67 research outputs found
Design of production systems with hybrid energy and water generation for sustainable value creation
Mooring line fatigue damage evaluation for floating marine energy converters: Field measurements and prediction
publication-status: Publishedtypes: ArticleThe vision of large-scale commercial arrays of floating marine energy converters (MECs) necessitates the robust, yet cost-effective engineering of devices. Given the continuous environmental loading, fatigue has been iden- tified as one of the key engineering challenges. In particular the mooring sys- tem which warrants the station-keeping of such devices is subject to highly cyclic, non-linear load conditions, mainly induced by the incident waves. To ensure the integrity of the mooring system the lifecycle fatigue spec- trum must be predicted in order to compare the expected fatigue damage against the design limits. The fatigue design of components is commonly as- sessed through numerical modelling of representative load cases. However, for new applications such as floating marine energy converters numerical models are often scantily validated. This paper describes an approach where load measurements from large- scale field trials at the South West Mooring Testing Facility (SWMTF) are used to calculate and predict the fatigue damage. The described procedure employs a Rainflow cycle analysis in conjunction with the Palmgren-Miner rule to estimate the accumulated damage for the deployment periods and individual sea states. This approach allows an accurate fatigue assessment and prediction of mooring lines at a design stage, where field trial load measurements and wave climate information of potential installation sites are available. The mooring design can thus be optimised regarding its fatigue life and costly safety factors can be reduced. The proposed method also assists in monitoring and assessing the fatigue life during deployment periods
Corporate sustainability reporting index and baseline data for the cruise industry
Sustainability policies and corporate reports demonstrate the impacts cruise companies acknowledge as their responsibility, and the actions put in place to address them. This paper develops a corporate social responsibility index based on the Global Reporting Initiative, with industry specific additions including labor and human rights, health and safety, and environmental and economic aspects. Companies disclose more management than performance data, which is typical of early stages of development. Companies disclosing less information focus on soft indicators which are easy to mimic and demonstrate posturing. Items disclosed tend to be marginal to the core of the business, have a positive economic impact or pre-empt sector regulation. Reports echo the voice of the corporations and not the demands of stakeholders. Institutional isomorphism has not influenced a homogenization in reporting, with only the largest firms reporting at this stage
AerialMPTNet: Multi-Pedestrian Tracking in Aerial Imagery Using Temporal and Graphical Features
Multi-pedestrian tracking in aerial imagery has several applications such as
large-scale event monitoring, disaster management, search-and-rescue missions,
and as input into predictive crowd dynamic models. Due to the challenges such
as the large number and the tiny size of the pedestrians (e.g., 4 x 4 pixels)
with their similar appearances as well as different scales and atmospheric
conditions of the images with their extremely low frame rates (e.g., 2 fps),
current state-of-the-art algorithms including the deep learning-based ones are
unable to perform well. In this paper, we propose AerialMPTNet, a novel
approach for multi-pedestrian tracking in geo-referenced aerial imagery by
fusing appearance features from a Siamese Neural Network, movement predictions
from a Long Short-Term Memory, and pedestrian interconnections from a GraphCNN.
In addition, to address the lack of diverse aerial pedestrian tracking
datasets, we introduce the Aerial Multi-Pedestrian Tracking (AerialMPT) dataset
consisting of 307 frames and 44,740 pedestrians annotated. We believe that
AerialMPT is the largest and most diverse dataset to this date and will be
released publicly. We evaluate AerialMPTNet on AerialMPT and KIT AIS, and
benchmark with several state-of-the-art tracking methods. Results indicate that
AerialMPTNet significantly outperforms other methods on accuracy and
time-efficiency.Comment: ICPR 202
Energy-water-food nexus in the Spanish greenhouse tomato production
The nexus energy–water–food of the tomato greenhouse production in the Almeria region (Spain) has been studied following a Process Systems Analysis Method connecting the ecosystem services to the market demands with a holistic view based on Life Cycle Assessment. The management of the agri-food subsystem, the industrial subsystem and the urban subsystem plays an important role in the nexus of the E–W–F system, where transport and information technologies connect the three subsystems to the global markets. The local case study of the tomato production in Almeria (Spain) has been developed as an example of the food production under cropland restrictions, semiarid land. After study of the economic and social sustainability in time, the evolution of the ecosystem services supply is the main restriction of the system, where after the land use change in the region, water and energy supply play the mean role with a trade-off between the water quality degradation and the economic cost of the energy for water desalination. Water footprint, Carbon footprint and Chemicals footprint are useful indicators to the environmental sustainability assessment of local alternatives in the E–W–F system under study. As it is shown in the conclusions, the holistic view based on the process analysis method and the life cycle assessment methodology and indicators is an useful tool for decision support
Mapping and Integrating Value Creation Factors with Life-cycle Stages for Sustainable Manufacturing
ALCOHOL CONSUMPTION AND THE EFFECT OF SOCIODEMOGRAPHIC VARIABLES ON ALCOHOL CONSUMPTION
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