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#### Year of publication

- 2014 (83) (remove)

Structural optimization has gained considerable attention in the design of structural engineering structures, especially in the preliminary phase.
This study introduces an unconventional approach for structural optimization by utilizing the Energy method with Integral Material Behavior (EIM), based on the Lagrange’s principle of minimum potential energy. An automated two-level optimization search process is proposed, which integrates the EIM, as an alternative method for nonlinear
structural analysis, and the bilevel optimization. The proposed procedure secures the equilibrium through minimizing the potential energy on one level, and on a higher level, a design objective function. For this, the most robust strategy of bilevel optimization, the nested method is used. The function of the potential energy is investigated along with its instabilities for physical nonlinear analysis through principle examples, by which the advantages and limitations using this method are reviewed. Furthermore, optimization algorithms are discussed.
A numerical fully functional code is developed for nonlinear cross section,
element and 2D frame analysis, utilizing different finite elements and is verified
against existing EIM programs. As a proof of concept, the method is applied on selected
examples using this code on cross section and element level. For the former one a
comparison is made with standard procedure, by employing the equilibrium equations
within the constrains. The validation of the element level was proven by a theoretical
solution of an arch bridge and finally, a truss bridge is optimized. Most of the
principle examples are chosen to be adequate for the everyday engineering practice, to
demonstrate the effectiveness of the proposed method.
This study implies that with further development, this method could become just as
competitive as the conventional structural optimization techniques using the Finite
Element Method.

The human body is surrounded by a micro‐climate which results from its convective release of heat. In this study, the air temperature and flow velocity of this micro‐climate were measured in a climate chamber at various room temperatures, using a thermal manikin simulating the heat release of the human being. Different techniques (Particle Streak Tracking, thermography, anemometry, and thermistors) were used for measurement and visualization. The manikin surface temperature was adjusted to the particular indoor climate based on simulations with a thermoregulation model (UCBerkeley Thermal Comfort Model). We found that generally, the micro‐climate is thinner at the lower part of the torso, but expands going up. At the head, there is a relatively thick thermal layer, which results in an ascending plume above the head. However, the micro‐climate shape strongly depends not only on the body segment, but also on boundary conditions: the higher the temperature difference between the surface temperature of the manikin and the air temperature, the faster the air flow in the micro‐climate. Finally, convective heat transfer coefficients strongly increase with falling room temperature, while radiative heat transfer coefficients decrease. The type of body segment strongly influences the convective heat transfer coefficient, while only minimally influencing the radiative heat transfer coefficient.