Evaluating and classifying contaminated areas based on loss functions using annealing simulations

This paper presents a methodology based on geostatistical theory for quantifying the risks associated with heavy-metal contamination in the harbor area of Santana, Amapa State, Northern Brazil. In this area there were activities related to the commercialization of manganese ore from Serra do Navio. Manganese and arsenic concentrations at unsampled sites were estimated by postprocessing results from stochastic annealing simulations; the simulations were used to test different criteria for optimization, including average, median, and quantiles. For classifying areas as contaminated or uncontaminated, estimated quantiles based on functions of asymmetric loss showed better results than did estimates based on symmetric loss, such as the average or the median. The use of specific loss functions in the decision-making process can reduce the costs of remediation and health maintenance. The highest global health costs were observed for manganese. (c) 2008 Elsevier B.V. All rights reserved

First charge collection and position-precision data on the medium-resistivity silicon strip detectors before and after neutron irradiation up to 2x10(14) n/cm(2)

Test strip detectors of 125 mu m, 500 mu m, and 1 mm pitches with about 1 cm(2) areas have been made on medium-resistivity silicon wafers (1.3 and 2.7 k Ohm cm). Detectors of 500 mu m pitch have been tested for charge collection and position precision before and after neutron irradiation (up to 2 x 10(14) n/cm(2)) using 820 and 1030 nm laser lights with different beam-spot sizes. It has been found that for a bias of 250 V a strip detector made of 1.3 k Ohm cm (300 mu m thick) can be fully depleted before and after an irradiation of 2 x 10(14) n/cm(2). For a 500 mu m pitch strip detector made of 2.7 k Ohm cm tested with an 1030 nm laser light with 200 mu m spot size, the position reconstruction error is about 14 mu m before irradiation, and 17 mu m after about 1.7 x 10(13) n/cm(2) irradiation. We demonstrated in this work that medium resistivity silicon strip detectors can work just as well as the traditional high-resistivity ones, but with higher radiation tolerance. We also tested charge sharing and position reconstruction using a 1030 nm wavelength (300 mu m absorption length in Si at RT) laser, which provides a simulation of MIP particles in high-physics experiments in terms of charge collection and position reconstruction, (C) 1999 Elsevier Science B.V. All rights reserved.

First charge collection and position-precision data on the medium-resistivity silicon strip detectors before and after neutron irradiation up to 2x10(14) n/cm(2)

Test strip detectors of 125 mu m, 500 mu m, and 1 mm pitches with about 1 cm(2) areas have been made on medium-resistivity silicon wafers (1.3 and 2.7 k Ohm cm). Detectors of 500 mu m pitch have been tested for charge collection and position precision before and after neutron irradiation (up to 2 x 10(14) n/cm(2)) using 820 and 1030 nm laser lights with different beam-spot sizes. It has been found that for a bias of 250 V a strip detector made of 1.3 k Ohm cm (300 mu m thick) can be fully depleted before and after an irradiation of 2 x 10(14) n/cm(2). For a 500 mu m pitch strip detector made of 2.7 k Ohm cm tested with an 1030 nm laser light with 200 mu m spot size, the position reconstruction error is about 14 mu m before irradiation, and 17 mu m after about 1.7 x 10(13) n/cm(2) irradiation. We demonstrated in this work that medium resistivity silicon strip detectors can work just as well as the traditional high-resistivity ones, but with higher radiation tolerance. We also tested charge sharing and position reconstruction using a 1030 nm wavelength (300 mu m absorption length in Si at RT) laser, which provides a simulation of MIP particles in high-physics experiments in terms of charge collection and position reconstruction, (C) 1999 Elsevier Science B.V. All rights reserved.

A Monte Carlo simulation of morphology and structure for thin films of symmetric triblock copolymer after quenching and annealing

Self-assembly thin films of symmetric triblock copolymer after annealing and quenching were examined by an effective Monte Carlo simulation method. The defects in the ordered lamellae of the thin films after quenching, which were dependent on the initialization of copolymer melts, are removed in the thin films after annealing. The mean-square gyration radius and end-to-end distance of copolymer chains in the thin films after annealing are smaller than those in the thin films after quenching because of the complete relaxation of polymer during annealing. We also find that the density of A block in the region near to the surface is higher than that in the interior of the thin films. As a result, it is different from the thin films of symmetric A(n)B(n) diblock copolymer, in which surface ordering forms before the interior, that ordering phenomena occurs first in the interior region in the thin films of symmetric A(n)B(m)A(n). triblocl copolymer.

Robot path planning in dynamic environments using a simulated annealing based approach

Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.

