Vakdyn, a program to calculate time dependent pressure profiles

We describe a program that calculates time dependent pressure profiles in conductance limited vacuum systems where the pump speed and out-gassing can vary as a function of time. In this way pump down or pressure bumps due to temporary leaks or out-gassing can be visualized and analyzed.     

Space, time and geometry

Space, time, and their pseudo-euclidian geometry have an algebraic origin from the Hamiltonian quaternions and their product systems. They have unique mathematical properties yielding also the large dimensionless fundamental constants and particle masses of physics. All natural laws must be Lorentz-invariant, also the gravitational field equations. Einstein's application of Riemannian geometry is only a calculation device valid only for very small dimensionless gravitational potentials. In this case his field equations transform asymptotically into linear field equations for tensor potentials very similar to the electromagnetic ones for vector potentials. All numerical observations known up to date only this case. Kazuo Kondo et al. used this calculation device for many physical problems related with tensors.     

Failure time distributions for complex equipment

The exponential distribution is inadequate as a failure time model for most components; however, under certain conditions (in particular, that component failure rates are small and mutually independent, and failed components are immediately replaced or perfectly repaired), it is applicable to complex repairable systems with large numbers of components in series, regardless of component distributions, as shown by Drenick in 1960. This result implies that system behavior may become simpler as more components are added. We review necessary conditions for the result and present some simulation studies to assess how well it holds in systems with finite numbers of components. We also note that Drenick's result is analogous to similar results in other systems disciplines, again resulting in simpler behavior as the number of entities in the system increases.     

Structure optimization of multi-state system with time redundancy

In this article, a multi-state system with time redundancy where each system element has its own operation time is considered. In addition, the system total task must be performed during the restricted time. The reliability optimization problem is treated as finding the minimal cost system structure subject to the reliability constraint. A method for reliability optimization for systems with time redundancy is proposed. This method is based on the universal generating function technique for the reliability index computation and on genetic algorithm for the optimization. It provides a solution for the optimization problem for the complex series–parallel system and for the system with bridge topology. Two types of systems will illustrate the approach: systems with ordinary hot reserve and systems with work sharing between elements connected in parallel. Numerical examples are also given.     

On fast integration for time variant structural reliability

In evaluating structural reliability under stochastic loadings, the system parameters such as stiffness, damping, strength, excitation frequency content and duration, etc., are usually assumed given. In reality, however, these quantities are seldom perfectly known. Their uncertainties may play a major role as far as the overall structural reliability is concerned. This paper reviews currently available methods to include this parameter uncertainties and a new method is also proposed. The accuracy and analytical and numerical efforts required are compared. Through numerical examples on systems under dynamic excitation, collapse of ductile or brittle redundant systems, the advantages of the proposed method are demonstrated.     

Carrier-phase time transfer

We have conducted several time-transfer experiments using the phase of the GPS carrier rather than the code, as is done in current GPS-based time-transfer systems. Atomic clocks were connected to geodetic GPS receivers; we then used the GPS carrier-phase observations to estimate relative clock behavior at 6-minute intervals. GPS carrier-phase time transfer is more than an order of magnitude more precise than GPS common view time transfer and agrees, within the experimental uncertainty, with two-way satellite time-transfer measurements for a 2400 km baseline. GPS carrier-phase time transfer has a stability of 100 ps, which translates into a frequency uncertainty of about two parts in 10(-15) for an average time of 1 day.     

A stochastic model of empty-vehicle travel time and load request service time in light-traffic material handling systems

Empty-vehicle travel time plays an important role in the design and control of automated guided vehicle systems (AGVSs). However, many analytical models of these systems assume the amount of empty-vehicle travel time is the same as the loaded-vehicle travel time. This paper examines empty-vehicle travel time in AGVSs with low traffic intensity. The model uses a discrete-time Markov chain based on vehicle location and represents dispatching rules in the one-step transition matrix. The model can be used to compute moments and cumulative probabilities for the empty-vehicle travel time. Coupled with the loaded-vehicle travel time and the loading/unloading time, similar results can be obtained for the time to service a load request.     

