Advanced Timing and Synchronization Methodologies for Digital VLSI Integrated Circuits

This dissertation addresses timing and synchronization methodologies that are critical to the design, analysis and optimization of high-performance, integrated digital VLSI systems. As process sizes shrink and design complexities increase, achieving timing closure for digital VLSI circuits becomes a significant bottleneck in the integrated circuit design flow. Circuit designers are motivated to investigate and employ alternative methods to satisfy the timing and physical design performance targets. Such novel methods for the timing and synchronization of complex circuitry are developed in this dissertation and analyzed for performance and applicability.Mainstream integrated circuit design flow is normally tuned for zero clock skew, edge-triggered circuit design. Non-zero clock skew or multi-phase clock synchronization is seldom used because the lack of design automation tools increases the length and cost of the design cycle. For similar reasons, level-sensitive registers have not become an industry standard despite their superior size, speed and power consumption characteristics compared to conventional edge-triggered flip-flops.In this dissertation, novel design and analysis techniques that fully automate the design and analysis of non-zero clock skew circuits are presented. Clock skew scheduling of both edge-triggered and level-sensitive circuits are investigated in order to exploit maximum circuit performances. The effects of multi-phase clocking on non-zero clock skew, level-sensitive circuits are investigated leading to advanced synchronization methodologies. Improvements in the scalability of the computational timing analysis process with clock skew scheduling are explored through partitioning and parallelization.The integration of the proposed design and analysis methods to the physical design flow of integrated circuits synchronized with a next-generation clocking technology-resonant rotary clocking technology-is also presented. Based on the design and analysis methods presented in this dissertation, a computer-aided design tool for the design of rotary clock synchronized integrated circuits is developed

Combinatorial Optimisation Problems in Logistics and Scheduling

This thesis presents a variety of problems and results in the fields of logistics and, in particular, of maritime and railways logistics. We first present a brief introduction to these problems, their characteristics, and the role they have in the quest for more efficient and greener global supply chains and transport systems; we also present the methodological tools employed for their solution. After this introduction, each chapter presents one specific problem, and corresponds to a self-contained research paper

Optimal Control of anisotropic Allen–Cahn equations

This thesis is concerned with the solution of an optimal control problem governed by an anisotropic Allen-Cahn equation as a model for, e.g., crystal growth. The first part treats the analytical existence theory and first order optimality conditions of the in time continuous and of the time discretized versions. The state equation is discretized implicitly in time with piecewise constant functions. To this end, we consider a more general quasilinear parabolic equation, where the quasilinear term is strongly monotone and obeys a certain growth condition while the lower order term is potentially non-monotone. The existence of the control-to-state operator and its Lipschitz continuity is shown for the time discretized as well as for the time continuous problem. Then we present for both the existence of global minimizers as well as the convergence of a subsequence of time discrete optimal controls to a global minimizer of the time continuous problem. The results hold in arbitrary space dimensions. Under some further restrictions we are able to show Fréchet differentiability of the in time discretized problem and use this to rigorously set up the first order conditions. For this the anisotropies are required to be smooth enough, which in this thesis is achieved by a suitable regularization. Therefore, the convergence behavior of the optimal controls are studied for a sequence of (smooth) approximations of the former quasilinear term. In addition the simultaneous limit in the approximation and the time step size is considered. For a class covering a large variety of anisotropies we introduce a certain regularization and show the previously formulated requirements. Finally, we will show that the results cannot be straightforwardly transferred to a semi-implicit discretization scheme. In the second part a trust region Newton method is presented, that eventually is used to numerically solve the optimal control problem. Different ways of preconditioning the involved Steihaug-CG solver are discussed and the limits of existing approaches in the present case are worked out. Then, several aspects of the implementation are examined, like the solver for the appearing partial differential equations, parallelization and the utility of adaptive meshes in the context of the control problem. In the final part, various numerical results based on the previously mentioned choice of anisotropies are presented. These include convergence with respect to the regularization parameter, numerical evidence for mesh independent behavior and a thorough discussion of the simulation in several relevant settings. We concentrate on two choices for the anisotropies and in addition include the isotropic case for comparison. Among others, crystal formation and topology changes are addressed and we see that the algorithm is able to handle these. Furthermore, the behavior of various quantities over the course of the algorithm is investigated. Here we observe that the number of Steihaug steps, and therefore the execution time per trust region step, growths considerably towards the end of the algorithm. Finally, we look at the impact of some implementational aspects with respect to execution speed. We observe that the implicit and semi-implicit approaches perform comparably fast if the implementation is suitably optimized. We however conclude that the implicit approach is preferable since it is less sensitive with respect to the regularization and is supported by more theoretical results

