energy Management System for the Optimization of the Up...
eni_Rossi Gianmarco - Energy Management System for the Optimization of the Up...
A COMPARATIVE STUDY ON DYNAMIC ANALYSIS OF MULTI- STORIED BUILDING (G+24) WIT...
A COMPARATIVE STUDY ON DYNAMIC ANALYSIS OF MULTI- STORIED BUILDING (G+24) WIT...
IRJET- Wind Energy Storage Prediction using Machine Learning
IRJET- Wind Energy Storage Prediction using Machine Learning
Seismic Analysis of Reinforced Concrete Building Using Fluid Viscous Damper
Seismic Analysis of Reinforced Concrete Building Using Fluid Viscous Damper
Energy efficient clustering and routing optimization model for maximizing lif...
Energy efficient clustering and routing optimization model for maximizing lif...
Demand forecast of PV integrated bioclimatic buildings using ensemble framework
Demand forecast of PV integrated bioclimatic buildings using ensemble framework
Limitations in representing innovation in energy systems models
Limitations in representing innovation in energy systems models
Optimal Integration of the Renewable Energy to the Grid by Considering Small ...
Optimal Integration of the Renewable Energy to the Grid by Considering Small ...
More from TRUSS ITN
"On the bonding performance of distributed optical fiber sensors (DOFS) in st...
Distributed optical fiber sensors (DOFS) is one of the most promising and exciting technologies under research to be applied in the structural health monitoring (SHM) of civil engineering infrastructures. Therefore, in this paper, the authors present a laboratory experiment where a reinforced concrete beam was instrumented with a 5-meter-long polyimide DOFS in a way that four equal segments were bonded to the bottom surface of the beam using for each segment a different type of adhesive. Three strain gauges were also used to compare the results. The beam was then loaded, generating expected equal levels of strain for each of the segments allowing for a direct comparison between them. In this exercise, additionally to the comparison with the other instrumented sensors, it is also important the consideration and analysis of the associated Spectral Shift Quality (SSQ) values of the DOFS measurements.
"Mechanical characterisation of braided BFRP rebars for internal concrete rei...
This study investigates the tensile behaviour of basalt fibre reinforced polymer (BFRP) composites that were developed using braiding as a manufacturing technique. Those materials will be introduced in concrete reinforcement applications. Three BFRP rebar sizes with a circular constant cross section and different braided configurations are developed and characterised with respect to their internal architecture. The braid angle on each layer of the rebar, varying from 10◦ to 45◦, is an important parameter that has a direct impact on its performance characteristics. The effective longitudinal in-plane modulus (ExFRP) of each braided sample is calculated numerically using the classical laminate theory (CLT) approach and then, tensile tests are performed according to the relevant standard. Comparisons between analytical and experimental data demonstrate a significant influence of braiding parameters, like braiding angle and number of braiding layers, on the mechanical properties of BFRP rebars. In addition, it is noteworthy that all predicted moduli determined with CLT numerical approach are found to be higher than the test results and overestimate rebar’s stiffness, most probably due to the degree of undulation from braiding process.
"Structural health monitoring of bridges: a Bayesian network approach" presen...
Between February 2016 and April 2017 seven bridges around the world collapsed suddenly, by causing fatalities and significant economic losses. Structural Health Monitoring (SHM) techniques can assess the health state of an infrastructure by analysing its behaviour, and point out degraded elements that require to be maintained. As a consequence, SHM methods can improve the safety of the transportation network, and reduce the life cycle costs of the infrastructure, by optimizing the maintenance schedule. In this paper, a Bayesian Belief Network (BBN) approach is proposed to assess the health state of a beam-and-slab bridge, by relying on the analysis of its vertical acceleration. A procedure to robustly define the Conditional Probabilities Tables (CPTs) of the BBN is proposed, by merging expert judgement with information about the bridge behaviour. The BBN allows updating the health state of the bridge when a new measurement of the bridge acceleration is available, by taking account of the health state of each element of the bridge. In this way, the degradation level of the whole bridge and of its elements is monitored over time, and unexpected behaviour of the bridge are diagnosed.
"Using step-by-step Bayesian updating to better estimate the reinforcement lo...
Probabilistic assessment of ageing structures has become an important research area as it attracts the interest from not only researchers but also investors, municipalities, and governments. The most commonly used material for many important structures and infrastructure is reinforced concrete. Various degradations of such structures are manifest in the form of direct loss of reinforcement area. In this study, a time-dependent stochastic model of the reinforcement loss (in [%]) due to corrosion is presented, which has a crucial role in the estimation of the lifetime and the time-dependent health state of the structure. Bayesian updating is applied in multiple steps during the lifetime of the structure in order to improve the estimate of the reinforcement loss. An example application is shown where updating is applied in two steps.
