638 research outputs found
Design of grabs under operational conditions (abstract)
No full textBulk materials such as iron ore transported by bulk carriers are commonly unloaded by the use of grabs. The unloading process is time consuming and increasing the unloading capacity is of big importance for terminals. A validated co-simulation developed by the TU Delft in cooperation with Nemag enables to test grabs in the virtual environment. In practice a variation in unloading capacity is seen, due to dynamic operational conditions, such as different crane operators and bulk surface irregularities. To improve grab design the influence of operational conditions on the unloading capacity is investigated. Based on those results a design modification has been proposed and showed promising results.Marine Technology | Transport Engineering and Logistic
Towards Smart Grabs: Measuring Bulk Handling Grab Kinematics and Operations
No full textBulk handling grabs are often used for unloading bulk materials such as iron ore and coal from bulk carrying ships. To improve and compare virtual simulations of new grabs, accurate real life kinematic data of grabs is required. Moreover kinematic data can potentially provide insight in current use of grabs, which can be interesting information for both manufacturer and customer of the grab. The possibilities towards implementation of a sensor system on bulk handling grabs are investigated by selecting a suitable sensor and measuring kinematics and operations of imitated grab movements. This research focuses on investigating kinematics of multi rope grabs with dual scoops. A sensor selection procedure is followed resulting in the selection of an Inertial Measurement Unit (IMU) sensor with Global Navigation Satellite System (GNSS) receiver. In several experiments the sensor data is compared with reference data of imitated grab movements assumed as ground truth. When using multiple IMU’s (one on each grab scoop) providing orientation data, the opening angle can be determined. The results of the experiments indicate that the position data provided by the sensor can be used for classification of activities, but less for high precision movement trajectory reconstruction. Position and orientation data of imitated grab movements can be interpreted to generate performance indicators that describe grab operations. Experiments showed that performance indicators of imitated grab movements can be identified accurate up to an error of two seconds when comparing known performance indicators and sensor data analysis. When a high level of accuracy of the kinematic data is reached, performance indicators describing grab operations can be determined more accurately.Mechanical Engineerin
Systematic design optimization of grabs considering bulk cargo variability
No full textShip unloader grabs are usually designed using the manufacturer's in-house knowledge based on a traditional physical prototyping approach. The grab performance depends greatly on the properties of the bulk material being handled. By considering the bulk cargo variability in the design process, the grab performance can be improved significantly. A multi-objective simulation-based optimization framework is therefore established to include bulk cargo variability in the design process of grabs. The primary objective is to reach a maximized and consistent performance in handling a variety of iron ore cargoes. First, a range of bulk materials is created by varying levels of cohesive forces and plasticity in the elasto-plastic adhesive DEM contact model. The sensitivity analysis of the grabbing process to the bulk variability allowed three classes of iron ore materials to be selected that have significant influence on the product performance. Second, 25 different grab designs are generated using a random sampling method, Latin Hypercube Design, to be assessed as to their handling of the three classes of iron ore materials. Of this range of grab designs, optimal solutions are found using surrogate modelling-based optimization and the NSGA-II genetic algorithm. The optimization outcome is verified by comparing predictions of the optimization algorithm and results of DEM-MBD co-simulation. The established optimization framework offers a straightforward and reliable tool for designing grabs and other similar equipment.Transport Engineering and Logistic
Grabs and Cohesive Bulk Solids: Virtual prototyping using a validated co-simulation
No full textDue to the high demand of iron ore products in the steel industry, they have the largest share in dry bulk trading per year, above coal and grains. Approximately 9000 Cape-size bulk carriers with capacities up to 400 000 tonnes (DWT) transport the annual demand of iron ore to destination ports. Grabs are employed extensively to unload iron ore from ship holds. A fast and reliable unloading process is required to maintain a minimized cost for port operators and to deliver iron ore products to customers on time. In practice, many factors, such as moisture, varying material properties over the cargo depth and grab’s dynamics, contribute in creating challenges for achieving the desired performance during the unloading process. A solution for improving the unloading process is to enhance the design of grabs by using simulation-based methods. This enables a higher mass of iron ore to be collected per grab cycle, thus minimizing the total unloading time of a bulk carrier. Virtual prototyping of grabs is a novel simulation-based method that allows for evaluating the design performance in an affordable way. The virtual prototype of a grab as it interacts with bulk material are co-simulated at full-scale by coupling two different solvers: Discrete Element Method (DEM) and MultiBody Dynamics (MBD). The co-simulation requires virtual crane operator, CAD model of grab connected to a crane, and calibrated DEM material model as inputs. Over the past decade, reliable DEM calibration procedures have been developed to model free-flowing bulk solids, such as iron ore pellets, sand and gravel. However, due to moisture content the majority of iron ore products show cohesive and stress-history dependent behaviours, which should be considered in the calibration procedure. Additionally, considering particle size and shape of such fine iron ore products, the extreme computation time of DEM simulations is a challenge to be solved. Furthermore, a grab is often used to handle a broad variety of iron ore cargoes that are different in their properties, such as moisture content, shear strength and bulk density. The variability of bulk solid