396,720 research outputs found

    A fully Distributed Parallel Global Search Algorithm

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    The n-dimensional direct search algorithm DIRECT of Jones,Perttunen, and Stuckman has attracted recent attention from the multidisciplinary design optimization community. Since DIRECT only requires function values (or ranking)and balances global exploration with local refinement better than n-dimensional bisection, it is well suited to the noisy function values typical of realistic simulations. While not efficient for high accuracy optimization, DIRECT is appropriate for the sort of global design space exploration done in large scale engineering design. Direct and pattern search schemes have the potential to exploit massive parallelism, but efficient use of massively parallel machines is nontrivial to achieve. This paper presents a fully distribute control version of DIRECT that is designed for massively parallel (distribute memory architectures. Parallel results are presented for a multidisciplinary design optimization problem — configuration design of a high speed civil transport

    The Incidence of Inverter Incidents: Understanding and Quantifying Contributions to Risk in Systems with Large Amounts of Inverter-Based Resources

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    Renewable energy is an important and growing percentage of the total power supply. Additionally, non-wires alternatives, which are meant to substitute for the construction of more transmission lines, are increasing in quantity as the demand for electrical power increases. Many non-wires alternatives take the form of renewable energy resources and batteries, and are distributed over short distances through neighborhoods and communities. Inverters are used to connect these DC resources to the AC grid. However, there is growing industry concern that the disconnect function that is inherent to interconnection standards for inverter-based resources has the potential to result in a cascading failure if voltages deviate significantly from nominal. This thesis studies the conditions under which a cascading inverter collapse of this sort could occur. More specifically, it identifies engineering design parameters, such as time constants, that influence the speed and nature of these cascades, using a new model called Time-Dependant Inverters Model (TiDIM). While this model is preliminary, the results suggest that risk increases with a number of factors including large transmission or distribution line impedances, a large variance in inverter voltage setpoints, and an inappropriate number of inverter-based resources that can contribute to supplying too much or not enough power. Next, the thesis characterizes the risk at which one may expect this sort of event to occur as a function of line impedance and the resultant voltage magnitude. It is found that a greater proportion of inverter-connected power in the grid is associated with a higher probability of collapse, and a greater variance in inverter behavior is associated with a wider transition band, which is defined in this thesis as the range of impedances/voltages where the probability of collapse is an uncertain. Lastly, the thesis identifies cost-effective strategies to reduce the likelihood of such an event

    Program slicing by calculation

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    Program slicing is a well known family of techniques used to identify code fragments which depend on or are depended upon specific program entities. They are particularly useful in the areas of reverse engineering, program understanding, testing and software maintenance. Most slicing methods, usually oriented towards the imperatice or object paradigms, are based on some sort of graph structure representing program dependencies. Slicing techniques amount, therefore, to (sophisticated) graph transversal algorithms. This paper proposes a completely different approach to the slicing problem for functional programs. Instead of extracting program information to build an underlying dependencies' structure, we resort to standard program calculation strategies, based on the so-called Bird-Meertens formalism. The slicing criterion is specified either as a projection or a hiding function which, once composed with the original program, leads to the identification of the intended slice. Going through a number of examples, the paper suggests this approach may be an interesting, even if not completely general, alternative to slicing functional programsFundação para a Ciência e a Tecnologia (FCT

    Strategies for multiobjective genetic algorithm development: Application to optimal batch plant design in process systems engineering

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    This work deals with multiobjective optimization problems using Genetic Algorithms (GA). A MultiObjective GA (MOGA) is proposed to solve multiobjective problems combining both continuous and discrete variables. This kind of problem is commonly found in chemical engineering since process design and operability involve structural and decisional choices as well as the determination of operating conditions. In this paper, a design of a basic MOGA which copes successfully with a range of typical chemical engineering optimization problems is considered and the key points of its architecture described in detail. Several performance tests are presented, based on the influence of bit ranging encoding in a chromosome. Four mathematical functions were used as a test bench. The MOGA was able to find the optimal solution for each objective function, as well as an important number of Pareto optimal solutions. Then, the results of two multiobjective case studies in batch plant design and retrofit were presented, showing the flexibility and adaptability of the MOGA to deal with various engineering problems

    Automated verification of shape, size and bag properties.

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    In recent years, separation logic has emerged as a contender for formal reasoning of heap-manipulating imperative programs. Recent works have focused on specialised provers that are mostly based on fixed sets of predicates. To improve expressivity, we have proposed a prover that can automatically handle user-defined predicates. These shape predicates allow programmers to describe a wide range of data structures with their associated size properties. In the current work, we shall enhance this prover by providing support for a new type of constraints, namely bag (multi-set) constraints. With this extension, we can capture the reachable nodes (or values) inside a heap predicate as a bag constraint. Consequently, we are able to prove properties about the actual values stored inside a data structure

    Simulation Modeling of Alternative Staffing and Task Prioritization in Manual Post-Distribution Cross Docking Facilities

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    Many supply chains have grown increasingly complex, which has led to the development of different facility types. One such facility is known as a post-distribution cross docking system (Post-C). In these facilities, bulk sorted product is received from various suppliers. Each product has its own destination, so the bulk package is broken, sorted by destination, and staged by destination. Typical processing includes: sort received goods by product type; break bulk and sort out goods by destination; move palletized goods to the staging areas of their respective destinations. This paper compares a global staffing policy (in which all workers may perform any task) to a dedicated staffing policy (in which groups of workers are assigned specific tasks). Through comparisons of the two models, it was found the dedicated worker model’s benefits from reduced change-over outweigh the lower worker utilization it experiences
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