A simulation model of the control data 6400 scope operating system

This thesis describes a simulation model for the CDC 6400 computer system under the SCOPE 3.3 Operating System

A modelling approach to the evalution of computer system performance

Imperial Users onl

Architectures and GPU-Based Parallelization for Online Bayesian Computational Statistics and Dynamic Modeling

Recent work demonstrates that coupling Bayesian computational statistics methods with dynamic models can facilitate the analysis of complex systems associated with diverse time series, including those involving social and behavioural dynamics. Particle Markov Chain Monte Carlo (PMCMC) methods constitute a particularly powerful class of Bayesian methods combining aspects of batch Markov Chain Monte Carlo (MCMC) and the sequential Monte Carlo method of Particle Filtering (PF). PMCMC can flexibly combine theory-capturing dynamic models with diverse empirical data. Online machine learning is a subcategory of machine learning algorithms characterized by sequential, incremental execution as new data arrives, which can give updated results and predictions with growing sequences of available incoming data. While many machine learning and statistical methods are adapted to online algorithms, PMCMC is one example of the many methods whose compatibility with and adaption to online learning remains unclear. In this thesis, I proposed a data-streaming solution supporting PF and PMCMC methods with dynamic epidemiological models and demonstrated several successful applications. By constructing an automated, easy-to-use streaming system, analytic applications and simulation models gain access to arriving real-time data to shorten the time gap between data and resulting model-supported insight. The well-defined architecture design emerging from the thesis would substantially expand traditional simulation models' potential by allowing such models to be offered as continually updated services. Contingent on sufficiently fast execution time, simulation models within this framework can consume the incoming empirical data in real-time and generate informative predictions on an ongoing basis as new data points arrive. In a second line of work, I investigated the platform's flexibility and capability by extending this system to support the use of a powerful class of PMCMC algorithms with dynamic models while ameliorating such algorithms' traditionally stiff performance limitations. Specifically, this work designed and implemented a GPU-enabled parallel version of a PMCMC method with dynamic simulation models. The resulting codebase readily has enabled researchers to adapt their models to the state-of-art statistical inference methods, and ensure that the computation-heavy PMCMC method can perform significant sampling between the successive arrival of each new data point. Investigating this method's impact with several realistic PMCMC application examples showed that GPU-based acceleration allows for up to 160x speedup compared to a corresponding CPU-based version not exploiting parallelism. The GPU accelerated PMCMC and the streaming processing system can complement each other, jointly providing researchers with a powerful toolset to greatly accelerate learning and securing additional insight from the high-velocity data increasingly prevalent within social and behavioural spheres. The design philosophy applied supported a platform with broad generalizability and potential for ready future extensions. The thesis discusses common barriers and difficulties in designing and implementing such systems and offers solutions to solve or mitigate them

Feasibility study of an Integrated Program for Aerospace vehicle Design (IPAD). Volume 4: IPAD system design

The computing system design of IPAD is described and the requirements which form the basis for the system design are discussed. The system is presented in terms of a functional design description and technical design specifications. The functional design specifications give the detailed description of the system design using top-down structured programming methodology. Human behavioral characteristics, which specify the system design at the user interface, security considerations, and standards for system design, implementation, and maintenance are also part of the technical design specifications. Detailed specifications of the two most common computing system types in use by the major aerospace companies which could support the IPAD system design are presented. The report of a study to investigate migration of IPAD software between the two candidate 3rd generation host computing systems and from these systems to a 4th generation system is included

Software test and evaluation study phase I and II : survey and analysis

Issued as Final report, Project no. G-36-661 (continues G-36-636; includes A-2568

Development of a predictive musculoskeletal hybrid model based on maximum weight lifting task

