Doppler cooling of gallium atoms: 2. Simulation in complex multilevel systems

This paper derives a general procedure for the numerical solution of the Lindblad equations that govern the coherences arising from multicoloured light interacting with a multilevel system. A systematic approach to finding the conservative and dissipative terms is derived and applied to the laser cooling of p-block elements. An improved numerical method is developed to solve the time-dependent master equation and results are presented for transient cooling processes. The method is significantly more robust, efficient and accurate than the standard method and can be applied to a broad range of atomic and molecular systems. Radiation pressure forces and the formation of dynamic dark states are studied in the gallium isotope 66Ga.

Wideband and Isotropic Room Acoustics Simulation Using 2-D Interpolated FDTD Schemes

In this paper, a complete method for finite-difference time-domain modeling of rooms in 2-D using compact explicit schemes is presented. A family of interpolated schemes using a rectilinear, nonstaggered grid is reviewed, and the most accurate and isotropic schemes are identified. Frequency-dependent boundaries are modeled using a digital impedance filter formulation that is consistent with locally reacting surface theory. A structurally stable and efficient boundary formulation is constructed by carefully combining the boundary condition with the interpolated scheme. An analytic prediction formula for the effective numerical reflectance is given, and a stability proof provided. The results indicate that the identified accurate and isotropic schemes are also very accurate in terms of numerical boundary reflectance, and outperform directly related methods such as Yee's scheme and the standard digital waveguide mesh. In addition, one particular scheme-referred to here as the interpolated wideband scheme-is suggested as the best scheme for most applications.

Using simulation to assess cardiac first-responder schemes exhibiting stochastic and spatial complexities

A Monte-Carlo simulation-based model has been constructed to assess a public health scheme involving mobile-volunteer cardiac First-Responders. The scheme being assessed aims to improve survival of Sudden-Cardiac-Arrest (SCA) patients, through reducing the time until administration of life-saving defibrillation treatment, with volunteers being paged to respond to possible SCA incidents alongside the Emergency Medical Services. The need for a model, for example, to assess the impact of the scheme in different geographical regions, was apparent upon collection of observational trial data (given it exhibited stochastic and spatial complexities). The simulation-based model developed has been validated and then used to assess the scheme's benefits in an alternative rural region (not a part of the original trial). These illustrative results conclude that the scheme may not be the most efficient use of National Health Service resources in this geographical region, thus demonstrating the importance and usefulness of simulation modelling in aiding decision making.

Physical Models of Wind Instruments : A Generalized Excitation Coupled with a Modular Tube Simulation Platform

To develop real-time simulations of wind instruments, digital waveguides filters can be used as an efficient representation of the air column. Many aerophones are shaped as horns which can be approximated using conical sections. Therefore the derivation of conical waveguide filters is of special interest. When these filters are used in combination with a generalized reed excitation, several classes of wind instruments can be simulated. In this paper we present the methods for transforming a continuous description of conical tube segments to a discrete filter representation. The coupling of the reed model with the conical waveguide and a simplified model of the termination at the open end are described in the same way. It turns out that the complete lossless conical waveguide requires only one type of filter.Furthermore, we developed a digital reed excitation model, which is purely based on numerical integration methods, i.e., without the use of a look-up table.

Efficient Architectural Design Space Exploration via Predictive Modeling

Efficiently exploring exponential-size architectural design spaces with many interacting parameters remains an open problem: the sheer number of experiments required renders detailed simulation intractable.We attack this via an automated approach that builds accurate predictive models. We simulate sampled points, using results to teach our models the function describing relationships among design parameters. The models can be queried and are very fast, enabling efficient design tradeoff discovery. We validate our approach via two uniprocessor sensitivity studies, predicting IPC with only 1–2% error. In an experimental study using the approach, training on 1% of a 250-K-point CMP design space allows our models to predict performance with only 4–5% error. Our predictive modeling combines well with techniques that reduce the time taken by each simulation experiment, achieving net time savings of three-four orders of magnitude.

