An Integrated Design and Simulation Environment for Rapid Prototyping of Laminate Robotic Mechanisms

Laminate mechanisms are a reliable concept in producing lowcost robots for educational and commercial purposes. These mechanisms are produced using low-cost manufacturing techniques which have improved significantly during recent years and are more accessible to novices and hobbyists. However, iterating through the design space to come up with the best design for a robot is still a time consuming and rather expensive task and therefore, there is still a need for model-based analysis before manufacturing. Until now, there has been no integrated design and analysis software for laminate robots. This paper addresses some of the issues surrounding laminate analysis by introducing a companion to an existing laminate design tool that automates the generation of dynamic equations and produces simulation results via rendered plots and videos. We have validated the accuracy of the software by comparing the position, velocity and acceleration of the simulated mechanisms with the measurements taken from physical laminate prototypes using a motion capture system

Integration of process design and control: A review

There is a large variety of methods in literature for process design and control, which can be classified into two main categories. The methods in the first category have a sequential approach in which, the control system is designed, only after the details of process design are decided. However, when process design is fixed, there is little room left for improving the control performance. Recognizing the interactions between process design and control, the methods in the second category integrate some control aspects into process design. With the aim of providing an exploration map and identifying the potential areas of further contributions, this paper presents a thematic review of the methods for integration of process design and control. The evolution paths of these methods are described and the advantages and disadvantages of each method are explained. The paper concludes with suggestions for future research activities

Complex Networks on a Rock Joint

A complex network approach on a rough fracture is developed. In this manner, some hidden metric spaces (similarity measurements) between apertures profiles are set up and a general evolutionary network in two directions (in parallel and perpendicular to the shear direction) is constructed. Also, an algorithm (COmplex Networks on Apertures: CONA) is proposed in which evolving of a network is accomplished using preferential detachments and attachments of edges (based on a competition and game manner) while the number of nodes is fixed. Also, evolving of clustering coefficients and number of edges display similar patterns as well as are appeared in shear stress, hydraulic conductivity and dilation changes, which can be engaged to estimate shear strength distribution of asperities.Comment: ROCKENG09: Proceedings of the 3rd CANUS Rock Mechanics Symposium, Toronto, May 2009 (Ed: M.Diederichs and G. Grasselli

Generalized London free energy for high-TcT_c vortex lattices

We generalize the London free energy to include four-fold anisotropies which could arise from d-wave pairing or other sources in a tetragonal material. We use this simple model to study vortex lattice structure and discuss neutron scattering, STM, Bitter decoration and $\mu$SR experiments.Comment: REVTeX, 4 pages, 2 .ps figures included, submitted to PR

Integrated design and control using a dynamic inversely controlled process model

The profitability of chemical processes depends on their design and control. If the process design is fixed, there is little room left to improve control performance. Many commentators suggest design and control should be integrated. Nevertheless, the integrated problem is highly complex and intractable. This article proposes an optimization framework using a dynamic inversely controlled process model. The combinatorial complexities associated with the controllers are disentangled from the formulation, but the process and its control structure are still designed simultaneously. The new framework utilizes a multi-objective function to explore the trade-off between process and control objectives. The proposed optimization framework is demonstrated on a case study from the literature. Two parallel solving strategies are applied, and their implementations are explained. They are dynamic optimization based on (i) sequential integration and (ii) full discretization. The proposed integrated design and control optimization framework successfully captured the trade-off between control and process objectives

Optimal selection of control structure using a steady-state inversely controlled process model

The profitability of chemical processes strongly depends on their control systems. The design of a control system involves selection of controlled and manipulated variables, known as control structure selection. Systematic generation and screening alternative control structures requires optimization. However, the size of such an optimization problem is much larger when candidate controllers and their parameters are included and it rapidly becomes intractable. This paper presents a novel optimization framework using the notion of perfect control, which disentangles the complexities of the controllers. This framework reduces the complexity of the problem while ensuring controllability. In addition, the optimization framework has a goal-driven multi-objective function and requires only a steady-state inverse process model. Since dynamic degrees of freedom do not appear in a steady-state analysis, engineering insights are employed for developing the inventory control systems. The proposed optimization framework was demonstrated in a case study of an industrial distillation train

Multi-objective design and operation of Solid Oxide Fuel Cell (SOFC) Triple Combined-cycle Power Generation systems: Integrating energy efficiency and operational safety

Energy efficiency is one of the main pathways for energy security and environmental protection. In fact, the International Energy Agency asserts that without energy efficiency, 70% of targeted emission reductions are not achievable. Despite this clarity, enhancing the energy efficiency introduce significant challenge toward process operation. The reason is that the methods applied for energy-saving pose the process operation at the intersection of safety constraints. The present research aims at uncovering the trade-off between safe operation and energy efficiency; an optimization framework is developed that ensures process safety and simultaneously optimizes energy-efficiency, quantified in economic terms. The developed optimization framework is demonstrated for a solid oxide fuel cell (SOFC) power generation system. The significance of this industrial application is that SOFC power plants apply a highly degree of process integration resulting in very narrow operating windows. However, they are subject to significant uncertainties in power demand. The results demonstrate a strong trade-off between the competing objectives. It was observed that highly energy-efficient designs feature a very narrow operating window and limited flexibility. For instance, expanding the safe operating window by 100% will incur almost 47% more annualized costs. Establishing such a trade-off is essential for realizing energy-saving

Multi-objective design and operation of solid oxide fuel cell (SOFC) Triple Combined-cycle Power Generation Systems: integrating energy efficiency and operational safety

Energy efficiency is one of the main pathways for energy security and environmental protection. In fact, the International Energy Agency asserts that without energy efficiency, 70% of targeted emission reductions are not achievable. Despite this clarity, enhancing the energy efficiency introduce significant challenge toward process operation. The reason is that the methods applied for energy-saving pose the process operation at the intersection of safety constraints. The present research aims at uncovering the trade-off between safe operation and energy efficiency; an optimization framework is developed that ensures process safety and simultaneously optimizes energy-efficiency, quantified in economic terms. The developed optimization framework is demonstrated for a solid oxide fuel cell (SOFC) power generation system. The significance of this industrial application is that SOFC power plants apply a highly degree of process integration resulting in very narrow operating windows. However, they are subject to significant uncertainties in power demand. The results demonstrate a strong trade-off between the competing objectives. It was observed that highly energy-efficient designs feature a very narrow operating window and limited flexibility. For instance, expanding the safe operating window by 100% will incur almost 47% more annualized costs. Establishing such a trade-off is essential for realizing energy-saving