Systematic variations in polymer gel dosimeter calibration due to container influence and deviations from water equivalence

There are a number of gel dosimeter calibration methods in contemporary usage. The present study is a detailed Monte Carlo investigation into the accuracy of several calibration techniques. Results show that for most arrangements the dose to gel accurately reflects the dose to water, with the most accurate method involving the use of a large diameter flask of gel into which multiple small fields of varying dose are directed. The least accurate method was found to be that of a long test tube in a water phantom, coaxial with the beam. The large flask method is also the most straightforward and least likely to introduce errors during setup, though, to its detriment, the volume of gel required is much more than other methods.

Optimization of container process at seaport terminals

Seaport container terminals are an important part of the logistics systems in international trades. This paper investigates the relationship between quay cranes, yard machines and container storage locations in a multi-berth and multi-ship environment. The aims are to develop a model for improving the operation efficiency of the seaports and to develop an analytical tool for yard operation planning. Due to the fact that the container transfer times are sequence-dependent and with the large number of variables involve, the proposed model cannot be solved in a reasonable time interval for realistically sized problems. For this reason, List Scheduling and Tabu Search algorithms have been developed to solve this formidable and NP-hard scheduling problem. Numerical implementations have been analysed and promising results have been achieved.

Optimising container processes at multimodal seaport terminals : an integrated approach and application

A Multimodal Seaport Container Terminal (MSCT) is a complex system which requires careful planning and control in order to operate efficiently. It consists of a number of subsystems that require optimisation of the operations within them, as well as synchronisation of machines and containers between the various subsystems. Inefficiency in the terminal can delay ships from their scheduled timetables, as well as cause delays in delivering containers to their inland destinations, both of which can be very costly to their operators. The purpose of this PhD thesis is to use Operations Research methodologies to optimise and synchronise these subsystems as an integrated application. An initial model is developed for the overall MSCT; however, due to a large number of assumptions that had to be made, as well as other issues, it is found to be too inaccurate and infeasible for practical use. Instead, a method of developing models for each subsystem is proposed that then be integrated with each other. Mathematical models are developed for the Storage Area System (SAS) and Intra-terminal Transportation System (ITTS). The SAS deals with the movement and assignment of containers to stacks within the storage area, both when they arrive and when they are rehandled to retrieve containers below them. The ITTS deals with scheduling the movement of containers and machines between the storage areas and other sections of the terminal, such as the berth and road/rail terminals. Various constructive heuristics are explored and compared for these models to produce good initial solutions for large-sized problems, which are otherwise impractical to compute by exact methods. These initial solutions are further improved through the use of an innovative hyper-heuristic algorithm that integrates the SAS and ITTS solutions together and optimises them through meta-heuristic techniques. The method by which the two models can interact with each other as an integrated system will be discussed, as well as how this method can be extended to the other subsystems of the MSCT.

Optimising container transfers at multimodal terminals

The use of containers have greatly reduced handling operations at ports and at all other transfer points, thus increasing the efficiency and speed of transportation. This was done in an attempt to cut down the cost of maritime transport, mainly by reducing cargo handling and costs, and ships' time in port by speeding up handling operations. This paper discusses the major factors influencing the transfer efficiency of seaport container terminals. A network model is designed to analyse container progress in the system and applied to a seaport container terminal. The model presented here can be seen as a decision support system in the context of investment appraisal of multimodal container terminals. (C) 2000 Elsevier Science Ltd.

Genetic algorithms to schedule container transfers at multimodal terminals

Optimising the container transfer schedule at the multimodal terminals is known to be NP-hard, which implies that the best solution becomes computationally infeasible as problem sizes increase. Genetic Algorithm (GA) techniques are used to reduce container handling/transfer times and ships' time at the port by speeding up handling operations. The GA is chosen due to the relatively good results that have been reported even with the simplest GA implementations to obtain near-optimal solutions in reasonable time. Also discussed, is the application of the model to assess the consequences of increased scheduled throughput time as well as different strategies such as the alternative plant layouts, storage policies and number of yard machines. A real data set used for the solution and subsequent sensitivity analysis is applied to the alternative plant layouts, storage policies and number of yard machines.

