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Investigation Of The Seismic Behaviour Of Infill Masonry Using Numerical Modelling Approaches
(2017)
Masonry is a widely spread construction type which is used all over the world for different types of structures. Due to its simple and cheap construction, it is used as non-structural as well as structural element. In frame structures, such as
reinforced concrete frames, masonry may be used as infill. While the bare frame itself is able to carry the loads when it comes to seismic events, the infilled frame is not able to warp freely due to the constrained movement. This restraint results in a complex interaction between the infill and the surrounding frame, which may lead to severe damage to the infill as well as the surrounding frame. The interaction is studied in different projects and effective approaches for the description of the behavior are still lacking. Experimental programs are usually quite expensive, while numerical models, once validated, do offer an efficient approach for the investigation of the interaction when horizontally loaded. In order to study the numerous parameters influencing the seismic load bearing behavior, numerical models may be used. Therefore, this contribution presents a numerical approach for the simulation of infill masonry in reinforced concrete frames. Both parts, the surrounding frame as well as the infill are represented by micro modelling approaches to correctly take into account the different types of failure. The adopted numerical model describes the inelastic behavior of the system, as indicated by the obtained results of the overall structural response as well as the formation of damage in the infilled wall. Comparison of the numerical and experimental results highlights the valuable contribution of numerical simulations in the study and design of infilled frames. As damage of the infill masonry may occur in-plane due to the interaction as well as out-of-plane due to the low vertical load, both directions of loading are investigated.
The article presents the investigation of the seismic behaviour of a modern URM building located in the municipality of Finale Emilia in province of Modena, Northern Italy. The building is situated in the centre of the series of the 2012 Northern Italy earthquakes and has not suffered any damage during the earthquake series in 2012. The observed earthquake resistance of the building is compared with predicted resistances based on linear and nonlinear design approaches according to Eurocode. Furthermore, probabilistic analyses based on nonlinear calculation models taking into account scattering of the most relevant input parameters are carried out to identify their influence to the results and to derive fragility curves.
Investigation of TRPV1 loss-of-function phenotypes in transgenic shRNA expressing and knockout mice
(2008)
In the Laser Powder Bed Fusion (LPBF) process, parts are built out of metal powder material by exposure of a laser beam. During handling operations of the powder material, several influencing factors can affect the properties of the powder material and therefore directly influence the processability during manufacturing. Contamination by moisture due to handling operations is one of the most critical aspects of powder quality. In order to investigate the influences of powder humidity on LPBF processing, four materials (AlSi10Mg, Ti6Al4V, 316L and IN718) are chosen for this study. The powder material is artificially humidified, subsequently characterized, manufactured into cubic samples in a miniaturized process chamber and analyzed for their relative density. The results indicate that the processability and reproducibility of parts made of AlSi10Mg and Ti6Al4V are susceptible to humidity, while IN718 and 316L are barely influenced.
Single-photon emission tomography (SPET) with the amino acid analogue l-3-[123I]iodo-α-methyl tyrosine (IMT) is helpful in the diagnosis and monitoring of cerebral gliomas. Radiolabelled amino acids seem to reflect tumour infiltration more specifically than conventional methods like magnetic resonance imaging and computed tomography. Automatic tumour delineation based on maximal tumour uptake may cause an overestimation of mean tumour uptake and an underestimation of tumour extension in tumours with circumscribed peaks. The aim of this study was to develop a program for tumour delineation and calculation of mean tumour uptake which takes into account the mean background activity and is thus optimised to the problem of tumour definition in IMT SPET. Using the frequency distribution of pixel intensities of the tomograms a program was developed which automatically detects a reference brain region and draws an isocontour region around the tumour taking into account mean brain radioactivity. Tumour area and tumour/brain ratios were calculated. A three-compartment phantom was simulated to test the program. The program was applied to IMT SPET studies of 20 patients with cerebral gliomas and was compared to the results of manual analysis by three different investigators. Activity ratios and chamber extension of the phantom were correctly calculated by the automatic analysis. A method based on image maxima alone failed to determine chamber extension correctly. Manual region of interest analysis in patient studies resulted in a mean inter-observer standard deviation of 8.7%±6.1% (range 2.7%–25.0%). The mean value of the results of the manual analysis showed a significant correlation to the results of the automatic analysis (r = 0.91, P<0.0001 for the uptake ratio; r = 0.87, P<0.0001 for the tumour area). We conclude that the algorithm proposed simplifies the calculation of uptake ratios and may be used for observer-independent evaluation of IMT SPET studies. Three-dimensional tumour recognition and transfer to co-registered morphological images based on this program may be useful for the planning of surgical and radiation treatment.
