Classical quarks in dual electromagnetic fields

Electromagnetic properties of quark-like particles are examined in a classical field model involving extended dual electromagnetic fields. These can have fractional charges and a confining potential that derives essentially completely from a short-range weaker potential. The combined potentials exhibit an asymptotically free spherical surface and contribute to the masses of the particles. The quarks are shown to have an intrinsic symmetry that describes their structures in hadrons. Multi- quark solutions are easily obtained for both stable and unstable particles. Each quark can undergo simple harmonic motion in a range of frequencies

Capacity formulas in MWPC: some critical reflexions

An approximate analytical expression for "capacitance" of MWPC configurations circulates in the literature since decades and is copied over and over again. In this paper we will try to show that this formula corresponds to a physical quantity that is different from what it is usually thought to stand for

Non-Archimedean character of quantum buoyancy and the generalized second law of thermodynamics

Quantum buoyancy has been proposed as the mechanism protecting the generalized second law when an entropy--bearing object is slowly lowered towards a black hole and then dropped in. We point out that the original derivation of the buoyant force from a fluid picture of the acceleration radiation is invalid unless the object is almost at the horizon, because otherwise typical wavelengths in the radiation are larger than the object. The buoyant force is here calculated from the diffractive scattering of waves off the object, and found to be weaker than in the original theory. As a consequence, the argument justifying the generalized second law from buoyancy cannot be completed unless the optimal drop point is next to the horizon. The universal bound on entropy is always a sufficient condition for operation of the generalized second law, and can be derived from that law when the optimal drop point is close to the horizon. We also compute the quantum buoyancy of an elementary charged particle; it turns out to be negligible for energetic considerations. Finally, we speculate on the significance of the absence from the bound of any mention of the number of particle species in nature.Comment: RevTeX, 16 page

Electric power system concepts for integration of advanced sensor and pulsed loads in the DDG-51 class ships

Advanced weapons and sensors increase demand on the electric power systems of Navy surface combatants, driving the need for fully Integrated Power Systems (IPS) such as those found in the DDG-1000 Zumwalt class of ships. The goal of this paper is to introduce novel power system configurations that could potentially be integrated into future flights of the DDG-51 class to support expanded electric power system capability at reasonable cost. Two concepts are presented: the first addresses the need for additional power for advanced sensor systems and the second addresses the need for a more significant increase in capacity to support higher power electric loads.Center for Electromechanic

A lumped conceptual model to simulate groundwater level time-series

Lumped, conceptual groundwater models can be used to simulate groundwater level time-series quickly and efficiently without the need for comprehensive modelling expertise. A new model of this type, AquiMod, is presented for simulating groundwater level time-series in unconfined aquifers. Its modular design enables users to implement different model structures to gain understanding about controls on aquifer storage and discharge. Five model structures are evaluated for four contrasting aquifers in the United Kingdom. The ability of different model structures and parameterisations to replicate the observed hydrographs is examined. AquiMod simulates the quasi-sinusoidal hydrographs of the relatively uniform Chalk and Sandstone aquifers most efficiently. It is least efficient at capturing the flashy hydrograph of a heterogeneous, fractured Limestone aquifer. The majority of model parameters demonstrate sensitivity and can be related to available field data. The model structure experiments demonstrate the need to represent vertical aquifer heterogeneity to capture the storage-discharge dynamics efficiently

The 4D geometric quantities versus the usual 3D quantities. The resolution of Jackson's paradox

In this paper we present definitions of different four-dimensional (4D) geometric quantities (Clifford multivectors). New decompositions of the torque N and the angular momentum M (bivectors) into 1-vectors N_{s}, N_{t} and M_{s}, M_{t} respectively are given. The torques N_{s}, N_{t} (the angular momentums M_{s}, M_{t}), taken together, contain the same physical information as the bivector N (the bivector M). The usual approaches that deal with the 3D quantities $\mathbf{E}$, $\mathbf{B}$, $\mathbf{F}$, $\mathbf{L}$, $\mathbf{N}$, etc. and their transformations are objected from the viewpoint of the invariant special relativity (ISR). In the ISR it is considered that 4D geometric quantities are well-defined both theoretically and \emph{experimentally} in the 4D spacetime. This is not the case with the usual 3D quantities. It is shown that there is no apparent electrodynamic paradox with the torque, and that the principle of relativity is naturally satisfied, when the 4D geometric quantities are used instead of the 3D quantities.Comment: 13 pages, revte

