New Estimates of 24-Hour Probable Maximum Precipitation (PMP) for the British Isles

Estimates of PMP are needed in order to estimate the spillway design flood for dams which must be capable of safely passing the probable maximum flood (PMF). For over forty years the standard estimates of the Flood Studies Report (FSR) have almost always been used. However, since then several studies have shown that these values are too low, and new estimates for South West England and then Britain were published. This paper extends these studies to include the whole of the British Isles. The study uses 6570 station years’ data in a new method of frequency analysis that identifies part of the data which represents the long term situation. Further analyses to support the results of this approach have been produced from the in situ maximisation of 12 historic storms using World Meteorological Organisation methods. The results are broadly consistent with those obtained from frequency analysis. Values of 24 hour PMP in Britain range from 600 mm in upland areas of the Lake District, to 400 mm in parts of East Anglia. This range of values is present in Wales and parts of South West England. For Ireland the highest values are over the upland areas, such as in the Wicklow Mountains (550 mm) and SW Ireland (600 mm), while in the lowlands values around 350 mm can be expected. The question of uncertainty in estimating PMP is considered, most of which is due to the temporal and spatial shortcomings of the data. The implications for the probable maximum flood (PMF) and spillway design flood mean that widespread reassessment of dam safety should be carried out at once.

Green thinking in the steel rolling mill

In terms of energy use and carbon footprint,it is the primary processes of ironmaking and steelmaking that command most attention in our industry.The rolling mills,although energy-intensive by comparison with most industrial finishing operations,are often overlooked when a steel company considers its environmental responsibilities and its energy-saving opportunities. The high gearing of energy consumption of the primary processes over the finishing processes has an important consequence,however.The key to green rolling is as much about yield(and avoiding the remelting of scrap) as it is about direct energy use. This paper uses a project case study,the design and commissioning of the Endless Strip Processing(ESP) plant of Arvedi in Italy to illustrate how modern rolling mills are contributing to a greener steel industry.The relevant technical features include the energy savings implicit in near-net shape casting and in direct rolling,without intermediate reheating,advances in drive and power conversion technologies and the aforementioned concept of energy saving through yield maximisation. Some notable co-operative efforts towards greener rolling are also explained,including university collaborations and in particular the WellMet2050 project at the University of Cambridge.In conclusion,the green credentials of steel usage in general industry are considered and key messages for the engineering community are sought.

Texture-based latent space disentanglement for enhancement of a training dataset for ANN-based classification of fruit and vegetables

The capability of Convolutional Neural Networks(CNNs)for sparse representation has significant application to complex tasks like Representation Learning(RL).However,labelled datasets of sufficient size for learning this representation are not easily obtainable.The unsupervised learning capability of Variational Autoencoders(VAEs)and Generative Adversarial Networks(GANs)provide a promising solution to this issue through their capacity to learn representations for novel data samples and classification tasks.In this research,a texture-based latent space disentanglement technique is proposed to enhance learning of representations for novel data samples.A comparison is performed among different VAEs and GANs with the proposed approach for synthesis of new data samples.Two different VAE architectures are considered,a single layer dense VAE and a convolution based VAE,to compare the effectiveness of different architectures for learning of the representations.The GANs are selected based on the distance metric for disjoint distribution divergence estimation of complex representation learning tasks.The proposed texture-based disentanglement has been shown to provide a significant improvement for disentangling the process of representation learning by conditioning the random noise and synthesising texture rich images of fruit and vegetables。

Biologically Inspired Girder Structure for the Synchrotron Radiation Facility PETRA IV

Lightweight structures are widely used across different industry sectors.However,they get easily excited by external influences,such as vibrations.Undesired high vibration amplitudes can be avoided by shifting the structural eigenfrequencies,which can be achieved adapting the structural design considering optimisation procedures and structures primarily inspired by diatoms.This procedures has been applied to the development process of a girder structure installed in a synchrotron radiation facility to support heavy magnets and other components.The objective was to design a 2.9 m long girder structure with high eigenfrequencies,a high stiffness and a low mass.Based on a topology optimisation result,a parametric beam–shell model including biologically inspired structures(e.g.,Voronoi combs,ribs,and soft and organic-looking transitions)was built up.The subsequent cross-sectional optimisation using evolutionary strategic optimisation revealed an optimum girder structure,which was successfully manufactured using the casting technology.Eigenfrequency measurements validated the numerical models.Future changes in the specifications can be implemented in the bio-inspired development process to obtain adapted girder structures.

Landmark Report Launched on Maximising China's Tourism Potential

With the world’s attention firmly on China(PRC)in the run-up to the Beijing 2008 Olympic Games,the Pacific Asia Travel Association(PATA)has produced a landmark report on how the country’s tourism potential can be maximised. Endorsed by the China National Tourism Administration(CNTA), and sponsored by Visa,’Realising China’s Tourism Potential: Recommendations for Future Development’is the first definitive international study that presents a roadmap for growth and management of the US$100bn industry.