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Angle sensors based on the laser autocollimation are often employed to evaluate surface profiles of a target of interest. The authors have developed a femtosecond laser angle sensor, in which a spectrometer or an optical spectrum analyzer with a single-mode fiber is employed as the photodetector for simultaneous capturing of the multiple optical modes. In this paper, the concept of the femtosecond laser angle sensor is applied to evaluate the surface profile of a target of interest. An optical setup is designed in such a way that each mode in the spectrum of the mode-locked femtosecond is utilized as the laser beam to measure the local slope of a measurement target at each different point to evaluate the surface profile. Some basic experiments are carried out by using the developed optical setup with a mode-locked femtosecond laser source to evaluate basic performances of the developed optical setup as an optical angle sensor.

Confocal probes are widely employed in many industrial fields due to the depth-sectioning effect. The author’s group has also proposed a chromatic confocal probe employing a mode-locked femtosecond laser source which can realize an axial resolution of 30 nm and a measurement range of 40 μm Efforts have also been made to improve the thermal stability of the developed femtosecond laser chromatic confocal probe so that the probe can be applied for long-term displacement measurement or surface profile measurement. Meanwhile, surface profile measurement has not been carried out by using the developed femtosecond laser chromatic confocal probe. For the verification of the performance of developed probe in profile measurement, in this paper, an experimental setup is built and a basic experiment is carried out. By using the probe with further improved thermal stability, the measurement of a sample surface profile is carried out. In this paper, the development of the experimental setup with the femtosecond laser chromatic confocal probe, as well as the results of the surface profile measurements, is presented.

The growing resource shortage and environmental concerns have forced mankind to develop and utilize renewable energy sources. The penetration of solar photovoltaic (PV) power in the electricity market has been increasing over the past few decades due to its low construction costs, zero pollution nature, and enormous support from governments. However, the intermittency and randomness of PV power also cause huge grid fluctuations which limit its integration in the system. An accurate forecasting of solar PV power generation and optimization of operation and maintenance (O&M) management are essential for further development of the solar PV farms. A great number of related researches have been done in recent years. A review of PV power generation forecasting techniques together with their brief applications on the optimization of O&M management is presented in this paper. Machine learning methods are thought to be the most suitable at the present stage because of their ease of implementation and their capability in processing non-linear, complex data sets. Typical forecasting accuracy measures are summarized and further applications of PV power forecasting on the O&M management are also presented.

Bayesian statistics is a quintessential tool for model validation in many applications including smart materials, adaptive structures, and intelligent systems. It typically uses either experimental data or high-fidelity simulations to infer model parameter uncertainty of reduced order models due to experimental noise and homogenization of quantum or atomistic behavior. When heterogeneous data is available for Bayesian inference, open questions remain on appropriate methods to fuse data and avoid inappropriate weighting on individual data sets. To address this issue, we implement a Bayesian statistical method that begins with maximizing entropy. We show how this method can weight heterogeneous data automatically during the inference process through the error covariance. This Maximum Entropy (ME) method is demonstrated by quantifying uncertainty in 1) a ferroelectric domain structure model and 2) a finite deforming electrostrictive membrane model. The ferroelectric phase field model identifies continuum parameters from multiple density functional theory calculations. In the case of the electrostrictive membrane, parameters are estimated from both mechanical and electric displacement experimental measurements.

Corrective maintenance and preventive maintenance are two common maintenance strategies used in the wind farms, whose drawbacks are obvious and significant. Opportunistic maintenance strategy takes advantage of the dependencies existing among the wind turbine components and implement combined maintenance actions to reduce the huge downtime cost. The opportunistic maintenance strategy for wind turbines has made a great progress, as well as the strategy considering imperfect and condition-based maintenance. However, existing maintenance strategy researches are usually concerned with the maintenance itself and the effects of power generation are barely considered. Nowadays, a current research trend in manufacturing system is the integration of maintenance and production planning. In this paper, the effects of power generation on opportunistic maintenance strategy for wind turbines considering reliability are researched. The opportunistic maintenance reliability threshold is not constant and depends on the real-time power generation. Numerical examples are used to illustrate the economical advantages of this proposed strategy over traditional opportunistic maintenance strategy. Moreover, the optimal maintenance combination is also provided.