In situ SANS study of the surface and pore filling adsorption of subcritical and supercritical CO2 in porous silica as a function of pore size

We applied small-angle neutron scattering (SANS) and ultra small-angle neutron scattering (USANS) to monitor evolution of the CO2 adsorption in porous silica as a function of CO2 pressure and temperature in pores of different sizes. The range of pressures (0 < P < 345 bar) and temperatures (T=18 OC, 35 OC and 60 OC) corresponded to subcritical, near critical and supercritical conditions of bulk fluid. We observed that the adsorption behavior of CO2 is fundamentally different in large and small pores with the sizes D > 100 Å and D < 30 Å, respectively. Scattering data from large pores indicate formation of a dense adsorbed film of CO2 on pore walls with the liquid-like density (ρCO2)ads≈0.8 g/cm3. The adsorbed film coexists with unadsorbed fluid in the inner pore volume. The density of unadsorbed fluid in large pores is temperature and pressure dependent: it is initially lower than (ρCO2)ads and gradually approaches it with pressure. In small pores compressed CO2 gas completely fills the pore volume. At the lowest pressures of the order of 10 bar and T=18 OC, the fluid density in smallest pores available in the matrix with D ~ 10 Å exceeds bulk fluid density by a factor of ~ 8. As pressure increases, progressively larger pores become filled with the condensed CO2. Fluid densification is only observed in pores with sizes less than ~ 25 – 30 Å. As the density of the invading fluid reaches (ρCO2)bulk~ 0.8 g/cm3, pores of all sizes become uniformly filled with CO2 and the confinement effects disappear. At higher densities the fluid in small pores appears to follow the equation of state of bulk CO2 although there is an indication that the fluid density in the inner volume of large pores may exceed the density of the adsorbed layer. The equivalent internal pressure (Pint) in the smallest pores exceeds the external pressure (Pext) by a factor of ~ 5 for both sub- and supercritical CO2. Pint gradually approaches Pext as D → 25 – 30 Å and is independent of temperature in the studied range of 18 OC ≤ T ≤ 60 OC. The obtained results demonstrate certain similarity as well as differences between adsorption of subcritical and supercritical CO2 in disordered porous silica. High pressure small angle scattering experiments open new opportunities for in situ studies of the fluid adsorption in porous media of interest to CO2 sequestration, energy storage, and heterogeneous catalysis.

Nonlinear container ship model for the study of parametric roll resonance

Parametric roll is a critical phenomenon for ships, whose onset may cause roll oscillations up to +-40 degrees, leading to very dangerous situations and possibly capsizing. Container ships have been shown to be particularly prone to parametric roll resonance when they are sailing in moderate to heavy head seas. A Matlab/Simulink parametric roll benchmark model for a large container ship has been implemented and validated against a wide set of experimental data. The model is a part of a Matlab/Simulink Toolbox (MSS, 2007). The benchmark implements a 3rd-order nonlinear model where the dynamics of roll is strongly coupled with the heave and pitch dynamics. The implemented model has shown good accuracy in predicting the container ship motions, both in the vertical plane and in the transversal one. Parametric roll has been reproduced for all the data sets in which it happened, and the model provides realistic results which are in good agreement with the model tank experiments.

Validation of a container ship model for parametric rolling

The objective of this work is to formulate a nonlinear, coupled model of a container ship during parametric roll resonance, and to validate the model using experimental data.

A quay crane scheduling methodology for multimodal container terminals

This thesis develops an operational decision support tool for container terminal managements. The tool generates efficient schedules for shore cranes handling containers carried by mega container vessels.