properties influences the grabbing process considerably, and thus, the grab’s efficiency. The primary objective of this dissertation is to develop an accurate co-simulation of grab and cohesive iron ore, and utilizing it for optimizing virtual prototypes. Once properties of an iron ore product in interaction with equipment are characterized, a reliable multi-variable calibration procedure needs to be employed to set various input parameters of a DEM material model, including continuous and categorical variables. Furthermore, once proper scaling rules are applied on the DEM simulation, a full scale grab-material co-simulation can be set up to be validated. Next, by determining the optimal settings of design variables the effect of bulk cargo variation on the grab’s efficiency can be minimized. This is the fundamental strategy of robust grab design. Bulk terminal operators value grabs that are optimized for multiple objectives, including a maximized efficiency with a minimized deviation.Transport Engineering and Logistic
Supplement 1. (Table 2) Chemical composition of bottom sediments from grabs collected in the East Atlantic
No full textSupplement 1. (Table 2) Chemical composition of bottom sediments from grabs collected in the East Atlanti
Systematic Design Optimization of grabs handling cohesive bulk materials: Systematisch ontwerp optimalisatie van overslag grijpers voor cohesive bulk materialen
No full textGrabs are often used for unloading bulk carriers that transport iron ore cargoes around the globe. The unloading process is time-consuming, and terminals strive to maximise their turnover capacity. Grab performance is a combination of maximum crane capacity, grab design and bulk material behaviour. Due to bulk uncertainties occurred by varying physical bulk properties, moisture content and consolidation, grab performance is hard to predict. To incorporate the bulk variability in the design process of grabs, or other large-scale bulk handling equipment, an optimization framework is proposed in which equipment is systematically optimized. With the framework an iron ore grab is optimized for handling iron ore pellets and iron ore fines. By a minimum number of experiments grab design was improved, increasing the turnover capacity for iron ore pellets by 12% and iron ore fines with 8%, and reducing the effect of varying bulk conditions. Optimization methods such as Latin Hypercube sampling,surrogate modelling and genetic algorithms proved to be successful for grab optimization. Further research of implementing the framework in the design process, and surrogate modelling is recommended.To reference this document see also: http://resolver.tudelft.nl/uuid:deb8bce0-2d21-4c4b-9f45-d1601744771a / https://doi.org/10.1016/j.apt.2021.03.027Marine Technology | Transport Engineering and Logistic
Virtual prototyping of grabs: Co-simulations of discrete element and rigid body models
No full textThis dissertation has investigated whether a combination of DEM and MBD can be used for a reliable and accurate environment for predicting grab unloading performance. A grab is a type of bulk material handling equipment used for unloading materials such as coal and iron ore from vessel to shore. Both a grab and iron ore pellets have been modelled and coupled into a co-simulation. Particle stiffness reductions and coarse graining techniques have been developed and applied to reduce computational costs. The developed large scale coupled grab-pellets model compared very well with validation experiments conducted on a bulk terminal with a scissors grab. A demonstration of virtual prototyping of grabs showed that when this model is implemented in the grab design process significant improvements in grab performance can be achieved.Transport Engineering and Logistic
Abundance of species collected in grabs (0.04 m<sup>2</sup>) at Wormcam site by date.
No full text<p>Abundance of species collected in grabs (0.04 m<sup>2</sup>) at Wormcam site by date.</p
Combustion and Society: A Fire-Centred History of Energy Use
No full textFire is a force that links everyday human activities to some of the most powerful energetic movements of the Earth. Drawing together the energy-centred social theory of Georges Bataille, the fire-centred environmental history of Stephen Pyne, and the work of a number of ‘pyrotechnology’ scholars, the paper proposes that the generalized study of combustion is a key to contextualizing human energetic practices within a broader ‘economy’ of terrestrial and cosmic energy flows. We examine the relatively recent turn towards fossil-fuelled ‘internal combustion’ in the light of a much longer human history of ‘broadcast’ burning of vegetation and of artisanal pyrotechnologies – the use of heat to transform diverse materials. A combustion-centred analysis, it is argued, brings human collective life into closer contact with the geochemical and geologic conditions of earthly existence, while also pointing to the significance of explorative, experimental and even playful dispositions towards energy and matter. © 2014, SAGE Publications. All rights reserved
Design framework for DEM-supported prototyping of grabs including full-scale validation
No full textThe design of machinery for handling granular materials relies mainly on empirical methods and in-house engineering knowledge. This traditional approach provides incremental improvements that are often limited. Advancements in simulation and optimization can offer a promising alternative approach. Most of the research involved in improving or optimizing equipment design does not include the realistic performance of the new prototype and as such it is uncertain that the predicted performance is also guaranteed in practice. In this study, a design framework for a new generation of machinery handling granular materials, grabs, has been established that includes a full-scale validation step. This has been proven to lead to a breakthrough in equipment design. This design framework uses a co-simulation between Discrete Element Method (DEM) and Multi Body Dynamics (MBD), thus, capturing operational conditions in full-scale. The DEM simulation supported design step integrated as the main step to generate new prototypes. The performance of the prototype is evaluated by conducting full-scale experiments, thus validating the adequacy of the new design as well as the accuracy of the co-simulation. Through this a full design cycle has been fulfilled and a validated model has been achieved that is independent of specific design configurations.</p
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