In this study, the uncertain free vibration of structures with hybrid (random and fuzzy) parameters is investigated. The non-deterministic Young’s modulus of structural elements is modeled as random variables while the uncertain mass density is represented by fuzzy parameters with associated membership functions. By implementing the α -sublevel strategy, the stochastic fuzzy eigenvalue problem is rigorously transformed into a series of stochastic interval analysis of natural frequencies. In this context, the Unified Interval Stochastic Sampling (UISS) is adopted such that the statistical characteristics of the upper and lower bounds of natural frequencies at each α -sublevel can be calculated. Subsequently, the membership functions of mean and standard deviations are respectively established for the extreme bounds of eigenvalues. Benefiting from the stochastic samples offered by the UISS method, the probability profiles of the uncertain natural frequencies at each α -sublevel can be identified by utilizing either parametric or nonparametric statistical inference methods. The accuracy and effectiveness of the proposed approach is demonstrated by analyzing a practically motivated 3D structure with comparison to the results obtained by the conventional Monte Carlo simulation method.

The Maximum Entropy (ME) method is shown to provide a new approach for quantifying model uncertainty in the presence of complex, heterogeneous data. This is important in model validation of a variety of multifunctional constitutive relations. For example, multifunctional materials contain field-coupled material parameters that should be self-consistent regardless of the measurement. A classical example is piezoelectricity which may be quantified from charge induced by stress or strain induced by an electric field. The proposed tools provide new statistical information to address measurement discrepancies, guide model development, and catalyze materials discovery for data fusion problems. The error between the model outputs and heterogeneous data is quantified and used to formulate a second moment constraint within the entropy functional. This leads to an augmented likelihood function that weights each individual set of data by its respective variance and covariance between each data set. As a first step, the method is evaluated on a piezoelectric ceramic to illustrate how the covariance matrix influences piezoelectric parameter estimation from heterogeneous electric displacement and strain data.

Zero-suppressed Binary Decision Diagram (ZBDD) algorithm is an advanced method in fault tree analysis, which is developing quickly in recent years and being used in the development of the Probabilistic Safety Assessment (PSA) Quantification Engine. This algorithm converts a fault tree to a ZBDD structure, solves the minimal cut sets and calculates the top node unavailability. The ordering of the basic events and logical gates is the core technique of the ZBDD algorithm, which determines the efficiency of the ZBDD conversion and the size of the ZBDD structure. A variable ordering method based on the structure of the fault tree is developed in this paper, which gives a better basic events order by compressing the fault tree; meanwhile, the method offers a logical gates order. The nodes order derived from this method can accelerate the ZBDD conversion obviously.

Minimal Cut-sets (MCS) post processing is an important part of the Probabilistic Safety Assessment (PSA) analysis. Two alternative post processing methods have been described in this paper based on traditional and Zero-suppressed Binary Decision Diagram (ZBDD) methods. The first post processing method, named the Quick MCS Post Processing Method, obtains MCS results directly from the cut-sets list using a quick sort method according to a certain set of sorting rules. The alternative post processing method, named the ZBDD Based MCS Post Processing Method, obtains MCS results from the ZBDD structure which encodes the MCS, using the ZBDD algorithm according to the post processing rules. Tests show that both of the two methods can derive the accurate MCS post processing results.

Seismic risk of nuclear power plant has drawn increasing attention after Fukushima accident. An intensive study has been carried out in this paper, including sampling of component and structure fragility based on Monte Carlo method, fragility analysis on system or plant level, convolution of seismic hazard curves and fragility curves. To derive more accurate quantification results, the binary decision diagram (BDD) algorithm was introduced into the quantification process, which effectively reduces the deficiency of the conventional method on coping with large probability events and negated logic. Seismic Probabilistic Safety Analysis (PSA/PRA) quantification software was developed based on algorithms discussed in this paper. Tests and application has been made for this software with a specific nuclear power plant seismic PSA model. The results show that this software is effective on seismic PSA quantification.

Nowadays, the management level and information construction of wind power industry are still relatively backward, for example, the existing maintenance models for wind farm are much too single, and corrective maintenance strategy is the most commonly used, which means that maintenance measures are initiated only after a breakdown occurs in the system. Moreover, the wind farm spare parts management is out-dated, no practical and accurate spares demand assessment method is available. In order to enrich the choices of maintenance methods and eliminate the subjective influence in the demand analysis of spare parts, a spare parts demand prediction method for wind farm based on periodic maintenance strategy considering combination of different maintenance models for wind farms is proposed in this paper, which consists of five major steps, acquire the reliability functions of components, establish the maintenance strategy, set the maintenance parameters, maintenance strategy simulation and spare parts demand prediction. The discrete event simulation method is used to solve the prediction model, and results demonstrate the operability and practicality of the proposed demand forecasting method, which can provide guidance for the actual operation and maintenance of wind farms.