Manual material handling (MMH), particularly lifting, is one of the main reasons for work-related joint and back injuries. Injuries associated with MMH play a significant role in the economy. Therefore, it is necessary to determine subject-specific maximum lifting weight and explain why these lifting-related injuries occur. However, it is challenging to determine the maximum lifting weight by experiments as it is a time-consuming process and risky for the participants. Computational biomechanical models can reveal the insight of human lifting motion and help us to find the reasons behind lifting-related injuries. Musculoskeletal models are complicated and computationally heavy, making them infeasible for real-time application. Skeletal models are computationally efficient but lack muscle physiology in their formulations. This makes it unable to assess musculoskeletal injuries. A novel hybrid model is introduced in this study to predict maximum lifting weight and lifting motion and to evaluate musculoskeletal injury for that lifting motion. The hybrid predictive model consists of a predictive skeletal module and an Opensim musculoskeletal module to balance the computational speed and physiological accuracy. The skeletal models predict joint torques, joint angle profiles, center of pressure (COP), and ground reaction forces (GRFs) for both symmetric and asymmetric liftings. The predicted joint angles, GRFs and COP are inputted into OpenSim musculoskeletal module to estimate muscle activations and joint reaction forces. The hybrid predictive models are used to analyze joint torques, muscle activations, and lumbar spine joint reaction forces for both symmetric and asymmetric lifting tasks to prevent musculoskeletal injuries. The developed hybrid model is also able to predict maximum lifting weight by using subject-specific dynamic joint strength and assess associated injury risks. The proposed hybrid model is both computationally efficient and generic, and it can be readily applied to other motions as well. The hybrid predictive musculoskeletal model has wide applications for workers’ injury prevention to reduce the risk of musculoskeletal disorders

Performance measurement and evaluation of time-shared operating systems

Time-shared, virtual memory systems are very complex and changes in their performance may be caused by many factors - by variations in the workload as well as changes in system configuration. The evaluation of these systems can thus best be carried out by linking results obtained from a planned programme of measurements, taken on the system, to some model of it. Such a programme of measurements is best carried out under conditions in which all the parameters likely to affect the system's performance are reproducible, and under the control of the experimenter. In order that this be possible the workload used must be simulated and presented to the target system through some form of automatic workload driver. A case study of such a methodology is presented in which the system (in this case the Edinburgh Multi-Access System) is monitored during a controlled experiment (designed and analysed using standard techniques in common use in many other branches of experimental science) and the results so obtained used to calibrate and validate a simple simulation model of the system. This model is then used in further investigation of the effect of certain system parameters upon the system performance. The factors covered by this exercise include the effect of varying: main memory size, process loading algorithm and secondary memory characteristics

Modelling and control of united power flow controller for reinforcement of transmission systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The work involved in the thesis is concentrated on modelling and control of UPFC. The overall objective is to provide effective methods and tools for assessing the impact of UPFC in the reinforcement of transmission systems. The thesis clarifies modelling and control of UPFC into several subproblems, in which the associated models, algorithms and control strategies of UPFC have been systematically reviewed. An electromagnetic transient prototype model of the UPFC has been set up by using its detailed power electronic device as well as its internal closed-loop controller. The problems encountered in the process of building such a model and the way of handling them by EMTP have been discussed. This EMTP-based simulator of SPWM UPFC implemented has provided a useful tool to assist the development and validation of more detailed and practical model of the UPFC for further studies. The steady-state modelling and control for the UPFC has been developed, including: (i) The power injection model of the UPFC suitable for its implementation in an optimal multiplier power flow computation method has been derived in rectangular form. The effectiveness of the proposed algorithm has been compared with the user defined model method. (ii) A systematic method for deriving the control capabilities of the UPFC has been proposed based on predicting the feasibility limit of the system. Using an index derived from optimal multiplier, three dimensional diagrams describing the ranges have been obtained. The results are also verified through the singular value decomposition algorithm. (iii) A power injection model based control method (PIM) has been proposed and implemented to directly derive the UPFC parameters as so to achieve the control objectives. The assumptions, algorithmic process and validation of the PIM have been investigated in detail. Its pros and cons are also discussed. (iv) Five internal limits of the UPFC device have been derived as the constraints to its performance. A complete set of control rules considering these limits as well as their implementation in the PlM have been constructed to form the basis of optimal UPFC control strategies for its steady-state local control. All the above proposed methods are tested and validated on the IEEE 30-bus system, a practical 306-bus system and a meshed network. The thesis concludes by suggesting the future research areas in further UPFC studies

Aerospace Applications of Microprocessors

An assessment of the state of microprocessor applications is presented. Current and future requirements and associated technological advances which allow effective exploitation in aerospace applications are discussed