RGB-D sensors such as the Microsoft Kinect or the Asus Xtion are inexpensive 3D sensors. A depth image is computed by calculating the distortion of a known infrared light (IR) pattern which is projected into the scene. While these sensors are great devices they have some limitations. The distance they can measure is limited and they suffer from reflection problems on transparent, shiny, or very matte and absorbing objects. If more than one RGB-D camera is used the IR patterns interfere with each other. This results in a massive loss of depth information. In this paper, we present a simple and powerful method to overcome these problems. We propose a stereo RGB-D camera system which uses the pros of RGB-D cameras and combine them with the pros of stereo camera systems. The idea is to utilize the IR images of each two sensors as a stereo pair to generate a depth map. The IR patterns emitted by IR projectors are exploited here to enhance the dense stereo matching even if the observed objects or surfaces are texture-less or transparent. The resulting disparity map is then fused with the depth map offered by the RGB-D sensor to fill the regions and the holes that appear because of interference, or due to transparent or reflective objects. Our results show that the density of depth information is increased especially for transparent, shiny or matte objects.
The existence of several mobile operating systems, such as Android and iOS, is a challenge for developers because the individual platforms are not compatible with each other and require separate app developments. For this reason, cross-platform approaches have become popular but lack in cloning the native behavior of the different operating systems. Out of the plenty cross-platform approaches, the progressive web app (PWA) approach is perceived as promising but needs further investigation. Therefore, the paper at hand aims at investigating whether PWAs are a suitable alternative for native apps by developing a PWA clone of an existing app. Two surveys are conducted in which potential users test and evaluate the PWA prototype with regard to its usability. The survey results indicate that PWAs have great potential, but cannot be treated as a general alternative to native apps. For guiding developers when and how to use PWAs, four design guidelines for the development of PWA-based apps are derived based on the results.
• Most of the edible forest mushrooms are mycorrhizal and depend on carbohydrates produced by the associated trees. Fruiting patterns of these fungi are not yet fully understood since climatic factors alone do not completely explain mushroom occurrence.
• The objective of this study was to retrospectively find out if changing tree growth following an increment thinning has influenced the diversity patterns and productivity of associated forest mushrooms in the fungus reserve La Chanéaz, Switzerland.
• The results reveal a clear temporal relationship between the thinning, the growth reaction of trees and the reaction of the fungal community, especially for the ectomycorrhizal species. The tree-ring width of the formerly suppressed beech trees and the fruit body number increased after thinning, leading to a significantly positive correlation between fruit body numbers and tree-ring width.
• Fruit body production was influenced by previous annual tree growth, the best accordance was found between fruit body production and the tree-ring width two years previously.
• The results support the hypothesis that ectomycorrhizal fruit body production must be linked with the growth of the associated host trees. Moreover, the findings indicate the importance of including mycorrhizal fungi as important players when discussing a tree as a carbon source or sink.
The investigation of the possibility to determine various characteristics of powder heparin (n = 115) was carried out with infrared spectroscopy. The evaluation of heparin samples included several parameters such as purity grade, distributing company, animal source as well as heparin species (i.e. Na-heparin, Ca-heparin, and heparinoids). Multivariate analysis using principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), and partial least squares – discriminant analysis (PLS-DA) were applied for the modelling of spectral data. Different pre-processing methods were applied to IR spectral data; multiplicative scatter correction (MSC) was chosen as the most relevant.
Obtained results were confirmed by nuclear magnetic resonance (NMR) spectroscopy. Good predictive ability of this approach demonstrates the potential of IR spectroscopy and chemometrics for screening of heparin quality. This approach, however, is designed as a screening tool and is not considered as a replacement for either of the methods required by USP and FDA.