"Bridge condition evaluation using LDVs installed on a vehicle" presented at ...
In this paper, a structural health monitoring approach is proposed involving Laser Doppler Vibrometers (LDVs) installed on a vehicle. Relative velocities are measured to obtain the Rate of Instantaneous Curvature of the velocity (RIC). Standard deflection curvature is shown to be sensitive to local damage. Instantaneous Curvature (IC) is likewise sensitive but calculated using measurements provided from a vehicle. RIC is obtained using the first derivative of IC with respect to time.A damage indicator obtained from RIC, the Difference Ratio, is tested both in noise-free and noisy conditions.
"Outlier detection of point clouds generating from low-cost UAVs for bridge i...
Using an Unmanned Aerial Vehicle (UAV) for documentation and inspection of civil infrastructures has become increasingly popular. One area of interest is in bridge inspection as it holds the potential of being safer, more economical, and less disruptive, with respect to traffic flow. With 3D reconstruction method, structural deficiencies and 3D models can be obtained from a 3D point cloud generated from UAV imagery data. However, shadows and water reflectivity may affect the quality of the point cloud generated from images, which causes difficulty in data processing. This paper presents a detailed workflow of removing outlier data points through the statistical filter and geometric-based filter. The experimental results showed that the statistical filter gives the best performance.
"A machine learning approach for the estimation of fuel consumption related t...
Although vehicles emissions have a very significant impact on CO2 emissions, there remains a level of uncertainty concerning the methodological assumptions and parameters to consider in the calculation of greenhouse gas (GHG) emissions coming from the use phase of road pavements (Trupia et al 2016). In fact, recent studies highlighted how existing models can lead to very different results and that because of this, they are not fully ready to be implemented as standard in the life-cycle assessment (LCA) framework (Santero et al 2011; Trupia et al 2016).
This study presents an innovative approach, based on the application of Machine Learning to ‘Big Data’, for the calculation of the use phase emissions of road pavements due to truck fleet fuel consumption. The study shows that the Machine Learning regression technique is suitable to analyse the large quantities of data, coming from fleet and road asset management databases effectively, assessing and estimating the impact of rolling resistance-related parameters (pavement roughness and macrotexture measurements) on the use phase in road pavement LCA.
"Characterization of hoisting operations on the dynamic response of the lifti...
In the current paper, the impact of the hoisting operations, on the dynamic response of the lifting boom of a ship unloader, are taken into consideration. The lifting boom is used to carry out transient dynamic analysis, since it was recognized to be the single most representative element for studying the dynamic response of these structures. The response of the lifting boom was the result of dynamic analysis comprising two components: the structure (representing the waterside portion of the boom), and the applied load (expressed as different hoisting force profiles). A comparison between the different force profiles was carried out, in order to identify the parameters that mostly influence the dynamic behavior of the structure during a loading cycle. Furthermore, a baseline case based on pseudo-static analysis (as standard recommendation FEM 1987) was introduced and comparisons carried out in terms of vertical displacement and bending moments.
"Probabilistic decision basis and objectives for inspection planning and opti...
Marine and offshore engineering has long been challenged with the problem of structural integrity management (SIM) for assets such as ships and offshore platforms due to the harsh marine environments, where cyclic loading and corrosion are persistent threats to structural integrity. SIM for such assets is further complicated by the very large number of welded plates and joints, for which condition surveys by inspections and structural health monitoring become a difficult and expensive task. Structural integrity of such assets is also influenced by uncertainties associated with materials, loading characteristics, fatigue degradation model and inspection method, which have to be accounted for. Therefore, managing these uncertainties and optimizing the inspection and repair activities are relevant to improvements in SIM. This paper addresses probabilistic inspection planning and optimization by comparative analysis for a typical fatigue-prone structural detail based on reliability, life cycle cost (LCC) and value of inspection information (VoI). With the objective of clarifying the differences between the theoretical basis and objectives for probabilistic inspection optimization, three maintenance strategies for the structural detail are proposed and studied. It is found that different optimal inspection times are obtained with the objectives of reliability maximization, LCC minimization and VoI maximization. Also, planned inspection and repair can help to achieve higher reliability with fewer repairs than repair without inspection (i.e. time-based replacement). If the cost of unit inspection and repair is not negligible compared with failure consequence, it is suggested to employ the optimization objective of life cycle cost minimization, which considers the costs of SIM. The paper proposes a simple approach for quantifying the VoI, based on life cycle cost analysis for the three maintenance strategies. It is concluded that the VoI is relevant to both the optimal maintenance decision with and without inspection.
