固定化微生物脱除工业酸性废气中H_2S的研究

以H 2软性填料作为氧化亚铁硫杆菌的固定化载体 ,构成了固定床生物反应器。在一定操作条件下 ,考察了固定床生物反应器对Fe2 +的氧化速率 ,最大可达 7.6 7g/ (L·h)。并对固定床生物反应器运行中在载体表面形成的络合物进行了研究 ,X射线衍射证明此络合物为黄钾铁矾 [KFe3(SO4 ) 2 (OH) 6]。     

Optimal management of logistic activities in multi-site environments

The new emerging area of Enterprise Wide Optimization (EWO) has focused the attention in effectively solving the combined production/distribution scheduling problem. The importance of logistic activities performed in multi-site environments comes from the relative magnitude of the associated transportation costs and the good chance of getting large savings on such expenses. This paper first develops an exact MILP mathematical formulation for the multiple vehicle time-window-constrained pickup and delivery (MVPDPTW) problem. The approach is able to account for many-to-many transportation requests, pure pickup and delivery tasks, heterogeneous vehicles and multiple depots. Optimal solutions for a variety of benchmark problems with cluster/random distributions of pickup and delivery locations and limited sizes in terms of customer requests and vehicles have been discovered. However, the computational cost exponentially grows with the number of requests. For large-scale m-PDPTW problems, a local search improvement algorithm steadily providing a better solution through two evolutionary steps is also presented. A neighborhood structure around the starting solution is generated by first allowing multiple request exchanges among nearby trips and then permitting the reordering of nodes on every individual route. If a better set of routes is found, both steps are repeated until no improved solution is discovered. Compact MILP mathematical formulations for both sub-problems have been developed and solved through an efficient branch-and-bound algorithm. A significant number of large-scale m-PDPTW benchmark problems, some of them including up to 100 transportation requests, were successfully solved in reasonable CPU times.     

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.     

Cr对低碳Si-Mn系TRIP钢组织与力学性能的影响

主要研究了Cr对低碳Si-Mn系TRIP钢组织与力学性能的影响。首先利用Formastor-F型膨胀仪测定了含Cr和不含Cr两种低碳钢的连续冷却转变(CCT)曲线,分析指出了Cr对连续退火工艺的潜在影响;然后采用Gleeble-3800热/力模拟试验机对两种钢的薄板试样进行了连续退火模拟实验,并通过拉伸试验测定了力学性能;最后采用金相、扫描电镜、X-射线衍射分析等技术考察分析了两种钢的显微组织。结果表明:含Cr的TRIP钢的组织比较细小,铁素体晶粒近似等轴分布;两种TRIP钢的残余奥氏体含量相近,但含Cr钢的残余奥氏体中的含碳量较高。分析认为这是由于含Cr钢在热轧阶段较易生成细小的组织,而在热处理阶段则抑制贝氏体的生成,最终获得稳定的残余奥氏体。     

食物营养规划培训效果追踪和影响因素分析

本文采用调查问卷,追踪访问了参加食物营养规划培训班的人员一年后的工作开展、培训知识掌握和应用情况.结果表明,这些人员较好地掌握了培训知识,平均掌握率为70%,培训知识和技能应用率平均为46%;性别、年龄、技术职称和部门来源等对培训知识掌握和应用有一定的影响.     

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.