Thermal fatigue analysis of solar panel structure for micro-satellite applications

Thermal fatigue analysis based on 2D finite difference and 3D finite element methods is carried out to study the performance of solar panel structure during micro-satellite life time. Solar panel primary structure consists of honeycomb structure and composite laminates. The 2D finite difference (I-DEAS) model yields predictions of the temperature profile during one orbit. Then, 3D finite element analysis (ANSYS) is applied to predict thermal fatigue damage of solar panel structure. Meshing the whole structure with 2D multi-layer shell elements with sandwich option is not efficient, as it misses thermal response of the honeycomb structure. So we applied a mixed approach between 3D solid and 2D shell elements to model the solar panel structure without the sandwich option.

Later Pleistocene evolution of the Exe valley: A chronstratigraphic model of terrace formation and its implications for Palaeolithic archaeology

This paper presents the ?rst systematic chronostratigraphic study of the river terraces of the Exe catchment in South West England and a new conceptual model for terrace formation in unglaciated basins with applicability to terrace staircase sequences elsewhere. The Exe catchment lay beyond the maximum extent of Pleistocene ice sheets and the drainage pattern evolved from the Tertiary to the Middle Pleistocene, by which time the major valley systems were in place and downcutting began to create a staircase of strath terraces. The higher terraces (8-6) typically exhibit altitudinal overlap or appear to be draped over the landscape, whilst the middle terraces show greater altitudinal separation and the lowest terraces are of a cut and ?ll form. The terrace deposits investigated in this study were deposited in cold phases of the glacial-interglacial Milankovitch climatic cycles with the lowest four being deposited in the Devensian Marine Isotope Stages (MIS) 4-2. A new cascade process-response model is proposed of basin terrace evolution in the Exe valley, which emphasises the role of lateral erosion in the creation of strath terraces and the reworking of inherited resistant lithological components down through the staircase. The resultant emergent valley topography and the reworking of artefacts along with gravel clasts, have important implications for the dating of hominin presence and the local landscapes they inhabited. Whilst the terrace chronology suggested here is still not as detailed as that for the Thames or the Solent System it does indicate a Middle Palaeolithic hominin presence in the region, probably prior to the late Wolstonian Complex or MIS 6. This supports existing data from cave sites in South West England.

Dynamic grey-box modeling for online monitoring of extrusion viscosity

Melt viscosity is a key indicator of product quality in polymer extrusion processes. However, real time monitoring and control of viscosity is difficult to achieve. In this article, a novel “soft sensor” approach based on dynamic gray-box modeling is proposed. The soft sensor involves a nonlinear finite impulse response model with adaptable linear parameters for real-time prediction of the melt viscosity based on the process inputs; the model output is then used as an input of a model with a simple-fixed structure to predict the barrel pressure which can be measured online. Finally, the predicted pressure is compared to the measured value and the corresponding error is used as a feedback signal to correct the viscosity estimate. This novel feedback structure enables the online adaptability of the viscosity model in response to modeling errors and disturbances, hence producing a reliable viscosity estimate. The experimental results on different material/die/extruder confirm the effectiveness of the proposed “soft sensor” method based on dynamic gray-box modeling for real-time monitoring and control of polymer extrusion processes. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers

Stone temperature and moisture variability under temperate environmental conditions: implications for sandstone weathering

Temperature and moisture conditions are key drivers of stone weathering processes in both natural and built environments. Given their importance in the breakdown of stone, a detailed understanding of their temporal and spatial variability is central to understanding present-day weathering behaviour and for predicting how climate change may influence the nature and rates of future stone decay.
Subsurface temperature and moisture data are reported from quarry fresh Peakmoor Sandstone samples exposed during summer (June–July) and late autumn / early winter (October–December) in a mid-latitude, temperate maritime environment. These data demonstrate that the subsurface thermal response of sandstone comprises numerous short-term (minutes), low magnitude fluctuations superimposed upon larger-scale diurnal heating and cooling cycles with distinct aspect-related differences. The short-term fluctuations create conditions in the outer 5–10 mm of stone that are much more ‘energetic’ in comparison to the more subdued thermal cycling that occurs deeper within the sandstone samples.
Data show that moisture dynamics are equally complex with a near-surface region (5–10 mm) in which frequent moisture cycling takes place and this, combined with the thermal dynamism exhibited by the same region may have significant implications for the nature and rate of weathering activity. Data indicate that moisture input from rainfall, particularly when it is wind-driven, can travel deep into the stone where it can prolong the time of wetness. This most often occurs during wetter winter months when moisture input is high and evaporative loss is low but can happen at any time during the year when the hydraulic connection between near-surface and deeper regions of the stone is disrupted with subsequent loss of moisture from depth slowing as it becomes reliant on vapour diffusion alone.
These data illustrate the complexity of temperature and moisture conditions in sandstone exposed to the ‘moderate’ conditions of a temperate maritime environment. They highlight differences in thermal and moisture cycling between near-surface (5–10 mm) and deeper regions within the stone and contribute towards a better understanding of the development of structural and mineralogical heterogeneity between the stone surface and substrate.

A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Bystander-induced differentiation: a major response to targeted irradiation of a urothelial explant model.

A ureter primary explant technique, using porcine tissue sections was developed to study bystander effects under in vivo like conditions where dividing and differentiated cells are present. Targeted irradiations of ureter tissue fragments were performed with the Gray Cancer Institute charged particle microbeam at a single location (2 microm precision) with 10 3He2+ particles (5 MeV; LET 70 keV/microm). After irradiation the ureter tissue section was incubated for 7 days allowing explant outgrowth to be formed. Differentiation was estimated using antibodies to Uroplakin III, a specific marker of terminal urothelial differentiation. Even although only a single region of the tissue section was targeted, thousands of additional cells were found to undergo bystander-induced differentiation in the explant outgrowth. This resulted in an overall increase in the fraction of differentiated cells from 63.5+/-5.4% to 76.6+/-5.6%. These changes are much greater than that observed for the induction of damage in this model. One interpretation of these results is that in the tissue environment, differentiation is a much more significant response to targeted irradiation and potentially a protective mechanism.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

Modelling the mechanical response of the Reed-mouthpiece-lip system of a clarinet. Part I. A one-dimensional distributed model

The motion of a clarinet reed that is clamped to a mouthpiece and supported by a lip is simulated in the time-domain using finite difference methods. The reed is modelled as a bar with non-uniform cross section, and is described using a one-dimensional, fourth-order partial differential equation. The interactions with the mouthpiece Jay and the player's lip are taken into account by incorporating conditional contact forces in the bar equation. The model is completed by clamped-free boundary conditions for the reed. An implicit finite difference method is used for discretising the system, and values for the physical parameters are chosen both from laboratory measurements and by accurate tuning of the numerical simulations. The accuracy of the numerical system is assessed through analysis of frequency warping effects and of resonance estimation. Finally, the mechanical properties of the system are studied by analysing its response to external driving forces. In particular, the effects of reed curling are investigated.