The molecular weight properties of lignins are one of the key elements that need to be analyzed for a successful industrial application of these promising biopolymers. In this study, the use of 1H NMR as well as diffusion-ordered spectroscopy (DOSY NMR), combined with multivariate regression methods, was investigated for the determination of the molecular weight (Mw and Mn) and the polydispersity of organosolv lignins (n = 53, Miscanthus x giganteus, Paulownia tomentosa, and Silphium perfoliatum). The suitability of the models was demonstrated by cross validation (CV) as well as by an independent validation set of samples from different biomass origins (beech wood and wheat straw). CV errors of ca. 7–9 and 14–16% were achieved for all parameters with the models from the 1H NMR spectra and the DOSY NMR data, respectively. The prediction errors for the validation samples were in a similar range for the partial least squares model from the 1H NMR data and for a multiple linear regression using the DOSY NMR data. The results indicate the usefulness of NMR measurements combined with multivariate regression methods as a potential alternative to more time-consuming methods such as gel permeation chromatography.
Although several successful applications of benchtop nuclear magnetic resonance (NMR) spectroscopy in quantitative mixture analysis exist, the possibility of calibration transfer remains mostly unexplored, especially between high- and low-field NMR. This study investigates for the first time the calibration transfer of partial least squares regressions [weight average molecular weight (Mw) of lignin] between high-field (600 MHz) NMR and benchtop NMR devices (43 and 60 MHz). For the transfer, piecewise direct standardization, calibration transfer based on canonical correlation analysis, and transfer via the extreme learning machine auto-encoder method are employed. Despite the immense resolution difference between high-field and low-field NMR instruments, the results demonstrate that the calibration transfer from high- to low-field is feasible in the case of a physical property, namely, the molecular weight, achieving validation errors close to the original calibration (down to only 1.2 times higher root mean square errors). These results introduce new perspectives for applications of benchtop NMR, in which existing calibrations from expensive high-field instruments can be transferred to cheaper benchtop instruments to economize.
Isomeric state in ¹³⁴ La
(1981)
Isomeric state in ¹³⁶ La
(1981)
Isomeric states in ¹³⁴ Ba
(1980)
Isomeric states in ¹³⁴ Ba
(1980)
IT Service Deployment
(2007)
Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.
Selective Laser Melting (SLM) is one of the Additive Manufacturing (AM) technologies applicable for producing complex geometries which are typically expensive or difficult to fabricate using conventional methods. This process has been extensively investigated experimentally for various metals and the fabrication process parameters have been established for different applications; however, fabricating 3D glass objects using SLM technology has remained a challenge so far although it could have many applications. This paper presents a summery on various experimental evaluations of a material database incorporating the build parameters of glass powder using the SLM process for jewelry applications.
Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability.
K0 production in e+e− annihilations at 30 GeV center of mass energy. TASSO Collaboration
(1980)
K3 User Guide
(2000)
Frequency mixing magnetic detection (FMMD) is a sensitive and selective technique to detect magnetic nanoparticles (MNPs) serving as probes for binding biological targets. Its principle relies on the nonlinear magnetic relaxation dynamics of a particle ensemble interacting with a dual frequency external magnetic field. In order to increase its sensitivity, lower its limit of detection and overall improve its applicability in biosensing, matching combinations of external field parameters and internal particle properties are being sought to advance FMMD. In this study, we systematically probe the aforementioned interaction with coupled Néel–Brownian dynamic relaxation simulations to examine how key MNP properties as well as applied field parameters affect the frequency mixing signal generation. It is found that the core size of MNPs dominates their nonlinear magnetic response, with the strongest contributions from the largest particles. The drive field amplitude dominates the shape of the field-dependent response, whereas effective anisotropy and hydrodynamic size of the particles only weakly influence the signal generation in FMMD. For tailoring the MNP properties and parameters of the setup towards optimal FMMD signal generation, our findings suggest choosing large particles of core sizes dc > 25 nm nm with narrow size distributions (σ < 0.1) to minimize the required drive field amplitude. This allows potential improvements of FMMD as a stand-alone application, as well as advances in magnetic particle imaging, hyperthermia and magnetic immunoassays.
