The determination of three selected sites for the construction and operation of a low level radioactive waste storage and burial facility

Radioactive wastes are by-products of the use of radiation technologies. As with many technologies, the wastes are required to be disposed of in a safe manner so as to minimise risk to human health. This study examines the requirements for a hypothetical repository and develops techniques for decision making to permit the establishment of a shallow ground burial facility to receive an inventory of low-level radioactive wastes. Australia’s overall inventory is used as an example. Essential and desirable siting criteria are developed and applied to Australia's Northern Territory resulting in the selection of three candidate sites for laboratory investigations into soil behaviour. The essential quantifiable factors which govern radionuclide migration and ultimately influence radiation doses following facility closure are reviewed. Simplified batch and column procedures were developed to enable laboratory determination of distribution and retardation coefficient values for use in one-dimensional advection-dispersion transport equations. Batch and column experiments were conducted with Australian soils sampled from the three identified candidate sites using a radionuclide representative of the current national low-level radioactive waste inventory. The experimental results are discussed and site soil performance compared. The experimental results are subsequently used to compare the relative radiation health risks between each of the three sites investigated. A recommendation is made as to the preferred site to construct an engineered near-surface burial facility to receive the Australian low-level radioactive waste inventory.

Changes in Level of Virus Accumulation and Incidence of Infection are Critical in the Characterization of Rice Tungro Bacilliform Virus (RTBV) Resistance in Rice

Analysis by enzyme-linked immunosorbent assay showed that Rice tungro bacilliform virus (RTBV) accumulated in a cyclic pattern from early to late stages of infection in tungro-susceptible variety, Taichung Native 1 (TN1), and resistant variety, Balimau Putih, singly infected with RTBV or co-infected with RTBV+Rice tungro spherical virus (RTSV). These changes in virus accumulation resulted in differences in RTBV levels and incidence of infection. The virus levels were expressed relative to those of the susceptible variety and the incidence of infection was assessed at different weeks after inoculation. At a particular time point, RTBV levels in TN1 or Balimau Putih singly infected with RTBV were not significantly different from the virus level in plants co-infected with RTBV+RTSV. The relative RTBV levels in Balimau Putih either singly infected with RTBV or co-infected with RTBV+RTSV were significantly lower than those in TN1. The incidence of RTBV infection varied at different times in Balimau Putih but not in TN1, and to determine the actual infection, the number of plants that became infected at least once anytime during the 4wk observation period was considered. Considering the changes in RTBV accumulation, new parameters for analyzing RTBV resistance were established. Based on these parameters, Balimau Putih was characterized having resistance to virus accumulation although the actual incidence of infection was >75%.

Optimal track access rights allocation for agent negotiation in an open railway market

In open railway access markets, a train service provider (TSP) negotiates with an infrastructure provider (IP) for track access rights. This negotiation has been modeled by a multi-agent system (MAS) in which the IP and TSP are represented by separate software agents. One task of the IP agent is to generate feasible (and preferably optimal) track access rights, subject to the constraints submitted by the TSP agent. This paper formulates an IP-TSP transaction and proposes a branch-and-bound algorithm for the IP agent to identify the optimal track access rights. Empirical simulation results show that the model is able to emulate rational agent behaviors. The simulation results also show good consistency between timetables attained from the proposed methods and those derived by the scheduling principles adopted in practice.

Dwell-time and run-time control for DC mass rapid transit railways

Dwell times at stations and inter-station run times are the two major operational parameters to maintain train schedule in railway service. Current practices on dwell-time and run-time control are that they are only optimal with respect to certain nominal traffic conditions, but not necessarily the current service demand. The advantages of dwell-time and run-time control on trains are therefore not fully considered. The application of a dynamic programming approach, with the aid of an event-based model, to devise an optimal set of dwell times and run times for trains under given operational constraints over a regional level is presented. Since train operation is interactive and of multi-attributes, dwell-time and run-time coordination among trains is a multi-dimensional problem. The computational demand on devising trains' instructions, a prime concern in real-time applications, is excessively high. To properly reduce the computational demand in the provision of appropriate dwell times and run times for trains, a DC railway line is divided into a number of regions and each region is controlled by a dwell- time and run-time controller. The performance and feasibility of the controller in formulating the dwell-time and run-time solutions for real-time applications are demonstrated through simulations.

Service bid comparisons by fuzzy ranking in open railway market timetabling

In an open railway access market, the Infrastructure Provider (IP), upon the receipts of service bids from the Train Service Providers (TSPs), assigns track access rights according to its own business objectives and the merits of the bids; and produces the train service timetable through negotiations. In practice, IP chooses to negotiate with the TSPs one by one in such a sequence that IP optimizes its objectives. The TSP bids are usually very complicated, containing a large number of parameters in different natures. It is a difficult task even for an expert to give a priority sequence for negotiations from the contents of the bids. This study proposes the application of fuzzy ranking method to compare and prioritize the TSP bids in order to produce a negotiation sequence. The results of this study allow investigations on the behaviors of the stakeholders in bid preparation and negotiation, as well as evaluation of service quality in the open railway market.

Intelligent negotiation behaviour model for an open railway access market

In an open railway access market, the provisions of railway infrastructures and train services are separated and independent. Negotiations between the track owner and train service providers are thus required for the allocation of the track capacity and the formulation of the services timetables, in which each party, i.e. a stakeholder, exhibits intelligence from the previous negotiation experience to obtain the favourable terms and conditions for the track access. In order to analyse the realistic interacting behaviour among the stakeholders in the open railway access market schedule negotiations, intelligent learning capability should be included in the behaviour modelling. This paper presents a reinforcement learning approach on modelling the intelligent negotiation behaviour. The effectiveness of incorporating learning capability in the stakeholder negotiation behaviour is then demonstrated through simulation.

Forecasting crashes at the planning level: Simultaneous negative binomial crash model applied in Tucson, Arizona

At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.

Conflict resolution through negotiation in a railway open access market : a multi-agent system approach

Open access reforms to railway regulations allow multiple train operators to provide rail services on a common infrastructure. As railway operations are now independently managed by different stakeholders, conflicts in operations may arise, and there have been attempts to derive an effective access charge regime so that these conflicts may be resolved. One approach is by direct negotiation between the infrastructure manager and the train service providers. Despite the substantial literature on the topic, few consider the benefits of employing computer simulation as an evaluation tool for railway operational activities such as access pricing. This article proposes a multi-agent system (MAS) framework for the railway open market and demonstrates its feasibility by modelling the negotiation between an infrastructure provider and a train service operator. Empirical results show that the model is capable of resolving operational conflicts according to market demand.

Railway junction traffic control by heuristic methods

Traffic conflicts at railway junctions are very conmon, particularly on congested rail lines. While safe passage through the junction is well maintained by the signalling and interlocking systems, minimising the delays imposed on the trains by assigning the right-of-way sequence sensibly is a bonus to the quality of service. A deterministic method has been adopted to resolve the conflict, with the objective of minimising the total weighted delay. However, the computational demand remains significant. The applications of different heuristic methods to tackle this problem are reviewed and explored, elaborating their feasibility in various aspects and comparing their relative merits for further studies. As most heuristic methods do not guarantee a global optimum, this study focuses on the trade-off between computation time and optimality of the resolution.