# Browsing by Subject "Simulation methods"

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Item Advanced tabulation techniques for faster dynamic simulation, state estimation and flowsheet optimization(2009-08) Abrol, Sidharth; Edgar, Thomas F.Show more Large-scale processes that are modeled using differential algebraic equations based on mass and energy balance calculations at times require excessive computation time to simulate. Depending on the complexity of the model, these simulations may require many iterations to converge and in some cases they may not converge at all. Application of a storage and retrieval technique, named in situ adaptive tabulation or ISAT is proposed for faster convergence of process simulation models. Comparison with neural networks is performed, and better performance using ISAT for extrapolation is shown. In particular, the requirement of real-time dynamic simulation is discussed for operating training simulators (OTS). Integration of ISAT to a process simulator (CHEMCAD®) using the input-output data only is shown. A regression technique based on partial least squares (PLS) is suggested to approximate the sensitivity without accessing the first-principles model. Different record distribution strategies to build an ISAT database are proposed and better performance using the suggested techniques is shown for different case studies. A modified ISAT algorithm (mISAT) is described to improve the retrieval rate, and its performance is compared with the original approach in a case study. State estimation is a key requirement of many process control and monitoring strategies. Different nonlinear state estimation techniques studied in the past are discussed with their relative advantages/disadvantages. A robust state estimation technique like moving horizon estimation (MHE) has a trade-off between accuracy of state estimates and the computational cost. Implementation of MHE based ISAT is shown for faster state estimation, with an accuracy same as that of MHE. Flowsheet optimization aims to optimize an objective or cost function by changing various independent process variables, subject to design and model constraints. Depending on the nonlinearity of the process units, an optimization routine can make a number of calls for flowsheet (simulation) convergence, thereby making the computation time prohibitive. Storage and retrieval of the simulation trajectories can speed-up process optimization, which is shown using a CHEMCAD® flowsheet. Online integration of an ISAT database to solve the simulation problem along with an outer-loop consisting of the optimization routine is shown using the sequential-modular approach.Show more Item Dynamic response of laterally-loaded piles(2009-05) Thammarak, Punchet; Tassoulas, John LambrosShow more The laterally-loaded pile has long been a topic of research interest. Several models of the soil surrounding a pile have been developed for simulation of lateral pile behavior, ranging from simple spring and dashpot models to sophisticated three-dimensional finite-element models. However, results from the available pile-soil models are not accurate due to inherent approximations or constraints. For the springs and dashpots representation, the real and imaginary stiffness are calculated by idealizing the soil domain as a series of plane-strain slices leading to unrealistic pile behavior at low frequencies while the three-dimensional finite-element analysis is very computationally demanding. Therefore, this dissertation research seeks to contribute toward procedures that are computationally cost-effective while accuracy of the computed response is maintained identical or close to that of the three-dimensional finite-element solution. Based on the fact that purely-elastic soil displacement variations in azimuthal direction are known, the surrounding soil can be formulated in terms of an equivalent one-dimensional model leading to a significant reduction of computational cost. The pile with conventional soil-slice model will be explored first. Next, models with shear stresses between soil slices, including and neglecting the soil vertical displacement, are investigated. Excellent agreement of results from the proposed models with three-dimensional finite-element solutions can be achieved with only small additional computational cost.Show more Item Scheduling of Generalized Cambridge Rings(2009-08) Bauer, Daniel Howard; Hasenbein, John J.Show more A Generalized Cambridge Ring is a queueing system that can be used as an approximate model of some material handling systems used in modern factories. It consists of one or more vehicles that carry cargo from origins to destinations around a loop, with queues forming when cargo temporarily exceeds the capacity of the system. For some Generalized Cambridge Rings that satisfy the usual traffic conditions for stability, it is demonstrated that some nonidling scheduling polices are unstable. A good scheduling policy will increase the efficiency of these systems by reducing waiting times and by therefore also reducing work in process (WIP). Simple heuristic policies are developed which provide substantial improvements over the commonly used first-in-first-out (FIFO) policy. Variances are incorporated into previously developed fluid models that used only means to produce a more accurate partially discrete fluid mean-variance model, which is used to further reduce waiting times. Optimal policies are obtained for some simple special cases, and simulations are used to compare policies in more general cases. The methods developed may be applicable to other queueing systems.Show more Item Simulation of dynamic systems with uncertain parameters(2004) Zhang, Fu; Longoria, Raul G.Show more This dissertation describes numerical methods for representation and simulation of dynamic systems with time invariant uncertain parameters. Simulation is defined as computing a boundary of the system response that contains all the possible behaviors of an uncertain system. This problem features many challenges, especially those associated with minimizing the computational cost due to global optimization. To reduce computational cost, an approximation or surrogate of the original system model is constructed by employing Moving Least Square (MLS) Response Surface Method for non-convex global optimization. For more complicated systems, a gradient enhanced moving least square (GEMLS) response surface is used to construct the surrogate model more accurately and efficiently. This method takes advantage of the fact that parametric sensitivity of an ODE system can be calculated as a by-product with less computational cost when solving the original system. Furthermore, global sensitivity analysis for monotonic testing can be introduced in some cases to further reduce the number of samples. The proposed method has been applied to two engineering applications. The first is hybrid system verification by reachable set computing/approximation. First, the computational burden of using polyhedron for reachable set approximation is reviewed. It is then proven that the boundary of a reachable set is formed only by the trajectories from the boundary of an initial state region. This result reduces the search space from R n to R n−1 . Finally, the GEMLS method proposed is integrated with oriented rectangular hull for reachable set representation and an approximation with improved accuracy and efficiency can be achieved. Another engineering application is model-based fault detection. In this case, a fault free system is modeled as a parametric uncertain system whose parameters belong to a given bounded set. The performance boundary of a fault free system can be acquired by using the proposed approach and then employed as an adaptive threshold. A fault is defined when system parameters do not belong to the set due to malfunction or degradation. Once such a fault occurs, the monitored system performance will extend beyond the normal system boundary predicted.Show more