A quantitatively new analog-to-digital converter (ADC) module has been developed during 2010, in co-operation with Tedia Ltd. The module has a 28-bit final resolution and uses 32-bit arithmetic. There are two versions, with four and twelve analog inputs. The 4-input module replaces the original 21-bit version, produced until 2009. The 12-input module is intended to be deployed in small-aperture seismic arrays. The whole set consists of four 3-channel detached modules that can be interconnected with the main module using a cable of up to 100 m in length. This design increases signal-to-noise ratio (SNR) by placing the A/D part as close to the seismograph as possible in order to transmit digital data for storage. All channels are sampled coherently so that all four sensors are automatically synchronised. It allows the detection of local events even though the sync-signal is absent. In other words, the 12-input module is suitable for ad-hoc field measurements even in places where there is no GPS signal. All arrays operated by the Institute of Rock Structure and Mechanics (IRSM) are going to be upgraded to use these modules and some new sites will also be set-up with this innovative equipment (e.g. Lazy in Western Bohemia and Dobrá Voda in Slovakia)., Milan Brož and Jaroslav Štrunc., and Obsahuje bibliografii
The paper follows from the theory of explosion and interaction of an impact wave formed by the explosion and a structure..As a rule, a number of simplifying assumptions must be applied as regards the characteristics of the explosion and of the threatened structure to analyze the structure. As example of dynamic analysis of a new reinforced concrete structure, loaded with a blast wave was used to apply the principles of simpflified ingineering analysis of an explosion-loaded structure. The way of structure failure was analyzed based on time courses of calculated internal forces and displacenets of individual structure elements. The criteria of structural elements failure due to explosion load effects were determined as a part of the dynamic structure response assessment. and Obsahuje seznam literatury
The contribution deals with a deterministic-based structural optimisation (DBSO). The instroductory part of the paper covers a short overview of optimisation algorithms applicable to deterministic-based problems, general DBSO formulation and a target function(s) pattern for structural design. The following part gives attention to particular problem of general RC (reinforced concrete) cross-sectional design subjected to normal force and bending moments (ULS, i.e. ultimate limit state), where basic cross-sectional characteristics (cross-sectional dimensions, steel bars profiles and types of materials constitute an optimisation space with discrete attributes. The target function (including economical and ecological aspects) and principle problem solution(s) is defined and an illlustrative numerical example of a simple rectangular cross-section design is presented. The solution approach is further augmented to RC frame structures problems and a numerical example of a collector tube design is presented. and Obsahuje seznam literatury
Reliability-Based Structural Optimisation (RBSO) incorporates probabilistic structural reliability analysis into structural optimisation. A sample definition of an RBSO problem and its solution are presented for the optimisation of an RC cross-section, which is subjected to combinations of normal force and bending moments. The presented RBSO algorithm utilizes the LHS (Latin Hypercube Sampling) approximate simulation method for reliability computations. Numerical results for the particular data set are presented. and Obsahuje seznam literatury
Train-induced vibration prediction in multi-story buildings can effectively provide the effect of vibrations on buildings. With the results of prediction, the corresponding measures can be used to reduce the influence of the vibrations. To accurately predict the vibrations induced by train in multi-story buildings, support vector machine (SVM) is used in this paper. Since the parameters in SVM are very vital for the prediction accuracy, shuffled frog-leaping algorithm (SFLA) is used to optimize the parameters for SVM. The proposed model is evaluated with the data from field experiments. The results show SFLA can effectively provide better parameter values for SVM and the SVM models outperform a better performance than artificial neural network (ANN) for train-induced vibration prediction