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The main goal of this present study is to determine the performance you can obtain from the implementation of fixed Building Integrated Photovoltaics (BIPV) on one family houses. The study will use a comparative method on one family houses between a flat roof, and a piched roof with two slopes, with different orientations of the plot. These various scenarios respond to urban implementation rules that are particular in urban planning. The calculations were made for a single family house with a built area of 100sqm ...

Regarding to the situation in Romania, the country's total agricultural surface of 14.946 million ha, an area of 6.367 million ha (42.6%), with slopes greater than 5%, is prone to water erosion and other processes associated. Of these, over 900,000 ha are affected by very strong and excessive erosion. The study aims to quantify the soil loss by erosion process and to specify the main factor affecting the erosion development in the study area using geoprocessing techniques and the erosion predictive model Revised U...

The solution of subsoil-structure interaction is affected by several factors as a choice of interaction model, influence of physical-nonlinear behaviour of structure and co-effects of the upper structure and the foundation structure. The subsoil-structure interaction can be solve by application of analytical methods or numerical methods - eg. Finite Element Method (FEM) or Boundary Element Method (BEM). FEM was used for numerical analysis performed in this article. Many different interaction models implemented in ...

Linear programming problems are optimization problems where the objective function and constraints are all linear. Mathematica has a collection of algorithms for solving linear optimization problems with real variables, accessed via LinearProgramming, FindMinimum, FindMaximum, NMinimize, NMaximize, Minimize, and Maximize. LinearProgramming gives direct access to linear program- ming algorithms, provides the most flexibility for specifying the methods used, and is the most efficient for large-scale problems. FindMi...

Constrained optimization problems are problems for which a function f (x) is to be minimized or maximized subject to constraints ? (x) . Here f : Rn ? R is called the objective function and F(x) is a Boolean-valued formula. In Mathematica the constraints ? (x) can be an arbitrary Boolean combination of equations g (x) ?0 , weak inequalities g (x) >=0, strict inequalities g(x)> 0, x is integer and x>0 statements. A point u ? Rn is said to be a global minimum of f subject to constraints F if u satisfies the constrai...

Numerical algorithms for constrained nonlinear optimization can be broadly categorized into gradient-based methods and direct search methods. Gradient search methods use first derivatives (gradients) or second derivatives (Hessians) information. Examples are the sequential quadratic programming (SQP) method, the augmented Lagrangian method, and the (nonlinear) interior point method. Direct search methods do not use derivative information. Examples are Nelder|Mead, genetic algorithm and differential evolution, and ...

The energetic requalification of the existing buildings stock is a key question in the attainment of the ambitious program regarding the energy efficiency proposed by European Union. There are several measures taken to increase the energy efficiency, both for new buildings and for existing buildings, such us the 20 ? 20 ? 20 EU Policy and the Nearly Zero Energy Buildings goal set by the Energy Performance of Buildings Directive 2010/31/EC, which gives the guidelines to be followed in order to attenuate the energy ...