In this chapter, the key technologies and the instrumentation required for the subsurface exploration of ocean worlds are discussed. The focus is laid on Jupiter’s moon Europa and Saturn’s moon Enceladus because they have the highest potential for such missions in the near future. The exploration of their oceans requires landing on the surface, penetrating the thick ice shell with an ice-penetrating probe, and probably diving with an underwater vehicle through dozens of kilometers of water to the ocean floor, to have the chance to find life, if it exists. Technologically, such missions are extremely challenging. The required key technologies include power generation, communications, pressure resistance, radiation hardness, corrosion protection, navigation, miniaturization, autonomy, and sterilization and cleaning. Simpler mission concepts involve impactors and penetrators or – in the case of Enceladus – plume-fly-through missions.
Knowledge Management
(2001)
Knowledge-based productivity in “low-tech” industries: evidence from firms in developing countries
(2014)
Using firm-level data from five developing countries—Brazil, Ecuador, South Africa, Tanzania, and Bangladesh—and three industries—food processing, textiles, and the garments and leather products—this article examines the importance of various sources of knowledge for explaining productivity and formally tests whether sector- or country-specific characteristics dominate these relationships. Knowledge sources driving productivity appear mainly sector specific. Also differences in the level of development affect the effectiveness of knowledge sources. In the food processing sector, firms with higher educated managers are more productive, and in least-developed countries, additionally those with technology licenses and imported machinery and equipment. In the capital-intensive textiles sector, productivity is higher in firms that conduct R&D. In the garments and leather products sector, higher education of the managers, licensing, and R&D raise productivity.
The Kremer-Grest (KG) bead-spring model is a near standard in Molecular Dynamic simulations of generic polymer properties. It owes its popularity to its computational efficiency, rather than its ability to represent specific polymer species and conditions. Here we investigate how to adapt the model to match the universal properties of a wide range of chemical polymers species. For this purpose we vary a single parameter originally introduced by Faller and Müller-Plathe, the chain stiffness. Examples include polystyrene, polyethylene, polypropylene, cis-polyisoprene, polydimethylsiloxane, polyethyleneoxide and styrene-butadiene rubber. We do this by matching the number of Kuhn segments per chain and the number of Kuhn segments per cubic Kuhn volume for the polymer species and for the Kremer-Grest model. We also derive mapping relations for converting KG model units back to physical units, in particular we obtain the entanglement time for the KG model as function of stiffness allowing for a time mapping. To test these relations, we generate large equilibrated well entangled polymer melts, and measure the entanglement moduli using a static primitive-path analysis of the entangled melt structure as well as by simulations of step-strain deformation of the model melts. The obtained moduli for our model polymer melts are in good agreement with the experimentally expected moduli.
The Kremer–Grest (KG) polymer model is a standard model for studying generic polymer properties in molecular dynamics simulations. It owes its popularity to its simplicity and computational efficiency, rather than its ability to represent specific polymers species and conditions. Here we show that by tuning the chain stiffness it is possible to adapt the KG model to model melts of real polymers. In particular, we provide mapping relations from KG to SI units for a wide range of commodity polymers. The connection between the experimental and the KG melts is made at the Kuhn scale, i.e., at the crossover from the chemistry-specific small scale to the universal large scale behavior. We expect Kuhn scale-mapped KG models to faithfully represent universal properties dominated by the large scale conformational statistics and dynamics of flexible polymers. In particular, we observe very good agreement between entanglement moduli of our KG models and the experimental moduli of the target polymers.
Kyphoplasty of Osteoporotic Fractured Vertebrae: A Finite Element Analysis about Two Types of Cement
(2019)
Light-addressable potentiometric sensors (LAPS) consisting of a p-Si-SiO2 and p-Si-SiO2-Au structure, respectively, have been tested for a label-free electrical detection of DNA (deoxyribonucleic acid) hybridization. Three different strategies for immobilizing single-stranded probe DNA (ssDNA) molecules on a LAPS surface have been studied and compared: (a) immobilization of thiol-modified ssDNA on the patterned Au surface via gold-thiol bond, (b) covalent immobilization of amino-modified ssDNA onto the SiO2 surface functionalized with 3-aminopropyltriethoxysilane and (c) layer-by-layer adsorption of negatively charged ssDNA on a positively charged weak polyelectrolyte layer of poly(allylamine hydrochloride).
