Modelling the vibration response of a gas turbine using machine learning

This work deals with modelling the vibration response of a gas turbine obtained during the start-up process until reaching the nominal speed for power generation. Analysing the vibrations of a complex systems like a gas turbine is useful for the diagnostic of faults or damages in the internal mechanical components of the different stages that integrate a turbine. This work focuses on the study of the shaft vibrations of the bearing radial type mounted between the shaft and the bearing compressor associated with the speed of the turbine. This relationship is studied using experimental data collected from a particular gas turbine model. In particular, we propose a methodology to synthesize a computational model following a supervised learning approach implemented through different machine learning techniques, including a multi-layers perceptron network, support vector machine (SVM), random forest (RF) and genetic programming (GP) with local search. Results show that SVM, RF and GP perform very well in this task, producing accurate predictive models. Moreover, there are some interesting trade-offs between the methods, regarding generalization error, overfitting and model interpretability that are relevant for future applications and research.     

Modelling of a rolling contact problem with the viscoelastic material response included

This paper gives an approach to the study of a rolling contact problem where bodies in contact exhibit a viscoelastic behaviour. Taking the viscoelastic-elastic analogy into account, the numerical implementation to a certain class of viscoelastic solutions is presented first, followed by a simulation of the rolling contact problem. The simulation is based on the superposition of two special boundary problems, the former concerning a viscoelastic half-space loaded by a concentrated force, F(t), perpendicular to its surface, and the latter concerning a sphere loaded by two opposite concentrated forces.     

Modelling of the influence of HTdR on cell kinetics in mouse epidermis

Fluctuations occur in the labeling index (LI) of mouse epidermis over the first two days after application of tritiated thymidine (³HTdR) for which there has in the past been no explanation. Similarly, there has been no adequate explanation for the fluctuations in the percent labelled mitoses (PLM) data seen immediately after the first peak. Here we propose a model which provides an explanation for both these features. The hypothesis suggested is that some cells are killed by the ³HTdR either immediately when they are still in the S phase or later when they have reached G₁. In both cases the labelled precursor is released from the cell and may be incorporated into other S phase cells after an appropriate delay. The model has been formulated into a computer programme which can derive the appropriate LI or PLM curves and fit curves to the relevant data. The resulting curves fit the data well suggesting that such cytotoxic and reutilization processes may in fact occur.     

Modelling gross primary production in the Heihe river basin and uncertainty analysis

Accurate and timely monitoring of gross primary production (GPP) at regional and global scales is necessary for understanding the terrestrial biosphere carbon balance. In this article, 8-day composite GPP is estimated using the region production efficiency model (REG-PEM) in the Heihe river basin from 2006 to 2008. The result indicates that GPP meets the seasonal cycle well and varies with different land covers. Analysis of uncertainty and sensitivity of the REG-PEM model are implemented by the Monte Carlo method. GPP is simulated with a test data set; the data set includes three groups, and each group has 8000 points. The three groups obey uniform distribution, normal distribution and beta distribution, respectively. Uncertainty is assessed by the quantification of mean values and standard deviation of outputs. The distribution of simulated GPP is slightly different from that of model-calculated GPP over the study sites. Among the input parameters, the land surface water index (LSWI) and air temperature (T) make less of a contribution to model output than photosynthetic active radiation (PAR) and the enhanced vegetation index (EVI). The main sources of model uncertainty are input data uncertainty and uncertainty from the specific model.     

Modelling programming performance: Beyond the influence of learner characteristics

In the 21st century, the ubiquitous nature of technology today is evident and to a large extent, most of us benefit from the modern convenience brought about by technology. Yet to be technology literate, it is argued that learning to program still plays an important role. One area of research in programming concerns the identification of predictors of programming success. Previous studies have identified a number of predictors. This study examined the effect of a combination of predictors (gender, learning styles, mental models, prior composite academic ability, and medium of instruction) on programming performance. Data were collected anonymously through a website from 131 secondary school students in Hong Kong who opted for computer programming in the Computer and Information Technology curriculum. Partial Least Squares (PLS) modelling was used to test a hypothesized theoretical structural model. All of the five aforementioned variables were either direct or indirect predictors of programming performance and the antecedents accounted for 43.6% of the variance in programming performance. While this study shows the influence of learner characteristics such as gender, learning styles, and mental models on programming performance, it highlights the effect that prior composite academic ability and medium of instruction exert on learning outcomes, which is uncommon among studies of similar purpose. These findings have significant implications for policy makers and educators alike.     

