Beurteilung der Eignung der NPEMFE-Methode (Natural Pulsed Electromagnetic Field of Earth) mit dem "Cereskop" in Rutschungen und in Locker- und Festgesteinen mit Spannungsänderungen im Mittel- und Hochgebirge

Spannungsumlagerungen in Mineralen und Gesteinen induzieren in geologisch aktiven Bereichen mikromechanische und seismische Prozesse, wodurch eine schwache natürliche elektromagnetische Strahlung im Niederfrequenzbereich emittiert wird. Die elektromagnetischen Emissionen von nichtleitenden Mineralen sind auf dielektrische Polarisation durch mehrere physikalische Effekte zurückzuführen. Eine gerichtete mechanische Spannung führt zu einer ebenso gerichteten elektromagnetischen Emission. Die Quellen der elektromagnetischen Emissionen sind bekannt, jedoch können sie noch nicht eindeutig den verschiedenen Prozessen in der Natur zugeordnet werden, weshalb im Folgenden von einem seismo-elektromagnetischen Phänomen (SEM) gesprochen wird. Mit der neuentwickelten NPEMFE-Methode (Natural Pulsed Electromagnetic Field of Earth) können die elektromagnetischen Impulse ohne Bodenkontakt registriert werden. Bereiche der Erdkruste mit Spannungsumlagerungen (z.B. tektonisch aktive Störungen, potenzielle Hangrutschungen, Erdfälle, Bergsenkungen, Firstschläge) können als Anomalie erkannt und abgegrenzt werden. Basierend auf dem heutigen Kenntnisstand dieser Prozesse wurden Hangrutschungen und Locker- und Festgesteine, in denen Spannungsumlagerungen stattfinden, mit einem neuentwickelten Messgerät, dem "Cereskop", im Mittelgebirgsraum (Rheinland-Pfalz, Deutschland) und im alpinen Raum (Vorarlberg, Österreich, und Fürstentum Liechtenstein) erkundet und die gewonnenen Messergebnisse mit klassischen Verfahren aus Ingenieurgeologie, Geotechnik und Geophysik in Bezug gesetzt. Unter Feldbedingungen zeigte sich großenteils eine gute Übereinstimmung zwischen den mit dem "Cereskop" erkundeten Anomalien und den mit den konventionellen Verfahren erkundeten Spannungszonen. Auf Grundlage der bisherigen Kenntnis und unter Einbeziehung von Mehrdeutigkeiten werden die Messergebnisse analysiert und kritisch beurteilt.

Elektromagnetische Pionproduktion in manifest Lorentz-invarianter baryonischer chiraler Störungstheorie

In dieser Arbeit wurde die elektromagnetische Pionproduktion unter der Annahme der Isospinsymmetrie der starken Wechselwirkung im Rahmen der manifest Lorentz-invarianten chiralen Störungstheorie in einer Einschleifenrechnung bis zur Ordnung vier untersucht. Dazu wurden auf der Grundlage des Mathematica-Pakets FeynCalc Algorithmen zur Berechnung der Pionproduktionsamplitude entwickelt. Bis einschließlich der Ordnung vier tragen insgesamt 105 Feynmandiagramme bei, die sich in 20 Baumdiagramme und 85 Schleifendiagramme unterteilen lassen. Von den 20 Baumdiagrammen wiederum sind 16 als Polterme und vier als Kontaktgraphen zu klassifizieren; bei den Schleifendiagrammen tragen 50 Diagramme ab der dritten Ordnung und 35 Diagramme ab der vierten Ordnung bei. In der Einphotonaustauschnäherung lässt sich die Pionproduktionsamplitude als ein Produkt des Polarisationsvektors des (virtuellen) Photons und des Übergangsstrommatrixelements parametrisieren, wobei letzteres alle Abhängigkeiten der starken Wechselwirkung beinhaltet und wo somit die chirale Störungstheorie ihren Eingang findet. Der Polarisationsvektor hingegen hängt von dem leptonischen Vertex und dem Photonpropagator ab und ist aus der QED bekannt. Weiterhin lässt sich das Übergangsstrommatrixelement in sechs eichinvariante Amplituden zerlegen, die sich im Rahmen der Isospinsymmetrie jeweils wiederum in drei Isospinamplituden zerlegen lassen. Linearkombinationen dieser Isospinamplituden erlauben letztlich die Beschreibung der physikalischen Amplituden. Die in dieser Rechnung auftretenden Einschleifenintegrale wurden numerisch mittels des Programms LoopTools berechnet. Im Fall tensorieller Integrale erfolgte zunächst eine Zerlegung gemäß der Methode von Passarino und Veltman. Da die somit erhaltenen Ergebnisse jedoch i.a. noch nicht das chirale Zählschema erfüllen, wurde die entsprechende Renormierung mittels der reformulierten Infrarotregularisierung vorgenommen. Zu diesem Zweck wurde ein Verfahren entwickelt, welches die Abzugsterme automatisiert bestimmt. Die schließlich erhaltenen Isospinamplituden wurden in das Programm MAID eingebaut. In diesem Programm wurden als Test (Ergebnisse bis Ordnung drei) die s-Wellenmultipole E_{0+} und L_{0+} in der Schwellenregion berechnet. Die Ergebnisse wurden sowohl mit Messdaten als auch mit den Resultaten des "klassischen" MAID verglichen, wobei sich i. a. gute Übereinstimmungen im Rahmen der Fehler ergaben.