A multi-spot (16 spots) light-addressable potentiometric sensor (MLAPS) consisting of an Al–p-Si–SiO2 structure modified with a weak polyelectrolyte layer of PAH (poly(allylamine hydrochloride)) was applied for the label-free electrical detection of DNA (deoxyribonucleic acid) immobilization and hybridization by the intrinsic molecular charge for the first time. To achieve a preferentially flat orientation of DNA strands and thus, to reduce the distance between the DNA charge and MLAPS surface, the negatively charged probe single-stranded DNAs (ssDNA) were electrostatically adsorbed onto the positively charged PAH layer using a simple layer-by-layer (LbL) technique. In this way, more DNA charge can be positioned within the Debye length, yielding a higher sensor signal. The surface potential changes in each spot induced due to the surface modification steps (PAH adsorption, probe ssDNA immobilization, hybridization with complementary target DNA (cDNA), non-specific adsorption of mismatched ssDNA) were determined from the shifts of photocurrent–voltage curves along the voltage axis. A high sensor signal of 83 mV was registered after immobilization of probe ssDNA onto the PAH layer. The hybridization signal increases from 5 mV to 32 mV with increasing the concentration of cDNA from 0.1 nM to 5 μM. In contrast, a small signal of 5 mV was recorded in the case of non-specific adsorption of fully mismatched ssDNA (5 μM). The obtained results demonstrate the potential of the MLAPS in combination with the simple and rapid LbL immobilization technique as a promising platform for the future development of multi-spot light-addressable label-free DNA chips with direct electrical readout.
In this study, polyelectrolyte-modified field-effect-based electrolyte-insulator-semiconductor (EIS) devices have been used for the label-free electrical detection of double-stranded deoxyribonucleic acid (dsDNA)molecules. The sensor-chip functionalization with a positively charged polyelectrolyte layer provides the possibility of direct adsorptive binding of negatively charged target DNA oligonucleotides onto theSiO2-chip surface.EIS sensors can be utilized as a tool to detect surface-charge changes; the electrostatic adsorption of oligonucleotides onto the polyelectrolyte layer leads to a measureable surface-potential change. Signals of 39mV have been recorded after the incubation with the oligonucleotide solution. Besides the electrochemical experiments, the successful adsorption of dsDNA onto the polyelectrolyte layer has been verified via fluorescence microscopy. The presented results demonstrate that the signal recording of EISchips, which are modified with a polyelectrolyte layer, canbe used as a favorable approach for a fast, cheap and simple detection method for dsDNA.
Field-effect EIS (electrolyte-insulator-semiconductor) sensors modified with a positively charged weak polyelectrolyte layer have been applied for the electrical detection of DNA (deoxyribonucleic acid) immobilization and hybridization by the intrinsic molecular charge. The EIS sensors are able to detect the existence of target DNA amplicons in PCR (polymerase chain reaction) samples and thus, can be used as tool for a quick verification of DNA amplification and the successful PCR process. Due to their miniaturized setup, compatibility with advanced micro- and nanotechnologies, and ability to detect biomolecules by their intrinsic molecular charge, those sensors can serve as possible platform for the development of label-free DNA chips. Possible application fields as well as challenges and limitations will be discussed.
Label-free electrical detection of consecutive deoxyribonucleic acid (DNA) hybridization/denaturation by means of an array of individually addressable field-effect-based nanoplate silicon-on-insulator (SOI) capacitors modified with gold nanoparticles (Au-NP) is investigated. The proposed device detects charge changes on Au-NP/DNA hybrids induced by the hybridization or denaturation event. DNA hybridization was performed in a high ionic-strength solution to provide a high hybridization efficiency. On the other hand, to reduce the screening of the DNA charge by counter ions and to achieve a high sensitivity, the sensor signal induced by the hybridization and denaturation events was measured in a low ionic-strength solution. High sensor signals of about 120, 90, and 80 mV were registered after the DNA hybridization, denaturation, and re-hybridization events, respectively. Fluorescence microscopy has been applied as reference method to verify the DNA immobilization, hybridization, and denaturation processes. An electrostatic charge-plane model for potential changes at the gate surface of a nanoplate field-effect sensor induced by the DNA hybridization has been developed taking into account both the Debye length and the distance of the DNA charge from the gate surface.