Cure progress in epoxy systems: dependence on temperature and time

We have developed an analytical formula for the cure progress of epoxy systems as a function of both time t and temperature T. Complex viscosity η* or the storage modulus G′ are used as the measures of the cure progress. The equation is based on the shape of the isothermal viscosity vs. time curves typically found for thermoset systems; temperature dependence of the isothermal parameters is established, resulting in a single equation. The equation has been tested for two vastly different thermoset epoxy systems and found to provide reliable predictive capabilities. The equation seems applicable for predicting curing progress of most thermoset systems, without a limitation to epoxies. Moreover, the equation can be used for discriminating accurate experimental results from less accurate ones.     

Quantum state diffusion and time correlation functions

Abstract

In computing the spectra of quantum mechanical systems one encounters the Fourier transforms of time correlation functions, as given by the quantum regression theorem for systems described by master equations. Quantum state diffusion (QSD) gives a useful method of solving these problems by unravelling the master equation into stochastic trajectories; but there is no generally accepted definition of a time correlation function for a single QSD trajectory. In this paper we show how QSD can be used to calculate these spectra directly; by formally solving the equations which arise, we arrive at a natural definition for a two-time correlation function in QSD, which depends explicitly on the stochastic noise of the particular trajectory, and which agrees in the mean with the ensemble average definition of correlation functions.     

Energy-consistent time integration for nonlinear viscoelasticity

This paper is concerned with the numerical solution of the evolution equations of thermomechanical systems, in such a way that the scheme itself satisfies the laws of thermodynamics. Within this framework, we present a novel integration scheme for the dynamics of viscoelastic continuum bodies in isothermal conditions. This method intrinsically satisfies the laws of thermodynamics arising from the continuum, as well as the possible additional symmetries. The resulting solutions are physically accurate since they preserve the fundamental physical properties of the model. Furthermore, the method gives an excellent performance with respect to robustness and stability. Proof for these claims as well as numerical examples that illustrate the performance of the novel scheme are provided.     

Approximation of the probability distribution of the customer waiting time under an (r,s, q) inventory policy in discrete time

We study a single-item periodic review (r, s, q) inventory policy. Customer demands arrive on a discrete (e.g. daily) time axis. The replenishment lead times are discrete random variables. This is the time model underlying the majority of the Advanced Planning Software systems used for supply chain management in industrial practice. We present an approximation of the probability distribution of the customer waiting time, which is a customer-oriented performance criterion that captures supplier–customer relationships of adjacent nodes in supply chains. The quality of the approximation is demonstrated with the help of a simulation experiment.     

Multi-stage,multi-facility,batch production system with deterministic demand over a finite time horizon

Researches on multi-stage production systems, so far, have tended to schedule production according to the overall optimal batch size of the entire shop with little consideration of the influence of the individual stages of production on the batch sizes that are considered optimal. The authors have attempted, in this paper, to investigate the effects of scheduling according to the optimality of the respective production stages. The results are compared with those of the more common case of overall optimal batch scheduling     

Time and time again

In the study of human-machine systems, the need to have a model of the user is by now taken for granted. The model can be used both as support for design and analysis and as a representation of the user that resides somewhere in the machine. When it comes to the practice of modelling, two characteristic approaches can be recognized. The first focuses on the how of modelling, and is concerned mainly with the structure and contents of models. The second focuses on what is being modelled, and is concerned mainly with the functioning or performance of the model. The first approach has dominated human-machine systems research for several decades, and has led to orthodoxy in modelling by which certain structural characteristics are accepted without questioning. This unreflective attitude to modelling has been criticised several times, although with little effect. In taking the second approach and focusing on what should be modelled, two important issues are that human performance varies in level of control, i.e. in terms of how orderly it is, and that thinking and acting take time-- and occur in a context where time is limited. Although it is clearly essential that user models can account for these characteristics, very few existing models are capable of doing so because they focus on internal information processing rather than on performance in a dynamic environment. The paper describes a type of functional model, called contextual control models, which shows how it is possible to account for both different control modes and how performance is affected by time. Indeed, control and time are intimately linked and loss of one may lead to a loss of the other. The contextual control model distinguishes among four characteristic control modes (strategic, tactical, opportunistic and scrambled) and two time parameters (time to evaluate, time to select) that are seen relative to the available time. Finally, a number of applications of contextual control models are described.     