Studies show that fusion modeling can improve the forecasting accuracy of wind power. Fusion modeling is the process of selective use of information from individual forecasting models. The reasonable evaluation of the individual models is the premise and basis of model optimization so that the individual models with high forecasting accuracy can be selected to establish the fusion model. Because the results of a single index model evaluation may not be comprehensive, the multi-index fusion evaluation method based on maximizing deviations and subjective correction is proposed. The method is applied to the selection of short-term wind power forecasting models. Firstly, this method establishes the individual model base of wind power forecasting model. Secondly, it establishes the more comprehensive evaluation index system. Thirdly, it combines maximizing deviations with the subjective correction coefficient to determine the comprehensive weight of each model, which is used to calculate the fusion evaluation value and get the evaluation order to achieve the model optimization. Finally, based on five years of data from a wind power plant in Shanxi Province, the validated experiments by multiple sets of forecasting data have been done using MATLAB in this paper. The simulation results demonstrate that the evaluation based on the proposed fusion evaluation method is more comprehensive and stable compared to evaluation using a single index. More importantly, it can effectively guide the model optimization with simple operating steps.Copyright © 2016 by ASME

With the demand of renewable energy due to the pressure from environmental pollution and global warming, the wind industry has been growing rapidly over the past decades during which the offshore wind innovation is becoming more and more attractive because of vast offshore wind resources. In this paper, a novel tapered-column semi-submersible floating foundation with economical mooring system is developed to support 6MW wind turbine in South China Sea. The coupled aero-hydro-servo-structural analysis is done in GH-Bladed software to obtain the global dynamic response of the whole floating wind turbine. By combining the derived wind loads with the wave and current induced loads, the global performances of the foundation and attached mooring system under both extreme conditions and normal operation conditions are analyzed in AQWA software. The result reveals that the floating foundation complies with the design standard and meets requirements of wind turbine. This novel patent-pending floating foundation with tapered columns is proved as a successful design with high material efficiency and good seakeeping performance. Also a reliable and efficient design methodology of floating foundation based on optimal cost is provided in this paper which can be used as design reference of floating foundations.

Merging of large-scale city fires and forest fires causes rapid acceleration of fire growth. Once a merging fire occurs, it becomes more difficult to suppress, with greater potential damages. In particular, merging fires may induce fire whirls in windy conditions. However, the details of interactions in multiple fires that cause fire merging have not been fully clarified. For the interactions in multiple fires, the inter-fire distance among fires greatly affects the merging phenomenon. The objective of this paper is to examine the detailed merging conditions, particularly the burning rate increase and total heat release rate, by numerical simulation of reduced scale fires. The burning behavior of n-heptane in n × n fire arrays is examined, using the fire simulation software, FDS by NIST. In addition, another simple model is employed. The number of array matrix, n, is varied, together with the inter-fire distance. The simulation results show that there are considerable differences between both simulations and experiments. However, the differences between the simpler simulation Method II and experiments are fewer than the simulation Method I. The following possibilities are considered: (1) The oil pan size affects the difference, but the results between simulations and experiments are so large. (2) The grid size for simulations may have some effects on the simulation results due to the resolution, (3) the experimental results may not always be precise, since the burning rates in the experiments are measured by the burn-out time and (4) the wind caused by merging fires may reduce the radiative heat flux to the adjacent fuel. The relationship between flame length and burning rate and the relationship between flame length and radiative heat flux are well-correlated.Copyright © 2014 by ASME

The number of huge oil storage tanks is increasing in the world. If a fire occurs in one of these tanks, it is very difficult to suppress. Additionally, if a fire whirl occurs in an oil tank fire, it is extremely dangerous for firefighters to extinguish the fire. The authors have numerically studied huge fire whirls in a large oil tank depot and predicted the generation of those fire whirls. Here, another study is attempted to clarify the details of huge fire whirl in a large oil tank, using two kinds of fire whirl generation channels in CFD simulations using the software, FDS by NIST. Details of burning rates, velocities of whirling flames, radiative heat flux, heat release rates and whirling cycles are examined, using oil tanks with the diameters of 0.2 to 80 m. In oil tanks with a diameter of 80 m, a tall fire whirl is generated. The height is about 1000 m. In this study of oil tanks fires with small to large diameters, it has been found that fire whirl lengths are about 8 to 11 times of the oil tank diameter. The maximum radiative heat flux due to a fire whirl in 80 m diameter oil tanks exceeds 100 kW/m2. Since the maximum radiation is found at twice the distance of oil tank diameters from the tank centers, adjacent oil tanks may be ignited. This study has also examined a method used to prevent fire whirl generation in huge oil tanks.Copyright © 2014 by ASME