Using statistically designed experiments for safety system optimization

This paper describes the method of statistically designed experiments (SDE's), used as a structured method to investigate the best setting for a number of decision variables in a system design problem. Traditionally, in the design of safety critical systems, a trial and error type approach is undertaken to achieve a final system that meets the design objectives. This approach can be time consuming and often only an adequate design is found rather than the optimal design for the available resources. Optimal use of resources should be imperative when possible lives are at risk. To demonstrate the practicality of this new structured approach for optimising a safety system design, a high integrity safety system has been used. Each design is analysed using the Binary Decision Diagram analysis technique to establish the system unavailability, which is penalised if the system constraints are exceeded. System constraints indicate the limitations on the resources which can be utilised. The SDE approach highlights good and bad settings for possible design variables. This knowledge can then be used by more sophisticated search techniques. The latter part of this paper analyses the results from the best design generated using the SDE, for further optimisation using localised optimisation approaches

Choosing a heuristic for the “fault tree to binary decision diagram” conversion, using neural networks

Fault-tree analysis is commonly used for risk assessment of industrial systems. Several computer packages are available to carry out the analysis. Despite its common usage there are associated limitations of the technique in terms of accuracy and efficiency when dealing with large fault-tree structures. The most recent approach to aid the analysis of the fault-tree diagram is the BDD (binary decision diagram). To use the BDD, the fault-tree structure needs to be converted into the BDD format. Converting the fault tree is relatively straightforward but requires that the basic events of the tree be ordered. This ordering is critical to the resulting size of the BDD, and ultimately affects the qualitative and quantitative performance and benefits of this technique. Several heuristic approaches were developed to produce an optimal ordering permutation for a specific tree. These heuristic approaches do not always yield a minimal BDD structure for all trees. There is no single heuristic that guarantees a minimal BDD for any fault-tree structure. This paper looks at a selection approach using a neural network to choose the best heuristic from a set of alternatives that will yield the smallest BDD and promote an efficient analysis. The set of possible selection choices are 6 alternative heuristics, and the prediction capacity produced was a 70% chance of the neural network choosing the best ordering heuristic from the set of 6 for the test set of given fault trees

Efficient basic event orderings for binary decision diagrams

Over the last five years significant advances have been made in methodologies to analyse the fault tree diagram. The most successful of these developments has been the Binary Decision Diagram (BDD) approach. The Binary Decision Diagram approach has been shown to improve both the efficiency of determining the minimal cut sets of the fault tree ancl also the accuracy of the calculation procedure used to determine the top event parameters. The BDD technique povides a potential alternative to the traditional approaches based on Kinetic Tree Theory. To utilise the Binary Decision Diagram approach the fault tree structure is first converted to the BDD format. This conversion can be accomplished efficiently but requires the basic events in the fault tree to be placed in an ordering. A poor ordering can result in a Binary Decision Diagram which is not an efficient representation of the fault tree logic structure. The advantages to be gained by utilising the BDD technique rely on the efficiency of the ordering scheme. Alternative ordering schemes have been investigated and no one scheme is appropriate for every tree structure. Research to date has not found any rule based means of determining the best way of ordering basic events for a given fault tree structure. The work presented in this paper takes a machine learning approach based on Genetic Algorithms to select the most appropriate ordering scheme. Features which describe a fault tree structure have been identified and these provide the inputs to the machine learning algorithm. A set of possible ordering schemes has been selected based on previous heuristic work. The objective of the work detailed in the pap:r is to predict the most efficient of the possible ordering alternatives from parameters which describe a fault tree structure