Optimal design of gating systems by gradient search methods

A numerical optimization technique based on gradient-search is applied to obtain an optimal design of a typical gating system used for the gravity process to produce aluminum parts. This represents a novel application of coupling nonlinear optimization techniques with a foundry process simulator, and it is motivated by the fact that a scientifically guided search for better designs based on techniques that take into account the mathematical structure of the problem is preferred to commonly found trial-and-error approaches. The simulator applies the finite volume method and the VOF algorithm for CFD analysis. The direct gradient optimization algorithm, sequential quadratic programming (SQP), was used to solve both a 2D and a 3D gating system design problems using two design variables. The results clearly show the effectiveness of the proposed approach for finding high quality castings when compared with current industry practices.     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

High performance air pollution modeling for a power plant environment

The aim of this work is to provide a high performance air quality simulation using the STEM-II (Sulphur Transport Eulerian Model 2) program, a large-scale pollution modeling application. First, we optimize the sequential program with the aim of increasing data locality. Then, we parallelized the program using OpenMP directives for shared memory systems, and the MPI library for distributed memory machines. Performance results are presented for a SGI O2000 multiprocessor, a Fujitsu AP3000 multicomputer and a Cluster of PCs. Experimental results show that the parallel versions of the code achieve important reductions in the CPU time needed by each simulation. This will allow us to obtain results with adequate speed and reliability for the industrial environment where it is intended to be applied.     

Dynamics of photosynthetic pigments in an Andean lake in Colombia

Guatavita Lake is a small, sheltered tropical high mountain lake located in the Colombian Andes, with a closed watershed and a maximum depth of 25 m. It is the freshwater source for human consumption in nearby small towns, as well as being a site of cultural value for the country, as it was a sacred place to indigenous peoples until about five centuries ago. As the structure and function of this aquatic ecosystem is poorly understood, this study provides initial knowledge on its phytoplankton biomass dynamics, which should be useful in designing efficient management plans with environmental baseline information for similar lakes elsewhere. Physical and chemical data, and photosynthetic pigment concentrations, were measured for the period November 1999–November 2000 at the central vertical axis of Guatavita Lake. The vertical profile of the chlorophyll‐a concentration was closely related to the dissolved inorganic nitrogen concentrations and the thermal stratification characteristics. The maximum chlorophyll‐a concentration in the metalimnion was recorded for the thermal stratification period (November 1999–June 2000). Deepening of the maximum chlorophyll‐a concentration began in February, continuing to June, when it reached its lowest value at the 15 m depth. The phytoplankton biomass values showed an increment within the entire water column at the beginning of the mixing period (July). The relation between the metalimnetic peak of chlorophyll‐a and the dissolved inorganic nitrogen concentration suggests the growth of the phytoplankton community is limited mainly by the availability of nitrogen.     

Real-Time Three-Dimensional Occupancy Grid Modeling for the Detection and Tracking of Construction Resources

Awareness of the construction environment can be improved by automatic three-dimensional (3D) sensing and modeling of job sites in real time. Commercially available 3D modeling approaches based on range scanning techniques are capable of modeling static objects only, and thus cannot model dynamic objects in real time in an environment comprised of moving humans, equipment, and materials. Emerging prototype video range cameras offer an alternative by facilitating affordable, wide field of view, dynamic object tracking at frame rates better than 1?Hz (real time). This paper describes a methodology to model, detect, and track the position of static and moving objects in real time, based on data obtained from video range cameras. Experiments with this technology have produced results that indicate that video rate 3D data acquisition and analysis of construction environments can support effective modeling, detection, and tracking of project resources. This approach to job site awareness has inherent value and broad application. In combination with effective management practices and other sensing techniques, this technology has the potential to significantly improve safety on construction job sites.     

Uncertainty analysis based on sensitivity applied to angle-ply composite structures

This article describes a finite element-based formulation for the statistical analysis of the response of stochastic structural composite systems whose material properties are described by random fields. A first-order technique is used to obtain the second-order statistics for the structural response considering means and variances of the displacement and stress fields of plate or shell composite structures. Propagation of uncertainties depends on sensitivities taken as measurement of variation effects. The adjoint variable method is used to obtain the sensitivity matrix. This method is appropriated for composite structures due to the large number of random input parameters. Dominant effects on the stochastic characteristics are studied analyzing the influence of different random parameters. In particular, a study of the anisotropy influence on uncertainties propagation of angle-ply composites is carried out based on the proposed approach.     

Burner Performance Evaluation Using Test Code

Development of new burner technology is common practice nowadays. Standardized test codes are available to conduct tests to determine operating characteristics and thermal performance of different parts of steam generating units. This paper describes the results of testing performed to evaluate thermal efficiency of a 74.5?kW fire-tube steam generator fired with a new premixed flame burner in comparison to a typical standard-retrofit diffusion flame burner system. Two premixed flame burners sized at 7.6 and 10.1?cm were tested. Testing was performed in accordance with the ASME PTC 4.1 Power Test Code. The evaluation was conducted in the range of small- to mid-sized, natural gas-fired applications, from 1.06?to?2.64×106?kJ/h. The environmental nitrogen oxide (NOx) emissions performance was also compared for both burner technologies. The results of this evaluation indicate that firing the test boiler with the 7.6?cm new burner slightly improves unit thermal efficiency by 4.0–3.3% for a unit load ranging from approximately 1.06?to?1.79×106?kJ/h, respectively. Operation with the 10.1?cm new burner improves the thermal efficiency by approximately 1.6% at 2.32×106?kJ/h. The uncertainty in the measurements used in the efficiency calculations should account for approximately ±1.5% uncertainty in the reported gross efficiency. Reductions in NOx emissions of the order of 10% resulted from operation with the new premixed flame burners.     

Disassembly sequence planning in a disassembly cell context

In this paper a two-phase approach is proposed for determining the optimal disassembly sequence when the disassembly system has a cellular configuration. Operations are first grouped into cells based on the resources they require with the goal of minimizing machine acquisition costs. The aim is to group together those operations that use similar equipment in order to achieve good utilization levels of such equipment. A maximum cell size may be imposed. Once the cells have been formed and the operations have been assigned to them, a metaheuristic algorithm (namely GRASP) is used to search for the disassembly sequence for each product that leads to the minimum number of intercellular movements. To account for uncertainty regarding the condition in which the product may arrive, each disassembly task is assumed to be required with a certain probability, regardless of the other tasks. AND/OR precedence relations among the disassembly tasks are also considered. The proposed approach is illustrated on a randomly generated disassembly problem.     

Bioactivity of antifouling paints based on organotin toxicants

This paper discusses the bioactivity of antifouling paints based on organotin toxicants, such as tributyltin fluoride (TBTF) and triphenyltin fluoride (TPTF). These compounds were used alone or mixed as the main toxicant in formulations. The use of TPTF or mixtures of TPTF and TBTF, with vinyl binders, led to paints with satisfactory bioactivity during a 24 months immersion period. With the same binders, TBTF alone provided only 12 months of antifouling protection. The correlation coefficients calculated from the fouling attachment values and the rosin content in the binder showed that the bioactivity of the tested formulations depended on the solubility of the toxicant in sea water and on the composition and solubility of the binders.