Work Softening And Annealing Hardening Of Deformed Nanocrystalline Nickel

We reported that work softening takes place during room-temperature rolling of nanocrystalline Ni at an equivalent strain of around 0.30. The work softening corresponds to a strain-induced phase transformation from a face-centered cubic (fcc) to a body-centered cubic (bcc) lattice. The hardness decreases with increasing volume fraction of the bcc phase. When the deformed samples are annealed at 423 K, a hardening of the samples takes place. This hardening by annealing can be attributed to a variety of factors including the recovery transformation from the bcc to the fcc phase, grain boundary relaxation, and retardation of dislocation gliding by microtwins.

Aplicação da técnica simulated annealing na investigação da ciclagem de nitrogênio na inteface água-sedimento

Neste trabalho é apresentado a aplicação de um método de otimização a fim de estimar parâmetros que normalmente estão presentes na modelagem matemática da dinâmica de espécies químicas na interface água-sedimento. O Problema Direto aqui consistiu na simulação das concentrações das espécies orgânicas e inorgânicas (amônia e nitrato) de nitrogênio, num ambiente idealizado, o qual foi fracionado em quatro camadas: uma camada de água (1 metro) e três camadas de sedimento (0-1 cm, 1-2 cm e 2-10 cm). O Problema Direto foi resolvido pelo Método de Runge Kutta, tendo sido gerada uma simulação de 50 dias. Na estimativa dos coeficientes de difusão e porosidade foi aplicado o Método Simulated Annealing (SA). A eficiência da estratégia aqui adotada foi avaliada através do confronto entre dados experimentais sintéticos e as concentrações calçadas pela solução do Problema Direto, adotando-se os parâmetros estimados pela SA. O melhor ajuste entre dados experimentais e valores calculados se deu quando o parâmetro estimado foi a porosidade. Com relação à minimização da função objetivo, a estimativa desse parâmetro também foi a que exigiu menor esforço computacional. Após a introdução de um ruído randômico às concentrações das espécies nitrogenadas, a técnica SA não foi capaz de obter uma estimativa satisfatória para o coeficiente de difusão, com exceção da camada 0-1 cm sedimentar. Para outras camadas, erros da ordem de 10 % foram encontrados (para amônia na coluna dágua, pro exemplo). Os resultados mostraram que a metodologia aqui adotada pode ser bastante promissora enquanto ferramenta de gestão de corpos dágua, especialmente daqueles submetidos a um regime de baixa energia, como lagos e lagoas costeiras.

Emitter of hetero-junction solar cells created using pulsed rapid thermal annealing

In this paper, we use a pulsed rapid thermal processing (RTP) approach to create an emitter layer of hetero-junction solar cell. The process parameters and crystallization behaviour are studied. The structural, optical and electric properties of the crystallized films are also investigated. Both the depth of PN junction and the conductivity of the emitter layer increase with the number of RTP pulses increasing. Simulation results show that efficiencies of such solar cells can exceed 15% with a lower interface recombination rate, but the highest efficiency is 11.65% in our experiments.

Stochastic protein folding simulation in the three-dimensional HP-model

We present results from three-dimensional protein folding simulations in the HP-model on ten benchmark problems. The simulations are executed by a simulated annealing-based algorithm with a time-dependent cooling schedule. The neighbourhood relation is determined by the pull-move set. The results provide experimental evidence that the maximum depth D of local minima of the underlying energy landscape can be upper bounded by D < n(2/3). The local search procedure employs the stopping criterion (In/delta)(D/gamma) where m is an estimation of the average number of neighbouring conformations, gamma relates to the mean of non-zero differences of the objective function for neighbouring conformations, and 1-delta is the confidence that a minimum conformation has been found. The bound complies with the results obtained for the ten benchmark problems. (c) 2008 Elsevier Ltd. All rights reserved.

Population-based local search for protein folding simulation in the MJ energy model and cubic lattices

We present experimental results on benchmark problems in 3D cubic lattice structures with the Miyazawa-Jernigan energy function for two local search procedures that utilise the pull-move set: (i) population-based local search (PLS) that traverses the energy landscape with greedy steps towards (potential) local minima followed by upward steps up to a certain level of the objective function; (ii) simulated annealing with a logarithmic cooling schedule (LSA). The parameter settings for PLS are derived from short LSA-runs executed in pre-processing and the procedure utilises tabu lists generated for each member of the population. In terms of the total number of energy function evaluations both methods perform equally well, however. PLS has the potential of being parallelised with an expected speed-up in the region of the population size. Furthermore, both methods require a significant smaller number of function evaluations when compared to Monte Carlo simulations with kink-jump moves. (C) 2009 Elsevier Ltd. All rights reserved.

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Intelligent energy resource management considering vehicle-to-grid: A simulated annealing approach

This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

Solving the Vehicle Routing Problem with Genetic ALgorithm and Simulated Annealing

This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.