Jacket is an ideal supporting structure for large 4 to 6 MW offshore wind turbine (OWT) in deep sea. However, Due to the harsh marine environment, as well as offshore wind farms are mostly located near a busy waterway, it is inevitable that ships crash offshore wind power structures. Sometimes, collision accidents may result in severe damage in the support structure. To study the collision behavior of jacket offshore structure, dynamic characteristics of the jacket OWT foundation is analyzed in this paper, based on ADINA explicit dynamic analysis method, considering different ship speed, impact locations and joint thickness. Based on the numerical results, the joints are reinforced in special location to meet requirements. Structural performances of jacket type OWT foundation under ship impact are studied. The research results in the paper can provide the reference for practical engineering design.Copyright © 2014 by ASME

A new concept Spar FPSO (Floating Production Storage and Offloading) is proposed for South China Sea deepwater oil field development integrating the advantages of the deep-draft Spar concept whose excellent stability and global performance enables dry-tree drilling and production, and the conventional ship-shaped FPSO for oil storage and offloading. This paper presents a study of the tandem offloading system for the new concept Spar FPSO. The paper will first give an overview of various offloading configurations and their characteristics for deepwater development; then a tandem offloading system similar to conventional ship-shaped FPSO is recommended for further investigation considering operational experience, safety and economical benefits. As the offloading operations are generally weather-limited, offloading environmental conditions for the study are selected based on API, ABS and South China Sea offshore operation practices. For a case study, hydrodynamic performance of the Spar FPSO in tandem offloading configuration with a shuttle tanker in 1500m water depth was investigated numerically and experimentally. Numerical simulations were conducted by means of fully coupled nonlinear time-domain analysis. The distance between the shuttle tanker and the Spar FPSO is optimized based on the relative motions of the two floaters and the hawser tension requirement of the shuttle tanker. Experimental results from model test are presented and compared with analytical time-domain simulation results. It is shown that the results of numerical simulations are consistent with the model test. The tandem offloading system demonstrates robust performance and cost-effectiveness for the proposed Spar FPSO concept.

The wind energy converters have extreme requirements to lateral deformation and rotation for support structures. Mono-pile, as a popular foundation structure for offshore wind energy towers, must be with sufficient large diameter and deep embedded length to limit the deformation and rotation within the tolerance under cyclic loads. Larger power offshore wind turbine (OWT), bigger pile diameter should be needed. However, large outer diameter pile will lead to difficult construction and high cost. In this study, a new conception of composite mono-pile is presented to decrease the outer diameter of pile. To investigate the structural behavior of composite mono-pile, the finite elements software ABAQUS is employed to analyze and compare with general mono-pile for 1.5 MW OWT under static loads. The numerical results demonstrate that stiffness of composite mono-pile can be improved effectively. Therefore, in same environment condition, composite mono-pipe diameter will be smaller than typical mono-pile, correspondingly, construction difficult and cost will be decreased. In addition, mechanical characteristics of composite mono-pile are analyzed and rational diameter and thickness selection of inserted pile are advised. The research results can provide the reference for practical engineering.Copyright © 2013 by ASME

In recent times, Origami has received an increasing research interest because of its capability to produce foldable tessellations and structures. This paper describes a new modular tetrahedral representation called “Kinetogami”. We embed the cuts and joining patterns into the crease pattern and create folded hinges across basic structural units (BSU), typically not done in Origami. We demonstrate sets of explicit 2D fabrication lay-outs and construction rules in order to fold reconfigurable structures and mechanisms in 3D by using a single flat paper sheet. The structural and combinatorial characteristics of Kinetogamic derivatives are further explored in a hierarchical manner. Inspired by Kinetogami, we design a family of multi-limbed tetrahedral robotic form that reconfigures and adapts. The kinematic properties of individual limbs are investigated and multiple gaits involving flipping, squatting/rising, squirming and slithering are synthesized for a representative hexapod robot. Our newly developed folding design paradigm provides affordances for a novel generation of robotic motion actuation and transformable reconfiguration.Copyright © 2012 by ASME

In the present work, injection of liquid kerosene into a high-pressure subsonic air crossflow was investigated experimentally. Tests were conducted at air pressures up to 2.0 MPa and at air temperatures from normal temperature to elevated temperature. Liquid kerosene was injected at room temperature through a 0.5 mm diameter plain orifice. Schlieren imaging technique was used for jet structure visualization, from which the jet penetration trajectory was determined by the image processing. For the conditions tested, a correlation of jet penetration trajectory was developed, with momentum flux ratio, Weber number and crossflow temperature ratio as independent variables. Upper surface trajectories of kerosene spray under different test conditions were compared. Experimental and analytical results showed that the penetration trajectory of liquid kerosene under higher air temperature was greater than that under normal temperature, while momentum ratios were the same.Copyright © 2012 by ASME