Modeling and simulation of polymer flooding including the effects of fracturing

Chemical enhanced oil recovery (EOR) technology has attracted increasing interest in recent years with declining oil production from conventional oil reserves. Water flooding of heterogeneous reservoirs with viscous oil leaves considerable amount of remaining oil even at high producing water cuts. Polymer flooding is a mature EOR technology for augmenting recovery of moderately viscous oil. Water soluble polymers are used to reduce water mobility and improve sweep efficiency. For very viscous oil, polymer flooding is a potential non-thermal approach for minimizing viscous fingering and improving both displacement sweep efficiency and volumetric sweep efficiency. Polymer manufacturing techniques has been significantly advanced since 1980’s, which provides improved polymer quality and keeps polymer price relatively low. Compared with unconventional oil recovery techniques such as hydraulic fracturing, well planned and optimized polymer flooding can be profitable even at pessimistic oil price. It is thus crucial to have a reservoir simulator that is able to accurately model polymer properties and simulate polymer flooding in complex reservoir systems. Polymer rheological behavior is dependent on polymer molecular structure, concentration, Darcy velocity, brine salinity, hardness, permeability, porosity, etc. We improved polymer rheology modeling for heterogeneous reservoirs where permeability varies for orders of magnitude. For an injection well, a large portion of pressure drop is lost near wellbore where apparent polymer viscosity as a function of Darcy velocity varies drastically. Conventional analytical well models fail to capture the non-Newtonian effect of apparent polymer viscosity and make injectivity predictions widely deviated from true solutions especially for coarse-grid simulations. We developed a semi-analytical polymer injectivity model and implemented it into UTCHEM. This model is able to handle both shear-thinning and shear-thickening polymer rheology. It successfully avoids the grid effect and matches fine-grid simulation results and analytical solutions. Another challenge is to model polymer injectivity under fracturing conditions. To maintain an economic polymer injection rate, wellbore pressure may exceed the fracture initiation pressure. We developed a framework to couple a fracture model with UTCHEM. This coupled simulator is able to model fracture propagation during polymer injection. Finally several simulation studies were conducted to show the impacts of polymer rheological behavior, loss of polymer into aquifer, near wellbore effect and fracture propagation.Petroleum and Geosystems Engineerin

Proceedings of the NASA Conference on Space Telerobotics, volume 4

Papers presented at the NASA Conference on Space Telerobotics are compiled. The theme of the conference was man-machine collaboration in space. The conference provided a forum for researchers and engineers to exchange ideas on the research and development required for the application of telerobotic technology to the space systems planned for the 1990's and beyond. Volume 4 contains papers related to the following subject areas: manipulator control; telemanipulation; flight experiments (systems and simulators); sensor-based planning; robot kinematics, dynamics, and control; robot task planning and assembly; and research activities at the NASA Langley Research Center

Proceedings of the Eighth Annual Thermal and Fluids Analysis Workshop: Spacecraft Analysis and Design

This document contains papers presented at the Eighth Annual Thermal and Fluids Analysis Workshop (TFAWS) on Spacecraft Analysis and Design hosted by the NASA/Johnson Space Center (JSC) on September 8-11, 1997, and held at the University of Houston - Clear Lake (UHCL) in the Bayou Building. The Workshop was sponsored by NASA/JSC. Seminars were hosted and technical papers were provided in fluid and thermal dynamics. Seminars were given in GASP, SINDA, SINAPS Plus, TSS, and PHOENICS. Seventeen papers were presented

Weatherford: Undergraduate Catalog 2022-2023

SWOSU presents the 2022-2023 Undergraduate Catalog for the Weatherford campus!https://dc.swosu.edu/und/1033/thumbnail.jp

Techniques for Transparent Parallelization of Discrete Event Simulation Models

Simulation is a powerful technique to represent the evolution of real-world phenomena or systems over time. It has been extensively used in different research fields (from medicine to biology, to economy, and to disaster rescue) to study the behaviour of complex systems during their evolution (symbiotic simulation) or before their actual realization (what-if analysis). A traditional way to achieve high performance simulations is the employment of Parallel Discrete Event Simulation (PDES) techniques, which are based on the partitioning of the simulation model into Logical Processes (LPs) that can execute events in parallel on different CPUs and/or different CPU cores, and rely on synchronization mechanisms to achieve causally consistent execution of simulation events. As it is well recognized, the optimistic synchronization approach, namely the Time Warp protocol, which is based on rollback for recovering possible timestamp-order violations due to the absence of block-until-safe policies for event processing, is likely to favour speedup in general application/ architectural contexts. However, the optimistic PDES paradigm implicitly relies on a programming model that shifts from traditional sequential-style programming, given that there is no notion of global address space (fully accessible while processing events at any LP). Furthermore, there is the underlying assumption that the code associated with event handlers cannot execute unrecoverable operations given their speculative processing nature. Nevertheless, even though no unrecoverable action is ever executed by event handlers, a means to actually undo the action if requested needs to be devised and implemented within the software stack. On the other hand, sequential-style programming is an easy paradigm for the development of simulation code, given that it does not require the programmer to reason about memory partitioning (and therefore message passing) and speculative (concurrent) processing of the application. In this thesis, we present methodological and technical innovations which will show how it is possible, by developing innovative runtime mechanisms, to allow a programmer to implement its simulation model in a fully sequential way, and have the underlying simulation framework to execute it in parallel according to speculative processing techniques. Some of the approaches we provide show applicability in either shared- or distributed-memory systems, while others will be specifically tailored to multi/many-core architectures. We will clearly show, during the development of these supports, what is the effect on performance of these solutions, which will nevertheless be negligible, allowing a fruitful exploitation of the available computing power. In the end, we will highlight which are the clear benefits on the programming model tha