Simulation techniques in an artificial society model

Artificial society refers to a generic class of agent-based simulation models used to discover global social structures and collective behavior produced by simple local rules and interaction mechanisms. Artificial society models are applicable in a variety of disciplines, including the modeling of chemical and biological processes, natural phenomena, and complex adaptive systems. We focus on the underlying simulation techniques used in artificial society discrete-event simulation models, including model time evolution and computational performance.;Although for some applications synchronous time evolution is the correct modeling approach, many other applications are better represented using asynchronous time evolution. We claim that asynchronous time evolution can eliminate potential simulation artifacts produced using synchronous time evolution. Using an adaptation of a popular artificial society model, we show that very different output can result based solely on the choice of asynchronous or synchronous time evolution. Based on the event list implementation chosen, the use of discrete-event simulation to incorporate asynchronous time evolution can incur a substantial loss in computational performance. Accordingly, we evaluate select event list implementations within the artificial society simulation model and demonstrate that acceptable performance can be achieved.;In addition to the artificial society model, we show that transforming from a synchronous to an asynchronous system proves beneficial for scheduling resources in a parallel system. We focus on non-FCFS job scheduling policies that permit jobs to backfill, i.e., to move ahead in the queue, given that they do not delay certain previously submitted jobs. Instead of using a single queue of jobs, we propose a simple yet effective backfilling scheduling policy that effectively separates short from long jobs by incorporating multiple queues. By monitoring system performance, our policy adapts its configuration parameters in response to severe changes in the job arrival pattern and/or resource demands. Detailed performance comparisons via simulation using actual parallel workload traces indicate that our proposed policy consistently outperforms traditional backfilling in a variety of contexts

Chip-controlled 3-D complex cutting tool insert design and virtual manufacturing simulation

Designing suitable tools for the turning operation is of vital interest to manufacturers. The tool inserts used nowadays adopt complex geometric shapes. A question facing many manufacturers is how to effectively design complex shaped tool inserts and how to prove the validity of such design. One of the important criteria for selecting inserts is the ability to control chip formation and chip breaking;The research work described in this dissertation attempted to bring innovation into the cutting tool insert design process by using feature-based modeling and by proposing a predictive chip model and integrating it into the design process. Such model integration makes the tool insert design a much more effective process and also enhances the decision-making required in insert design;A new 3-D kinematic chip model was developed to depict chip behavior in a complex groove insert. The model derived showed the analytical relationships between chip shape parameters and chip motion parameters. This dissertation explained how the kinematic model could be modified to take into account all possible 3-D complex groove shapes. A mathematical model was also developed from experimental data to serve the current need for cutting tool design;Other research work presented in this dissertation is the simulation of the machining process in a virtual environment. The virtual machining simulation can be of great benefit for researchers in manufacturing to use the platform as a testbed for product development and testing

Data Bandwidth Reduction Techniques For Distributed Embedded Simulatio

Maintaining coherence between the independent views of multiple participants at distributed locations is essential in an Embedded Simulation environment. Currently, the Distributed Interactive Simulation (DIS) protocol maintains coherence by broadcasting the entity state streams from each simulation station. In this dissertation, a novel alternative to DIS that replaces the transmitting sources with local sources is developed, validated, and assessed by analytical and experimental means. The proposed Concurrent Model approach reduces the communication burden to transmission of only synchronization and model-update messages. Necessary and sufficient conditions for the correctness of Concurrent Models in a discrete event simulation environment are established by developing Behavioral Congruence ¨B(EL, ER) and Temporal Congruence ¨T(t, ER) functions. They indicate model discrepancies with respect to the simulation time t, and the local and remote entity state streams EL and ER, respectively. Performance benefits were quantified in terms of the bandwidth reduction ratio BR=N/I obtained from the comparison of the OneSAF Testbed Semi-Automated Forces (OTBSAF) simulator under DIS requiring a total of N bits and a testbed modified for the Concurrent Model approach which required I bits. In the experiments conducted, a range of 100 d BR d 294 was obtained representing two orders of magnitude reduction in simulation traffic. Investigation showed that the models rely heavily on the priority data structure of the discrete event simulation and that performance of the overall simulation can be enhanced by an additional 6% by improving the queue management. A low run-time overhead, self-adapting storage policy called the Smart Priority Queue (SPQ) was developed and evaluated within the Concurrent Model. The proposed SPQ policies employ a lowcomplexity linear queue for near head activities and a rapid-indexing variable binwidth calendar queue for distant events. The SPQ configuration is determined by monitoring queue access behavior using cost scoring factors and then applying heuristics to adjust the organization of the underlying data structures. Results indicate that optimizing storage to the spatial distribution of queue access can decrease HOLD operation cost between 25% and 250% over existing algorithms such as calendar queues. Taken together, these techniques provide an entity state generation mechanism capable of overcoming the challenges of Embedded Simulation in harsh mobile communications environments with restricted bandwidth, increased message latency, and extended message drop-outs