Recovering the delay time from time series applying the nearest-neighbor method

A novel method based on applying the nearest-neighbor method is proposed for recovering the delay time of delayed-feedback systems from their time series. The parameters of the method can be chosen within wide limits and the method itself remains efficient at very high levels of the dynamic and measurement noise.     

Efficient algorithms for approximate time separation of events

Finding bounds on time separation of events is a fundamental problem in the verification and analysis of asynchronous and concurrent systems. Unfortunately, even for systems without repeated events or choice, computing exact bounds on time separation of events is an intractable problem when both min and max type timing constraints are present. In this paper, we describe a method for approximating min and max type constraints, and develop a polynomial-time algorithm for computing approximate time separation bounds in choice-free systems without repeated events. Next, we develop a pseudo-polynomial time technique for analysing a class of asynchronous systems in which events repeat over time. Unlike earlier works, our algorithms can analyse systems with both min and max type timing constraints efficiently. Although the computed bounds are conservative in the worst-case, experimental results indicate that they are fairly accurate in practice. We present formal proofs of correctness of our algorithms, and demonstrate their efficiency and accuracy by applying them to a suite of benchmarks. A complete asynchronous chip has been modelled and analysed using the proposed technique, revealing potential timing problems (already known to designers) in the datapath design.     

The role of time frames in design decision-making

This paper discusses the value of time frame discrepancies as a means of accounting for certain aspects of uncertainty confronting design decision-makers. Such discrepancies are distinguished from organizational lag by reference to a systems framework. Three case studies indicate the capabilities of a provisional taxonomy for the identification of time frames appropriate to each level of planning and design activity.     

Attractor coverage time,time dimension,and its relation to capacity dimension

We have studied the time to complete coverage of a chaotic attractor by cells as a function of the cell size. This dependence is described with good precision by a power law. The system attractor is characterized by a new quantity called the time dimension by analogy with the capacity dimension. A relation between the two values has been studied. For a homogeneous chaotic attractor characterized by a uniform invariant probability density distribution, the two dimensions coincide. In the case of an inhomogeneous chaotic attractor, the time dimension is greater than the capacity one.     

The up and down time distribution in a 1 out of n system with general life time and repair time distributions

In repairable systems with redundancy, failed units can be replaced by spare units in order to reduce system down time. The failed units are sent to a repair shop or manufacturer for maintenance and are subsequently returned for re-use.In this paper we consider a 1 out of n system with cold standby and we assume that repaired machines are as ‘good-as-new’. We derive an approximation method for the distribution of the up time and the down time of the system in case of a general failure distribution and a general repair time distribution. This allows the model to be used in a wide variety of applications.     

Form invariance of coordinate pulsar time metrics

Generalized models are obtained for barycentric pulsar time intervals in reference systems moving in space. It is shown that the observed intervals are determined by pulsar rotation parameters whose values agree in inertial and moving reference systems with an estimated error. Barycentric and topocentric time intervals are compared for pulsars B1937+21 and B0329+54. Translated from Izmeritel’naya Tekhnika, No. 5, pp. 40–45, April, 2009.     

Inventory and lead time planning with lead-time-sensitive demand

Supply and order lead times can have substantial effects on operations performance and perceived customer service, particularly under uncertain customer demand. Certain customers place a high premium on shorter order lead times, while others may be willing to trade a longer lead time for a lower price. This paper studies a problem in which a supplier wishes to determine the best positioning of a product with respect to order lead time and price. We consider a continuous review inventory replenishment system, where the difference between the procurement lead time and promised sales order lead time influences both cycle stock and safety stock costs, and procurement costs may increase as a result of investment in procurement lead time reduction. We provide models and methods for determining the best combination of price and sales lead time for systems with high economies of scale when demand depends on both sales lead time and price. Our results indicate that for a broad range of practical settings, such systems employ a pure make-to-stock policy or a policy that sets sales lead time equal to the procurement lead time at optimality.