"Impact of input variables on the seismic response of free-standing spent fue...
Stochastic input data brings aleatoric and epistemic uncertainty to the rack seismic analysis. From the synthetic acceleration-time history of the earthquake to the heterogeneous features of the rack system, several sources of uncertainty exist. The manufacturing process itself may produce slight deviations in the dynamic properties and mass distribution of the rack units. Moreover, each unit is loaded with a different number of fuel elements according to the operation needs of the plant. Even the exact clearance spaces between units are hardly inspectable due to radioactive ambiance. Hence, all of these uncertainties propagate across the nonlinear transient analysis and affect the accuracy and robustness of the numerical outputs. This paper carries out a ‘one-factor-ata-time’ parametric analysis of five key input variables: acceleration time-history, rack mass, fuel loading, rack Eigen-frequencies and hydrodynamic masses. This technique examines the impact on the main transient outputs when an analysis parameter is systematically varied while the others remain at their nominal value. Numerical results are provided for a simple two-rack system as a source of insight into the uncertain seismic response of a real rack system. It is highlighted that the dispersion is much higher for the sliding displacements than for the maximal forces on support.
"Fatigue testing of reinforced concrete beam instrumented with distributed op...
The use of fiber optic sensors on civil engineering structural health monitoring (SHM) applications have become quite popular for the past two decades. Within this type of sensors however, the study and use of Optical Backscatter Reflectometry (OBR) based Distributed Optical Fiber Sensors (DOFS) is relatively new. In this way, there is still some uncertainty that would allow the use of this technology in a more systematic and standardized way. Some of this uncertainty is related with the long-term reliability behavior of these sensors when applied on the monitoring of a structure under a large number of load cycles. In this way, the authors conducted a laboratory experiment where a reinforced concrete beam was instrumented with a DOFS that was adhered in a way to allow the measuring of strain on four different longitudinal segments on its bottom surface. A fatigue test was then conducted on this element where the inputted load range was the one expected on a standard highway bridge between its self-weight and the additional traffic load. Furthermore, each longitudinal segment of the DOFS was adhered to the concrete using a different adhesive in order to assess the optimal one in these conditions. The obtained data is then compared with strain gauges that are also instrumented on the concrete beam.
"Nothing on the road axle detection system using direct strain measurements –...
This paper proposes a new axle detection methodology using direct strain measurements. Initially, numerical analyses are carried out on a 1-D simply supported bridge structure to investigate the strain response of a bridge to a 2-axle moving vehicle. The strain response obtained from the numerical model is further studied and a new axle detection strategy, based on the second derivative of strain with respect to time, is proposed. Having developed the theoretical concept, field testing is carried out on a single span simply supported railway bridge to validate the proposed methodology and test its robustness of on a full-scale bridge.
"Vibration-based, output-only damage identification of bridge under vehicle i...
Many traditional methods of damage identification in bridge structures implement numerical models and/or modal parameters as a means of condition assessment. While such techniques can often be effective, they may also succumb to their own intrinsic constraints, such as shortcoming in numerical model calibration to dynamic behaviour and environmental sensitivity of modal parameters. Furthermore, the degree of vibration signal non-stationarity that may be induced due to vehicle excitation can limit the applicability of some common signal processing techniques, such as Fourier transforms. The current study investigates vibration-based approaches to damage identification that circumvent some of these issues. Vibration data obtained from a real bridge structure subjected to a progressive damage test under vehicle induced excitation is used as a test subject. Novel vibration parameters obtained from the raw signals are assessed for their damage detection, localisation and quantification capabilities. Additionally, advanced Empirical Mode Decomposition (EMD) and the Hilbert-Huang Transformation (HHT) is applied to the non-stationary signals for the purpose of damage identification. The investigation shows that damage detection, localisation and quantification is achievable from the vehicle induced vibration signals using the proposed empirical techniques.
"Finding the influence line for a bridge based on random traffic and field me...
The influence line of a structure reflects its structural behaviour as well as any possible damage present on the bridge. An iterative algorithm is presented in this paper in order to obtain the shape of the influence line of a bridge together with the load distribution of trucks passing overhead. One great advantage of this approach is that sensor calibration with pre-weighed trucks can be avoided. The only initial information needed are the measurement data and a preliminary estimate of influence line based on engineering judgement. An illustrative example is shown, where strain data have been collected on a reinforced concrete culvert. Apart from the efficiency of the proposed algorithm, the influence of the temperature on the results is also shown.