Modelling small area counts in the presence of overdispersion and spatial autocorrelation

The problems arising when modelling counts of rare events observed in small geographical areas when overdispersion and residual spatial autocorrelation are present or anticipated are considered. Different models are presented for handling inference in this case. The different strategies are implemented using data on offender counts at the enumeration district scale for Sheffield, England and results compared. This example is chosen because previous research suggests that social processes and social composition variables are key to understanding geographical variation in offender counts which will, as a consequence, show evidence of clustering both at the scale of the enumeration district and at larger scales. This in turn leads the analyst to anticipate the presence of overdispersion and spatial autocorrelation. Diagnostic measures are described and different modelling strategies are implemented. The evidence suggests that modelling strategies based on the use of spatial random effects models or models that include spatial filters appear to work well and provide a robust basis for model inference but gaps remain in the methodology that call for further research.     

Modelling observed California Current mesoscale eddies and the ecosystem response

Satellite and in situ observations are used to test model dynamics for the California Current System (CCS). The model and data are combined to reconstruct the mesoscale ocean structure during a given three-week period. The resulting physical flow field is used to drive a 3D ecosystem model to interpret SeaWiFS and in situ chlorophyll-a (chl-a) variations. With this approach a more complete and consistent picture of the physical and ecosystem processes of the CCS is obtained, providing the basis for addressing fundamental questions about dynamics and predictability of the coastal ocean.     

Modelling the steady state response of CuAlNi/polyimide bimorph actuator

Microsystem Technologies - Microactuators developed from shape memory alloy (SMA) thin films on flexible substrates find good applications in MEMS design. This article presents the models of the...     

亚热带小流域不同沉积区土壤粘粒矿物的演变

在亚热带丘陵河谷地小流域范围内地表物质的迁移常可导致不同沉积区物质组成的变化 .从黄泥土→洪积泥砂土→培泥砂土 ,随着搬运距离的增加 ,其粘粒矿物组成发生了一系列的变化 ;高岭石逐渐下降 ,云母逐渐增加 ,蛭石渐趋下降消失 ,而绿泥石则逐渐形成 ;同时赤铁矿、针铁矿也先后下降消失 .矿物的演化与沉积物所处环境的水分条件及溶液中盐基物质和酸碱度变化有关     

Evaluating four nitrous oxide emission algorithms in response to N rate on an irrigated corn field

In this study, the RZWQM2 (Root Zone Water Quality Model) was used to simulate the responses of N₂O emissions to different Nitrogen application rates on an irrigated corn field from 2003 to 2006, in eastern Colorado, USA. Four different algorithms from the literature were coupled with RZWQM2 and compared for simulating N₂O emissions during nitrification and denitrification processes. The RZWQM2 was first calibrated for corn yield, N uptake, soil water (0–10 cm) and soil Nitrate-N content (0–180 cm) and the simulated daily nitrification and denitrification rates were used to calculate N₂O emission using the algorithms from DAYCENT, NOE (Nitrous Oxide Emissions),WNMM (Water and Nitrogen Management Model), and FASSET models. The best N₂O emission was simulated when the fraction of N₂O release from nitrification was modified by water filled pore space (WFPS) as in the NOE model and the fraction N₂O release from denitrification was adopted from the DAYCENT model.     