Invariant Information Local Sub-map Filter (IILSF) for Efficient Simultaneous Localisation and Mapping of Large Environments

This paper presents an Invariant Information Local Sub-map Filter (IILSF) as a technique for consistent Simultaneous Localisation and Mapping (SLAM) in a large environment. It harnesses the benefits of sub-map technique to improve the consistency and efficiency of Extended Kalman Filter (EKF) based SLAM. The IILSF makes use of invariant information obtained from estimated locations of features in independent sub-maps, instead of incorporating every observation directly into the global map. Then the global map is updated at regular intervals. Applying this technique to the EKF based SLAM algorithm: (a) reduces the computational complexity of maintaining the global map estimates and (b) simplifies transformation complexities and data association ambiguities usually experienced in fusing sub-maps together. Simulation results show that the method was able to accurately fuse local map observations to generate an efficient and consistent global map, in addition to significantly reducing computational cost and data association ambiguities.

Defining Simulation Intent

Defining Simulation Intent involves capturing high level modelling and idealisation decisions in order to create an efficient and fit-for-purpose analysis. These decisions are recorded as attributes of the decomposed design space.

An approach to defining Simulation Intent is described utilising three known technologies: Cellular Modelling, the subdivision of space into volumes of simulation significance (structures, gas paths, internal and external airflows etc.); Equivalencing, maintaining a consistent and coherent description
of the equivalent representations of the spatial cells in different analysis models; and Virtual Topology, which offers tools for partitioning and de-partitioning the model without disturbing the manufacturing oriented design geometry. The end result is a convenient framework to which high level analysis attributes can be applied, and from which detailed analysis models can be generated
with a high degree of controllability, repeatability and automation. There are multiple novel aspects to the approach, including its reusability, robustness to changes in model topology and the inherent links created between analysis models at different levels of fidelity and physics.

By utilising Simulation Intent, CAD modelling for simulation can be fully exploited and simulation work-flows can be more readily automated, reducing many repetitive manual tasks (e.g. the definition of appropriate coupling between elements of different types and the application of boundary conditions). The approach has been implemented and tested with practical examples, and
significant benefits are demonstrated.

VEDA:Variation-aware energy-efficient discrete Wavelet Transform architecture

In this paper, we present a unified approach to an energy-efficient variation-tolerant design of Discrete Wavelet Transform (DWT) in the context of image processing applications. It is to be noted that it is not necessary to produce exactly correct numerical outputs in most image processing applications. We exploit this important feature and propose a design methodology for DWT which shows energy quality tradeoffs at each level of design hierarchy starting from the algorithm level down to the architecture and circuit levels by taking advantage of the limited perceptual ability of the Human Visual System. A unique feature of this design methodology is that it guarantees robustness under process variability and facilitates aggressive voltage over-scaling. Simulation results show significant energy savings (74% - 83%) with minor degradations in output image quality and avert catastrophic failures under process variations compared to a conventional design. © 2010 IEEE.

Software-Managed Energy-Efficient Hybrid DRAM/NVM Main Memory

This paper evaluates the viability of user-level software management of a hybrid DRAM/NVM main memory system. We propose an operating system (OS) and programming interface to place data from within the user application. We present a profiling tool to help programmers decide on the placement of application data in hybrid memory systems. Cycle-accurate simulation of modified applications confirms that our approach is more energy-efficient than state-of-the- art hardware or OS approaches at equivalent performance. Moreover, our results are validated on several candidate NVM technologies and a wide set of 14 benchmarks.
The key observation behind this work is that, for the work- loads we evaluated, application objects are too short-lived to motivate migration. Utilizing this property significantly reduces the hardware complexity of hybrid memory systems.

Energy-Efficient In-Memory Data Stores on Hybrid Memory Hierarchies

Increasingly large amounts of data are stored in main memory of data center servers. However, DRAM-based memory is an important consumer of energy and is unlikely to scale in the future. Various byte-addressable non-volatile memory (NVM) technologies promise high density and near-zero static energy, however they suffer from increased latency and increased dynamic energy consumption.

This paper proposes to leverage a hybrid memory architecture, consisting of both DRAM and NVM, by novel, application-level data management policies that decide to place data on DRAM vs. NVM. We analyze modern column-oriented and key-value data stores and demonstrate the feasibility of application-level data management. Cycle-accurate simulation confirms that our methodology reduces the energy with least performance degradation as compared to the current state-of-the-art hardware or OS approaches. Moreover, we utilize our techniques to apportion DRAM and NVM memory sizes for these workloads.