Modelling the impact of acid deposition on the hydrochemistry of the Loch Dee catchments, S.W. Scotland

This work describes an investigation into the impact of acid deposition on the hydrochemistry of the three main tributary catchments at Loch Dee in Southwest Scotland. The research covers two main objectives. First, the hydrochemical processes that determine the observed streamwater chemistry are examined empirically through the determination of the hydrochemical budgets for each sub-catchment. Second, the ability of the Integrated Lake Watershed Acidification Study model (ILWAS) to simulate the observed hydrochemical processes is evaluated. From the hydrochemical budgets two major factors are identified as responsible for the spatial variability in the streamwater chemistry at Loch Dee. These factors are the underlying geology and land-use management techniques. The role of afforestation is difficult to judge due to the immaturity of the forest. However, the budgets indicate that any influence is a result of the pre-afforestation ploughing and drainage rather than the presence of the trees. On a temporal basis the hydrochemical budgets show considerable variability on both a monthly and an annual timescale, with the variability in the streamwater outputs of bases and nutrients primarily related to the variability in precipitation quantity. The budgets also indicate that, particularly on an annual timescale, the dry deposition of sulphate and hence of acidity to the catchment varies considerably. Furthermore, on a monthly timescale, the temporal variation in the budgets indicates that the conservative ion chloride can be physically stored within the catchments. This finding has severe implications for the estimation of dry deposition inputs and for the utilisation of simple hydrochemical models. The ILWAS model is generally able to simulate the hydrological response of both catchments. However, the chemical simulations of both catchments are considerably smoothed and bear little resemblance to the observed data. This failure is ascribed to the large number of input variables for which site-specific data are not available, together with the use of monthly averaged precipitation quality to drive the model. Sensitivity analysis of the model indicates that the most critical input variables are the soil depth and soil solution chemistry, and that the majority of the input variables can be considered as calibration parameters. Given the subsequent large number of calibration parameters it is suggested that a unique calibration of the model will rarely be possible. Consequently, it is concluded that the primary use of the ILWAS model will be as an explanatory tool for examining conceptual ideas about the hydrochemical processes that determine acidification. The model's value as a management tool to help mitigate the effects of anthropogenically derived changes in surface water chemistry will be extremely limited

Impact Models to Assess Regional Acidification

Sensitive receptors such as soil and fresh bodies of water are at the end of a long chain of events in the process of regional acidification. This chain begins thousands of kilometers upwind at the emitters of acidifying pollutants. The topics covered in this book are important in the study of regional acidification for two reasons. First, it is important to assess the sensitivity of terrestrial and aquatic ecosystems to the deposition of acidifying pollutants. If the sensitivity of an ecosystem is known, then international control strategies can be developed to reduce deposition in the receptor areas of greatest importance. This is an important factor in designing the most effective strategies because of the very high costs of reducing emissions of acidifying pollutants. Second, it is important to be able to predict changes in ecosystems for decades into the future, whether it be an improvement owing to decreases in acidifying emissions or, alas, a further deterioration because control strategies are nonexistent or inadequate. In either event, it is important to be able to judge the results of our actions. Decision makers tend to be mistrustful of models unless they can judge their reliability. The application and testing of the models in Part III of this book cover, therefore, an important facet of model building. This book is an ideal companion to another book that is forthcoming from the Transboundary Air Pollution Project at IIASA: The RAINS Model of Acidification: Science and Strategies in Europe. The latter book is a description of the development and use of the Regional Acidification INformation and Simulation (RAINS) model, an integrated assessment model for developing and determining control strategies to reduce regional acidification in Europe. Much of the research described in this book forms part of the foundation of the RAINS model. These two books cover a great deal of the present knowledge about assessing and dealing with a very important environmental problem in Europe regional acidification