The influence of load on the frequency response of rock bolt anchorage

A research programme into both the static and dynamic performance of ground anchorage systems, with an emphasis on resin bonded rock bolts, started at the University of Aberdeen in the early 1980s. The work involved measurements on active construction sites which was underpinned by laboratory and computer modelling and led to the development of a new method for the non-destructive testing of anchorages. Part of the research programme was focused on assessing how changes in the load influence the dynamic responses of an anchorage. This in turn produced a new testing method able to determine the variation in frequency response of the anchorage with changes in load. The development of a lumped parameter model able to simulate the response of anchorages to changes in static load and an applied impulse load was a further step forward in the research programme. The achievements of the lumped parameter model revealed the head of the anchorage to be the most influential component of the anchorage system in determining dynamic response. The results obtained from the numerical model when laboratory anchorages were simulated are shown to be in agreement with the results obtained from the actual laboratory tests. Based on the successful results obtained to date regarding laboratory rock bolt anchorages, a further step was made in order to employ the numerical model for the first time to observe the influence of load on the frequency response of rock bolt anchorages installed in the field. This paper describes the application of the model to such field anchorages and highlights some of the detailed modelling aspects required to replicate real anchorage behaviour.     

Assessing the long-term impact of urbanization on run-off using a remote-sensing-supported hydrological model

Land use/land cover (LULC) change in Dongguan, a city belonging to the Pearl River Delta metropolitan area, and its impact on the run-off of this city since the rapid urbanization period starting in 1979 are analysed in this article. Historic remote-sensing imagery (acquired in 1979, 1989, 2000, 2006, and 2013) was processed by the Support Vector Machine (SVM) method to obtain LULC data, and a long-term hydrologic impact assessment (L-THIA) model was applied to evaluate the long-term effects of LULC changes on surface run-off. The results show the urbanized area in Dongguan has increased more than 52% from 1979 to 2013 and the percentages of annual surface run-off depth and annual surface run-off coefficient are 58% and 5.83%, respectively. The increase in annual surface run-off is related to urbanization, and the centre area of the city has experienced the largest increase in annual surface run-off. The 32 towns’ local indicators of spatial association show centre towns are hot spots of increases in annual surface run-off in Dongguan city.     

Effect of heliotropism on the bidirectional reflectance of irrigated cotton

The dynamic movement of cotton leaves in the presence of sunlight has been described using gyroscopic coordinates. These coordinates were used to calculate the position of leaf normals with respect to the sun on an individual basis. A sensitivity analysis established that the angle between a leaf normal and the sun was most affected by changes in pitch and roll. Averaging leaf normals by quadrant (as established by the direction of the compass) showed the pronounced heliotropic behavior of cotton leaves and the differential behavior of cotton leaves relative to the quadrant of the sun. These results were subsequently applied to the estimation of the phase angle γ between the canopy normals and sun from cross sections of bidirectional reflectance curves obtained for a band spanning 0.57–0.69 μm. From the cross section determined by the principal plane at 6:07 MST, which turned out to be concave and nearly symmetrical, the canopy averaged value for γ was estimated to be about 90°, while the calculated value from the leaf angle data was 85°. At 12:08 MST the same cross section was convex and asymmetrical with respect to rotation about the nadir direction, indicating distinguishable forescattered and backscattered components. For the forescattered component the estimated value for γ was 15°, and the calculated value 20°. For the backscattered component the estimated value for γ was 12°, and the calculated value 21°. These results suggested that bidirectional reflectance information analyzed sequentially using a visible band for which the optical transmission is nearly zero can be used to monitor leaf movement and hence moisture availability.     

Effect of differing DEM creation methods on the results from a hydrological model

It is known that digital elevation models (DEMs) can vary in quality depending on their method of creation. Six DEMs derived from digitised contours from the British Ordnance Survey were compared. The DEMs were used to run TOPMODEL for a small catchment in Devon. There were differences between the DEMs in the prediction of the catchment area and the spatial pattern of topographic index values, although these differences were reduced by smoothing the DEMs. Because runoff in the area is dominated by subsurface flow, many of the model predictions were not sensitive to differences between the DEMs. However, predictions of surface runoff differed by over 200%, and caused variations of up to 25% in the prediction of hourly flow values. The predicted spatial pattern of surface runoff was strongly affected by the presence of interpolation artefacts in the DEM, with completely unrealistic predictions in the case of the worst quality DEMs.     