An efficient harmony search with new pitch adjustment for dynamic economic dispatch

A simple yet efficient harmony search (HS) method with a new pitch adjustment rule (NPAHS) is proposed for dynamic economic dispatch (DED) of electrical power systems, a large-scale non-linear real time optimization problem imposed by a number of complex constraints. The new pitch adjustment rule is based on the perturbation information and the mean value of the harmony memory, which is simple to implement and helps to enhance solution quality and convergence speed. A new constraint handling technique is also developed to effectively handle various constraints in the DED problem, and the violation of ramp rate limits between the first and last scheduling intervals that is often ignored by existing approaches for DED problems is effectively eliminated. To validate the effectiveness, the NPAHS is first tested on 10 popular benchmark functions with 100 dimensions, in comparison with four HS variants and five state-of-the-art evolutionary algorithms. Then, NPAHS is used to solve three 24-h DED systems with 5, 15 and 54 units, which consider the valve point effects, transmission loss, emission and prohibited operating zones. Simulation results on all these systems show the scalability and superiority of the proposed NPAHS on various large scale problems.

Sustainable non-automotive vehicles: The simulation challenges

Simulation is a well-established and effective approach to the development of fuel-efficient and low-emissions vehicles in both on-highway and off-highway applications.

The simulation of on-highway automotive vehicles is widely reported in literature, whereas research relating to non-automotive and off-highway vehicles is relatively sparse. This review paper focuses on the challenges of simulating such vehicles and discusses the differences in the approach to drive cycle testing and experimental validation of vehicle simulations. In particular, an inner-city diesel-electric hybrid bus and an ICE (Internal Combustion Engine) powered forklift truck will be used as case studies.

Computer prediction of fuel consumption and emissions of automotive vehicles on standardised drive cycles is well-established and commercial software packages such as AVL CRUISE have been specifically developed for this purpose. The vehicles considered in this review paper present new challenges from both the simulation and drive-cycle testing perspectives. For example, in the case of the forklift truck, the drive cycles involve reversing elements, variable mass, lifting operations, and do not specify a precise velocity-time profile. In particular, the difficulties associated with the prediction of productivity, i.e. the maximum rate of completing a series of defined operations, are discussed. In the case of the hybrid bus, the standardised drive cycles are unrepresentative of real-life use and alternative approaches are required in the development of efficient and low-emission vehicles.

Two simulation approaches are reviewed: the adaptation of a standard automotive vehicle simulation package, and the development of bespoke models using packages such as MATLAB/Simulink.

Resource Efficient Configuration of an Aircraft Assembly Line

The design of efficient assembly systems can significantly contribute to the profitability of products and the competitiveness of manufacturing industries. The configuration of a an efficient assembly line can be supported by suitable methodologies and techniques, such as design for manufacture and assembly, assembly sequence planning, assembly line balancing, lean manufacturing and optimization techniques. In this paper, these methods are applied with reference to the industrial case study of the assembly line of a Skycar light aircraft. The assembly process sequence is identified taking into account the analysis of the assembly structure and the required precedence constraints, and diverse techniques are applied to optimize the assembly line performance. Different line configurations are verified through discrete event simulation to assess the potential increase of efficiency and throughput in a digital environment and propose the most suitable configuration of the assembly line.

Efficient content pushing in IEEE 802.11p vehicular environments

Vehicular networking is a new field that is expected to be widely adopted in the near future. One of the key applications inherent to this novel communications paradigm is content delivery to on-board users. In this paper we focus specifically on broadcast-based content delivery. We propose a content delivery scheme that is optimized for performance in order to improve the maximum amount of data than can be delivered, while also reducing delivery time to a minimum. With this goal our study combines both analytical and simulation results to determine the optimal packet size for content delivery so as to achieve the maximum throughput possible at different distances, and considering both static and mobile receivers. Experimental results show that our optimizations provide efficient delivery of multimedia contents for distances up to 200 meters when relying on IEEE 802.lip based broadcasting. Copyright © 2010 ACM.