System Simulation

It is argued that underlying the Church–Turing hypothesis there is an implicit physical assertion. Here, this assertion is presented explicitly as a physical principle: ‘every finitely realizible physical system can be perfectly simulated by a universal model computing machine operating by finite means’. Classical physics and the universal Turing machine, because the former is continuous and the latter discrete, do not obey the principle, at least in the strong form above. A class of model computing machines that is the quantum generalization of the class of Turing machines is described, and it is shown that quantum theory and the 'universal quantum computer’ are compatible with the principle. Computing machines resembling the universal quantum computer could, in principle, be built and would have many remarkable properties not reproducible by any Turing machine. These do not include the computation of non-recursive functions, but they do include ‘quantum parallelism’, a method ...

SimOS is a simulation environment capable of modeling complete computer systems, including a full operating system and all application programs that run on top of it. Two features help make this possible. First, SimOS provides an extremely fast simulation of system hardware, and the second feature that enables SimOS to model the full operating system is its ability to control the level of simulation detail. Designed for efficient and accurate study of both uniprocessor and multiprocessor systems, SimOS simulates computer hardware in enough detail to run an entire operating system and provides substantial flexibility in the tradeoff between simulation speed and detail

This paper presents an integral predictive and nonlinear robust control strategy to solve the path following problem for a quadrotor helicopter. The dynamic motion equations are obtained by the Lagrange–Euler formalism. The proposed control structure is a hierarchical scheme consisting of a model predictive controller (mpc) to track the reference trajectory together with a nonlinear H∞H∞ controller to stabilize the rotational movements. In both controllers the integral of the position error is considered, allowing the achievement of a null steady-state error when sustained disturbances are acting on the system. Simulation results in the presence of aerodynamic disturbances, parametric and structural uncertainties are presented to corroborate the effectiveness and the robustness of the proposed strategy.

This paper uses a new, large-scale, dynamic life-cycle simulation model to compare the welfare and macroeconomic effects of transitions to five fundamental alternatives to the U.S. federal income tax, including a proportional consumption tax and a flat tax. The model incorporates intragenerational heterogeneity and a detailed specification of alternative tax systems. Simulation results project significant long-run increases in output for some reforms. For other reforms, namely those that seek to insulate the poor and initial older generations from adverse welfare changes, long-run output gains are modest. (JEL H20, C68)

In this paper, a semi-active control of vehicle suspension system with magnetorheological (MR) damper is presented. At first a MR damper working in flow mode is designed. Performance testing is done for this damper with INSTRON machine. Then a mathematical model, Bouc–Wen model, is adopted to characterize the performance of the MR damper. With optimization method in MATLAB® and experimental results of MR damper, the coefficients of the model are determined. Finally, a scaled quarter car model is set up including the model of the MR damper and a semi-active control strategy is adopted to control the vibration of suspension system. Simulation results show that with the semi-active control the vibration of suspension system is well controlled.

Research on more productive and sustainable sugarcane production systems would be aided by a comprehensive simulator of the sugarcane crop that is cognisant of a broader crop-soil-management system. A sugarcane crop model is described that can be deployed in the APSIM framework for agricultural systems simulation. The model operates on a daily time step, grows a leaf canopy, uses intercepted radiation to produce assimilate, and partitions this assimilate into leaf, structural stalk and sugar. The crop physiological processes represented in the model respond to the radiation and temperature environment and are sensitive to water and nitrogen supply. The model simulates growth, water use, N accumulation, sugar dry weight and fresh cane yield for plant and ratoon crops in response to climate, soil, management and genotypic factors. The model was developed on 35 datasets from Australia, Hawaii, South Africa and Swaziland, covering a wide range of crop classes, latitudes, water regimes and nitrogen supply conditions. Coefficients of determination for model predictions compared to observed data included 0.79 for LAI, 0.93 for crop biomass, 0.83 for stalk sucrose and 0.86 for N accumulation in above ground tissues. The particular strengths of this model are discussed in the context of agricultural systems simulation.

The increasing constraints on power consumption in many computing systems point to the need for power modeling and estimation for all components of a system. The Operating System (OS) constitutes a major software component and dissipates a significant portion of total power in many modern application executions. Therefore, modeling OS power is imperative for accurate software power evaluation, as well as power management (e.g. dynamic thermal control and equal energy scheduling) in the light of OS-intensive workloads. This paper characterizes the power behavior of a commercial OS across a wide spectrum of applications to understand OS energy profiles and then proposes various models to cost-effectively estimate its run-time energy dissipation. The proposed models rely on a few simple parameters and have various degrees of complexity and accuracy. Experiments show that compared with cycle-accurate full-system simulation, the model can predict cumulative OS energy to within 1% accurac...

Recently, there has been considerable interest in the use of Model Checking for Systems Biology. Unfortunately, the state space of stochastic biological models is often too large for classical Model Checking techniques. For these models, a statistical approach to Model Checking has been shown to be an effective alternative. Extending our earlier work, we present the first algorithm for performing statistical Model Checking using Bayesian Sequential Hypothesis Testing. We show that our Bayesian approach outperforms current statistical Model Checking techniques, which rely on tests from Classical (aka Frequentist) statistics, by requiring fewer system simulations. Another advantage of our approach is the ability to incorporate prior Biological knowledge about the model being verified. We demonstrate our algorithm on a variety of models from the Systems Biology literature and show that it enables faster verification than state-of-the-art techniques, even when no prior knowledge is available.

... The thermoelectric module is clamped between a cooling jacket and a heater block. The heater block is made from aluminum. ... To control the hot-end temperature T H , the coolant flow through the cooling jacket is turned on and off by two control valves installed in the flow lines. ...