A multi-spot (4 × 4 spots) light-addressable potentiometric sensor (MLAPS) consisting of an Al–p-Si–SiO2 structure has been applied for the label-free electrical detection of DNA (deoxyribonucleic acid) immobilization and hybridization by the intrinsic molecular charge for the first time. Single-stranded probe ssDNA molecules (20 bases) were covalently immobilized onto the silanized SiO2 gate surface. The unspecific adsorption of mismatch ssDNA on the MLAPS gate surface was blocked by bovine serum albumin molecules. To reduce the screening effect and to achieve a high sensor signal, the measurements were performed in a low ionic-strength solution. The photocurrent–voltage (I–V) curves were simultaneously recorded on all 16 spots after each surface functionalization step. Large shifts of I–V curves of 25 mV were registered after the DNA immobilization and hybridization event. In contrast, a small potential shift (∼5 mV) was observed in case of mismatch ssDNA, revealing good specificity of the sensor. The obtained results demonstrate the potential of the MLAPS as promising transducer platform for the multi-spot label-free electrical detection of DNA molecules by their intrinsic molecular charge.
Label-free Electrostatic Detection of DNA Amplification by PCR Using Capacitive Field-effect Devices
(2016)
A capacitive field-effect EIS (electrolyte-insulator-semiconductor) sensor modified with a positively charged weak polyelectrolyte of poly(allylamine hydrochloride) (PAH)/single-stranded probe DNA (ssDNA) bilayer has been used for a label-free electrostatic detection of pathogen-specific DNA amplification via polymerase chain reaction (PCR). The sensor is able to distinguish between positive and negative PCR solutions, to detect the existence of target DNA amplicons in PCR samples and thus, can be used as tool for a quick verification of DNA amplification and the successful PCR process.
Label-free sensing of biomolecules by their intrinsic molecular charge using field-effect devices
(2015)
Among the variety of transducer concepts proposed for label-free detection of biomolecules, the semiconductor field-effect device (FED) is one of the most attractive platforms. As medical techniques continue to progress towards diagnostic and therapies based on biomarkers, the ability of FEDs for a label-free, fast and real-time detection of multiple pathogenic and physiologically relevant molecules with high specificity and sensitivity offers very promising prospects for their application in point-of-care and personalized medicine for an early diagnosis and treatment of diseases. The presented paper reviews recent advances and current trends in research and development of different FEDs for label-free, direct electrical detection of charged biomolecules by their intrinsic molecular charge. The authors are mainly focusing on the detection of the DNA hybridization event, antibody-antigen affinity reaction as well as clinically relevant biomolecules such as cardiac and cancer biomarkers.
Hydraulic modeling is the classical approach to investigate and describe complex fluid motion. Many empirical formulas in the literature used for the hydraulic design of river training measures and structures have been developed using experimental data from the laboratory. Although computer capacities have increased to a high level which allows to run complex numerical simulations on standard workstation nowadays, non-standard design of structures may still raise the need to perform physical model investigations. These investigations deliver insight into details of flow patterns and the effect of varying boundary conditions. Data from hydraulic model tests may be used for calibration of numerical models as well. As the field of hydraulic modeling is very complex, this chapter intends to give a short overview on capacities and limits of hydraulic modeling in regard to river flows and hydraulic structures only. The reader shall get a first idea of modeling principles and basic considerations. More detailed information can be found in the references.
In IEC 61312-2 equations for the assessment of the magnetic fields inside structures due to a direct lightning strike are given. These equations are based on computer simulations for shields consisting of a single-layer steel grid of a given mesh width. Real constructions, however, contain at least two layers of reinforcement steel grids. The objective of this study was to experimentally determine the additional shielding effectiveness of a second reinforcement layer compared to a single-layer grid. To this end, simulated structures were set up in the high current laboratory. The structures consisted of cubic cages of 2 m side length with one or with two reinforcement grids, respectively. The structures were exposed to direct lightning currents representing the variety of anticipated lightning current waveforms. The magnetic fields and their derivatives at several positions inside the structure as well as the voltage between “floor” and “roof” in the center were determined for different current injection points. From these data the improvement of the shielding caused by a second reinforcement layer is derived.