"Sensitivity of SHM sensors to bridge stiffness" presented at CERI2018 by Dan...
Bridges play an important role in transport infrastructure and it is necessary to frequently monitor them. Current vibration-based bridge monitoring methods in which bridges are instrumented using several sensors are sometimes not sensitive enough. For this reason, an assessment of sensitivity of sensors to damage is necessary. In this paper a sensitivity analysis to bridge flexural stiffness (EI) is performed. A discussion between the use of strain or deflections is provided. A relation between deflection and stiffness can be set by theorem of virtual work, expressing the problem as a matrix product. Sensitivity is obtained by deriving the deflection respect to the reciprocal of the stiffness at every analysed location of the bridge. It is found that a good match between the deflection and the bridge stiffness profile can be obtained using noise-free measurements. The accuracy of sensors is evaluated numerically in presence of damage and measurement noise. Field measurements in the United States are also described to identify the potential issues in real conditions.
"Reduction of uncertainties associated to the dynamic response of a ship unlo...
Here, the TRUSS (Training in Reducing Uncertainty in Structural Safety) ITN (Innovative Training Network) Horizon 2020 project (http://trussitn.eu, 2015-19) demonstrates how the accuracy of residual life assessment predictions can be improved by achieving a good agreement between measured and predicted dynamic responses of a crane structure. Existing records of measured strain data are often missing information such as the weight of the payload, the hoisting speed and acceleration that are relevant for structural assessment purposes. This paper aims to reduce uncertainties associated with the recorded data in an aged grab ship unloader by comparing measured and non-linear transient finite element analyses results for a loading/unloading cycle. The speed pattern is determined from a best match to the measured record. The moving load consisting of ‘trolley + grab + payload’ is modelled with parameters that are derived from minimizing differences between measured and simulated responses. The determination of these loading parameters is central to accurately assess the remaining life of ship unloaders.
"A comparative study on different BFRP rebar design methodologies" presented ...
This study compares the physical properties and tensile behaviour of two different basalt fibre reinforced polymer (BFRP) rebar designs. Both types are developed using basalt fibres and epoxy resin as reinforcement and matrix respectively; composites with a constant cross section of 8 mm diameter are manufactured using a vacuum assisted resin infusion technique. The first configuration consists of eight braided layers at various angles, while the second one combines a unidirectional core with four outer braided layers. The latter hybrid design is introduced to improve the elastic modulus of braided BFRP reinforcement used in concrete structures. Tensile performance of all BFRP rebars produced in UCD laboratory is numerically and experimentally evaluated, and results for both approaches are compared. The effective longitudinal in-plane modulus (E_x^FRP) and the fibre volume fractions (φf) of each sample is calculated using the classical laminate theory and then, tensile tests are performed in accordance to the B2_ACI 440.3R-04 standard to experimentally validate the numerical results. Initial findings indicate that the elastic modulus of BFRP rebar can be enhanced by combining braiding with a unidirectional fibre core while a sufficient tensile strength is obtained, but additional research towards an optimal hybrid design is required.
"A big data approach for investigating the performance of road infrastructure...
“Using truck sensors for road pavement performance investigation” is a research project within TRUSS, an innovative training network funded from the EU under the Horizon 2020 programme. The project aims at assessing the impact of the condition of the road pavement unevenness and macrotexture, on the fuel consumption of trucks to reduce uncertainty in the framework of life-cycle assessment of road pavements. In the past, several studies claimed that a road pavement in poor condition can affect the fuel consumption of road vehicles. However, these conclusions are based just on tests performed on a selection of road segments using a few vehicles and this may not be representative of real conditions. That leaves uncertainty in the topic and it does not allow road mangers to review the current road maintenance strategies that could otherwise help in reducing costs and greenhouse gas emissions from the road transport industry. The project investigated an alternative approach that considers large quantities of data from standard sensors installed on trucks combined with information in the database of road agencies that includes measurements of the conditions of the road network. In particular, using advanced regression techniques, a fuel consumption model that can take into consideration these effects has been developed. The paper presents a summary of the findings of the project, it highlights implications for road asset management and the road maintenance strategies and discusses advantages and limitations of the approach used, pointing out possible improvements and future work.
"Statistical reliability of the screw pullout test in the assessment of in-si...