Modelling the influence of the gas to melt ratio on the solid fraction of the surface in spray formed billets

In this paper, the relationship between the Gas to Melt Ratio (GMR) and the solid fraction of an evolving billet surface is investigated numerically. The basis for the analysis is a recently developed integrated procedure for modelling the entire spray forming process. This model includes the atomisation stage taking thermal coupling into consideration and the deposition of the droplets at the surface of the billet taking geometrical aspects such as shading into account. The coupling between these two models is accomplished by ensuring that the total droplet size distribution of the spray is the summation of “local” droplet size distributions along the r-axis of the spray cone. The criterion for a successful process has been a predefined process window characterised by a desired solid fraction range at a certain distance from the atomizer. Inside this process window, the gas and melt flows have been varied and their influence on the solid fraction at the surface of the billet has been analysed.     

Dynamic response of NDVI to soil moisture variations during different hydrological regimes in the Sahel region

Over the last few decades, the African Sahel has become the focus of many studies regarding vegetation dynamics and their relationships with climate and people. This is because rainfall limits the production of biomass in the region, a resource on which people are directly dependent for their livelihoods. In this study, we utilized a remote-sensing approach to answering the following two questions: (1) how does the dynamic relationship between soil moisture and plant growth vary across hydrological regimes, and (2) are vegetation-type-dependent responses to soil moisture availability detectable from satellite imagery? In order to answer these questions, we studied the relationship between monthly modelled soil moisture as an indicator for water availability and the remotely sensed normalized difference vegetation index (NDVI) as a proxy for vegetation growth between a “recovery rainfall period” (1982 to 1997) and a “stable rainfall period” (1998 to 2013), at different time lags across the Sahel region. Using windowed cross-correlation, we find a strong significant positive relationship between NDVI and soil moisture at a concurrent time and at NDVI lagging behind soil moisture by 1 month for grassland, cropland, and deciduous shrubland vegetation – the dominant vegetation classes in the Sahel. South of the Sahel (the Sudanian and Guinean areas), we find longer optimal lags (soil moisture lagged by 1–3 months) in association with mixed forest and deciduous shrubland. We find no major significant change in optimal lag between the recovery and stable periods in the Sahelian region; however, in the Sudanian and Guinean areas, we observe a trend towards shorter time lags. This change in optimal lag suggests a vegetation change, which may be a response to a climatic shift or land-use change. This approach of identifying spatiotemporal trends in optimal lag correlations between modelled soil moisture and NDVI could prove to be a useful tool for mapping vegetation change and ecosystem behaviour, in turn helping inform climate change mitigation approaches and agricultural planning.     

Modelling the movement of a two-link manipulator

An algorithm for optimizing the control signal for simple movements of a two-link manipulator with four degrees of freedom is described. Based on the typical movement and functions of upper human extremities, the manipulator (so-called anthropomorphic manipulator) is composed of two links. The motion of the links is developed by four driving motors. The mathematic model is based of the Lagrange equations of the IInd king. The minimization of the time of movement with initial limitation of accuracy is obtained and the error of the final position is minimized without changing the time-optimal criterion. The relations connected with minimalization of both quality factors are considered. At the same time, the algorithm optimizes the torque distribution between the actuators which drive each link of manipulator. As well the manipulator as its activity are modelled on the digital computer. The results of the computer simulation of the algorithm, and the modelling of the time and accuracy optimal control, are presented.     

Application of a distributed large basin runoff model in the Great Lakes basin

This paper analyzes the application of a spatially distributed large basin runoff model (DLBRM) in the Great Lakes Basin of the United Stats and Canada and discusses four essential components of operational hydrologic model development: model structure, model input, model calibration, and Geographical Information System (GIS)-model interface. The results indicate that large scale operational hydrologic models that are based on mass continuity equations and include land surface, soil zones, and groundwater components require fewer parameters, are less data demanding, and are particularly suitable for solving water resources problems over large spatial and temporal scales than many other models. Use of GIS-model interfaces is essential for utilizing the existing multiple digital databases in defining model input and in facilitating model implementation and applicability.