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

Carbon nanotubes on nanoporous alumina: From surface mats to conformal pore filling

Control over nucleation and growth of multi-walled carbon nanotubes in the nanochannels of porous alumina membranes by several combinations of posttreatments, namely exposing the membrane top surface to atmospheric plasma jet and application of standard S1813 photoresist as an additional carbon precursor, is demonstrated. The nanotubes grown after plasma treatment nucleated inside the channels and did not form fibrous mats on the surface. Thus, the nanotube growth mode can be controlled by surface treatment and application of additional precursor, and complex nanotube-based structures can be produced for various applications. A plausible mechanism of nanotube nucleation and growth in the channels is proposed, based on the estimated depth of ion flux penetration into the channels.

Effects of the filling process on the evolution of the mushy zone and macrosegregation in alloy casting

A numerical model of the entire casting process starting from the mould filling stage to complete solidification is presented. The model takes into consideration any phase change taking place during the filling process. A volume of fluid method is used for tracking the metal–air interface during filling and an enthalpy based macro-scale solidification model is used for the phase change process. The model is demonstrated for the case of filling and solidification of Pb–15 wt%Sn alloy in a side-cooled two-dimensional rectangular cavity, and the resulting evolution of a mushy region and macrosegregation are studied. The effects of process parameters related to filling, namely degree of melt superheat and filling velocity on macrosegregation in the cavity, are also investigated. Results show significant differences in the progress of the mushy zone and macrosegregation pattern between this analysis and conventional analysis without the filling effect.

Functional dynamics of the nitrogen balance of sorghum. II. Grain filling period.

Maintenance of green leaf area during grain filling can increase grain yield of sorghum grown under terminal water limitation. This 'stay-green' trait has been related to the nitrogen (N) supply-demand balance during grain filling. This study quantifies the N demand of grain and N translocation rates from leaves and stem and explores effects of genotype and N stress on onset and rate of leaf senescence during the grain filling period. Three hybrids differing in potential height were grown at three levels of N supply under well-watered conditions. Vertical profiles of biomass, leaf area, and N% of leaves, stem and grain were measured at regular intervals. Weekly SPAD chlorophyll readings on main shoot leaves were correlated with observed specific leaf nitrogen (SLN) to derive seasonal patterns of leaf N content. For all hybrids, individual grain N demand was sink determined and was initially met through N translocation from the stem and rachis. Only if this was insufficient did leaf N translocation occur. Maximum N translocation rates from leaves and stem were dependent on their N status. However, the supply of N at canopy scale was also related to the amount of leaf area senescing at any one time. This supply-demand framework for N dynamics explained effects of N stress and genotype on the onset and rate of leaf senescence.

Thermoelectric Properties of Co4Sb12 Skutterudite Materials with Partial In Filling and Excess In Additions

The properties of Co4Sb12 with various In additions were studied. X-ray diffraction revealed the presence of the pure δ-phase of In0.16Co4Sb12, whereas impurity phases (γ-CoSb2 and InSb) appeared for x = 0.25, 0.40, 0.80, and 1.20. The homogeneity and morphology of the samples were observed by Seebeck microprobe and scanning electron microscopy, respectively. All the quenched ingots from which the studied samples were cut were inhomogeneous in the axial direction. The temperature dependence of the Seebeck coefficient (S), electrical conductivity (σ), and thermal conductivity (κ) was measured from room temperature up to 673 K. The Seebeck coefficient of all In-added Co4Sb12 materials was negative. When the filler concentration increases, the Seebeck coefficient decreases. The samples with In additions above the filling limit (x = 0.22) show an even lower Seebeck coefficient due to the formation of secondary phases: InSb and CoSb2. The temperature variation of the electrical conductivity is semiconductor-like. The thermal conductivity of all the samples decreases with temperature. The central region of the In0.4Co4Sb12 ingot shows the lowest thermal conductivity, probably due to the combined effect of (a) rattling due to maximum filling and (b) the presence of a small amount of fine-dispersed secondary phases at the grain boundaries. Thus, regardless of the non-single-phase morphology, a promising ZT (S 2 σT/κ) value of 0.96 at 673 K has been obtained with an In addition above the filling limit.