The assessment of concrete compressive strength is an essential element in assessing the load carrying capacity of structural members in an existing structure. The reliability of non-destructive tests (NDTs) results for assessing concrete strength is always a questionable issue. This is mainly due to the uncertainty associated with the strength predictions based on the NDT measurements. This paper studies the Post-installed Screw Pullout (PSP) test as a potential method for assessing in-situ concrete strength. The objective of this paper is to study the reliability of the assessment using PSP test by analysing the effects of several influencing factors: presence of coarse aggregates, types and size of coarse aggregates, and the amount of coarse and fine aggregates. Analyses of results are presented to evaluate the repeatability and reliability of the PSP test with respect to test standard deviation, coefficient of variation and RMSE. The repeatability of the screw pullout test has been compared with the other NDTs available in literature.
"Automated bridge deck evaluation through UAV derived point cloud" presented ...
Imagery-based, three-dimensional (3D) reconstructions from Unmanned Aerial Vehicles (UAVs) hold the potential to provide a safer, more economical, and less disruptive approach for bridge inspection. This paper describes a methodology using a low-cost UAV to generate an imagery-based, dense point cloud for bridge deck inspection. Structure from motion (SfM) is employed to create a three-dimensional (3D) point cloud. Outlier data are removed through a density-based filtering method. Next, the unsupervised learning algorithm k-means and an object-based region growing algorithm are compared for accuracy with respect to bridge deck extraction. Last, an automatic pavement evaluation method is proposed to estimate the deck’s pavement condition. The procedure is demonstrated through an actual case study, in which a 3D point cloud of 16 million valid points was generated from 212 images. With that data set, the region growing method successfully extracted the deck area with an F-score close to 95%, while the unsupervised learning approach only achieved 76%. In the last, to evaluate the surface condition of the extracted pavement, a polynomial surface fitting method was designed to evaluate and visualise the damages.
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"On the bonding performance of distributed optical fiber sensors (DOFS) in st...
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"Sensitivity of SHM sensors to bridge stiffness" presented at CERI2018 by Dan...
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"Surrogate infill criteria for operational fatigue reliability analysis" presented at IALCCE2018 by Rui Teixeira
- 1. Reducing Uncertainty in Structural Safety Special Session SS6 Ghent, Belgium 28-31 October 2018
- 3. Outline Introduction Offshore wind Turbine systems Stress-cycle (SN) fatigue assessment Meta-modelling of SN fatigue Search function Results and application on a reliability analysis framework
- 4. Introduction Levelized Cost of Energy (LCOE) for different sources of renewable energy divided by region. Source : IRENA 2017 report. The demand for renewable energy is unquestionable. Innovation in the practices to design and operate Offshore Wind Turbines has been the main key driver to enhance competiveness (IRENA, 2017). Research along with regulatory framework are expected to be the main enablers of OWT development up to 2050. Scale-up, where the increase of the tower component height has been a major driver of competiveness for OWTs. Ref: IRENA. Renewable power generation costs in 2017. Technical report, International Renewable Energy Agency, 2017.
- 5. Offshore wind turbine systems
- 6. OWT fatigue design IEC61400 and DNV guidelines. Run multiple time domain simulations at operational states and count stresses and cycles using counting algorithm (e.g. rainflow counting) Plus SN curve and:
- 7. Meta-modelling of SN fatigue Gaussian process regression models, or Kriging models, have seen an increase in its application to structural problems. Polynomial Component : is Gaussian process with mean 0 and covariance . . Define a surrogate of short- term SN damage:
- 8. LHS DoE Approximation Common approach in literature works. Not consistent.
- 9. Learning criteria Kriging enables notion of improvement. Relation to the physical problem of fatigue. Learning criteria.
- 10. Comparison with standard methodology Robust even when only the corner of the space were given. Convergence to the 1 year prediction.
- 11. Comparison with standard methodology Compare with the traditional binning of data. Reduction of computational time up to 80% without compromising accuracy. Reduction never inferior to 50% for all the cases studied. SN slopes of 3, 5 and double 3 and 5.
- 12. Application for reliability analysis Allows to define multiple design surfaces. Each one replicates the IEC design assessment. Distribution of design SN fatigue based on the uncertainty of the design reliability considerations. Use the noise component:
- 13. Conclusions A meta-modelling technique was successfully implemented in order to reduce the computational time of the fatigue design for OWT analysis. It uses a Gaussian process predictor to surrogate the stress-cycle fatigue damage from different operational states. It was applied to the tower component, but the same methodology can be extended to any other component. The meta-model probabilistic behaviour was of interest to define a In a reliability analysis framework, the main interest is of the surrogate approach presented is the reduction of computational time that may enable reliability based optimization procedures, which challenging to apply for SN fatigue analysis due to their cost.
- 14. The TRUSS ITN project (http://trussitn.eu) has received funding from the European Horizon 2020 research and innovation programme under the Marie -Curie grant agreement No. 642453