Permeability prediction and construction of 3D geological model: application of neural networks and stochastic approaches in an Iranian gas reservoir

Determination of petrophysical parameters by using available data has a specific importance in exploration and production studies for oil and gas industries. Modeling of corrected permeability as a petrophysical parameter can help in decision making processes. The objective of this study is to construct a comprehensive and quantitative characterization of a carbonate gas reservoir in marine gas field. Artificial neural network is applied for prediction of permeability in accordance with other petrophysical parameters at well location. Correlation coefficient for this method is 84 %. In the study, the geological reservoir model is developed in two steps: First, the structure skeleton of the field is constructed, and then, reservoir property is distributed within it by applying new stochastic methods. Permeability is modeled by three techniques: kriging, sequential Gaussian simulation (SGS) and collocated co-simulation using modeled effective porosity as 3D secondary variable. This paper enhances the characterization of the reservoir by improving the modeling of permeability through a new algorithm called collocated co-simulation. Kriging is very simple in modeling the reservoir permeability, and also, original distribution of the data changes considerably in this model. In addition, the SGS model is noisy and heterogeneous, but it retains the original distribution of the data. However, the addition of a 3D secondary variable in third method resulted in a much more reliable model of permeability.     

A software framework for model predictive control with GenOpt

There is a growing interest in integrated control strategies for building systems with numerous responsive elements, such as solar shading devices, thermal storage and hybrid ventilation systems, both for energy efficiency and for demand response. Model predictive control is a promising way of approaching this challenge. This paper presents a flexible software framework for model predictive control using GenOpt, along with a modified genetic algorithm developed for use within it, and applies it to a case study of demand response by zone temperature ramping in an office space. Various areas for further research and development using this framework are discussed.     

Multiobjective optimization of building design using TRNSYS simulations,genetic algorithm,and Artificial Neural Network

Building optimization involving multiple objectives is generally an extremely time-consuming process. The GAINN approach presented in this study first uses a simulation-based Artificial Neural Network (ANN) to characterize building behaviour, and then combines this ANN with a multiobjective Genetic Algorithm (NSGA-II) for optimization. The methodology has been used in the current study for the optimization of thermal comfort and energy consumption in a residential house. Results of ANN training and validation are first discussed. Two optimizations were then conducted taking variables from HVAC system settings, thermostat programming, and passive solar design. By integrating ANN into optimization the total simulation time was considerably reduced compared to classical optimization methodology. Results of the optimizations showed significant reduction in terms of energy consumption as well as improvement in thermal comfort. Finally, thanks to the multiobjective approach, dozens of potential designs were revealed, with a wide range of trade-offs between thermal comfort and energy consumption.     

圆形封闭水箱非稳态数值模拟

采用数值方法对圆形封闭水箱内放置两根加热管的二维流动传热进行了非稳态数值模拟,探讨了Ra数从104到107四种情况和封闭水箱的加热管不同摆放位置下的流动和换热;对流场和温度场进行了分析,讨论了不同情况下加热管平均努赛尔数(Nuavg)的变化情况。数值模拟结果表明,随着Ra数增大水箱内的流动表现出了很大变化,决定了传热是导热或者是对流;两个水平加热管在水箱存在最佳的放置距离,这样可以使自然对流情况下的换热达到最好。     

AZ31-O镁合金和6061-T6铝合金搅拌摩擦焊接头的显微组织和力学性能(英文)

对3 mm厚的AZ31-O镁合金板和6061-T6铝合金板进行异种材料搅拌摩擦焊。实验中搅拌针的旋转速度为600~1400 r/min,前进速度为20~60 mm/min。结果表明,在旋转速度1000 r/min、前进速度40 mm/min的工艺条件下,可以获得无缺陷的焊接接头。组织观察发现搅拌区的晶粒尺寸要比基材区的明显小很多。在搅拌区形成了复杂的金属流动。显微硬度测试表明搅拌区的硬度分别是不均匀的。拉伸实验结果表明,接头的拉伸强度约为基材AZ31镁合金的76%,或6061铝合金的60%。接头拉伸断口SEM形貌观察表明为脆性断裂。     

A novel approach to enhance outdoor air quality: Pedestrian ventilation system

Higher population density has altered the cities' old landscape with dense areas consisting of high-rise buildings. As a result, detrimental phenomena appeared inside modern cities that threatened the inhabitant's health and comfort. Among these phenomena, the Urban Heat Island (UHI) is known as the most harmful side effect of the urbanization which affects the Outdoor Air Quality (OAQ).     

A variable neighborhood binary particle swarm algorithm for cell layout problem

In this paper, a new mathematical model is proposed for inter- and intra-cell layout problem in cellular manufacturing system. A binary particle swarm optimization algorithm with a new heuristic approach for satisfying the constraints of model is implemented to solve the proposed model. Also, a variable neighborhood search is applied for finding better local optimal solutions. Some sensitivity analyses are carried out to find the best values of PSO parameters. To prove the efficiency of the proposed algorithm, various numerical examples in small, medium, and large sizes in both perfect geometric shapes and random placements are generated and solved.     

The experimental/numerical study to predict mechanical behaviour at the ice/aluminium interface

Each year the accumulation of ice and snow on structures causes damages resulting in very expensive repairs and/or replacements. This paper examines the mechanical behaviour at the ice/aluminium interface in order to develop a numerical model simulating de-icing. We have carried out some systematic experimental tests to determine the necessary supporting experimental data for the numerical models. Thereafter a step by step approach is proposed to predict the realistic mechanical behaviour of the ice as well as at the ice/aluminium interface. More specifically, the brittle cracking theory is used to define the behaviour of ice at high strain rates, and the cohesive material theory is used to model de-icing and damage at the interfaces. These models have been used to simulate the de-icing of the thin aluminium plate under traction. The numerical results obtained using the beam theory show important differences compared to experimental data. Whereas those obtained using the new approach show a good agreement with the experimental data. Calibration of delaminating and cracking parameters has been performed using the experimental observations.     

Abrasion resistance of concrete containing SiO2 and Al2O3 nanoparticles in different curing media

In the present study, abrasion resistance and compressive strength of concrete specimens containing SiO₂ and Al₂O₃ nanoparticles which are cured in different curing media have been investigated. Portland cement was partially replaced by up to 2.0 wt.% SiO₂ and Al₂O₃ nanoparticles and mechanical properties of the produced specimens were measured. Increasing the nanoparticles content have found to increase the abrasion resistance of the specimens which were cured in water and saturated limewater, while this condition was not observed for compressive strength in both curing media. The enhancement of abrasion resistance was more for the specimens containing SiO₂ nanoparticles in both curing media. Since, abrasion resistance and compressive strength of the specimens follow a similar regime by increasing the nanoparticles content when they are cured in saturated limewater, some experimental relationships has been presented to correlate these two properties of concrete for this curing medium. On the whole, it has been concluded that the abrasion resistance of concrete does not only depend on the corresponding compressive strength.     

Reliability analysis and inspection updating by stochastic response surface of fatigue cracks in mixed mode

The analysis of engineering structures under fatigue crack growth aims at ensuring an appropriate reliability level over the entire operational lifetime. This paper deals with a new approach, namely the Stochastic Response Surface, to couple finite element analysis and reliability methods. The stochastic collocation method provides an explicit expression of the limit state function related to fatigue failure. This expression is used in first and second order reliability methods in order to compute the failure probability at a given structural age. When inspection is carried out, the structural reliability can be easily updated in terms of the observed crack length. Two numerical applications dealing with fatigue crack growth are presented to illustrate the proposed method, showing its performance in terms of numerical efficiency and accuracy.