Thermal Treatments of Fe—Mn Alkoxide of Glycerol: Infrared absorption and emission

Synthetic Fe—Mn alkoxide of glycerol samples are submitted to controlled heating conditions and examined by IR absorption spectroscopy. On the other hand, the same sample is studied by infrared emission spectroscopy (IRES), upon heating in situ from 100 to 600°C. The spectral techniques employed in this contribution, especially IRES, show that as a result of the thermal treatments ferromagnetic oxides (manganese ferrite) are formed between 350 and 400°C. Some further spectral changes are seen at higher temperatures.

Thermal treatment of weddellite—a Raman and infrared emission spectroscopic study

Thermal transformations of natural calcium oxalate dihydrate known in mineralogy as weddellite have been undertaken using a combination of Raman microscopy and infrared emission spectroscopy. The vibrational spectroscopic data was complimented with high resolution thermogravimetric analysis combined with evolved gas mass spectrometry. TG–MS identified three mass loss steps at 114, 422 and 592 °C. In the first mass loss step water is evolved only, in the second and third steps carbon dioxide is evolved. The combination of Raman microscopy and a thermal stage clearly identifies the changes in the molecular structure with thermal treatment. Weddellite is the phase in the temperature range up to the pre-dehydration temperature of 97 °C. At this temperature, the phase formed is whewellite (calcium oxalate monohydrate) and above 114 °C the phase is the anhydrous calcium oxalate. Above 422 °C, calcium carbonate is formed. Infrared emission spectroscopy shows that this mineral decomposes at around 650 °C. Changes in the position and intensity of the C=O and C---C stretching vibrations in the Raman spectra indicate the temperature range at which these phase changes occur.

Quantification of motor vehicle emission factors from on road measurements

Assessment and prediction of the impact of vehicular traffic emissions on air quality and exposure levels requires knowledge of vehicle emission factors. The aim of this study was quantification of emission factors from an on road, over twelve months measurement program conducted at two sites in Brisbane: 1) freeway type (free flowing traffic at about 100 km/h, fleet dominated by small passenger cars - Tora St); and 2) urban busy road with stop/start traffic mode, fleet comprising a significant fraction of heavy duty vehicles - Ipswich Rd. A physical model linking concentrations measured at the road for specific meteorological conditions with motor vehicle emission factors was applied for data analyses. The focus of the study was on submicrometer particles; however the measurements also included supermicrometer particles, PM2.5, carbon monoxide, sulfur dioxide, oxides of nitrogen. The results of the study are summarised in this paper. In particular, the emission factors for submicrometer particles were 6.08 x 1013 and 5.15 x 1013 particles per vehicle-1 km-1 for Tora St and Ipswich Rd respectively and for supermicrometer particles for Tora St, 1.48 x 109 particles per vehicle-1 km-1. Emission factors of diesel vehicles at both sites were about an order of magnitude higher than emissions from gasoline powered vehicles. For submicrometer particles and gasoline vehicles the emission factors were 6.08 x 1013 and 4.34 x 1013 particles per vehicle-1 km-1 for Tora St and Ipswich Rd, respectively, and for diesel vehicles were 5.35 x 1014 and 2.03 x 1014 particles per vehicle-1 km-1 for Tora St and Ipswich Rd, respectively. For supermicrometer particles at Tora St the emission factors were 2.59 x 109 and 1.53 x 1012 particles per vehicle-1 km-1, for gasoline and diesel vehicles, respectively.

Particle number and mass emission factors from combustion of wood samples collected from Queensland forest

Knowledge of particle emission characteristics associated with forest fires and in general, biomass burning, is becoming increasingly important due to the impact of these emissions on human health. Of particular importance is developing a better understanding of the size distribution of particles generated from forest combustion under different environmental conditions, as well as provision of emission factors for different particle size ranges. This study was aimed at quantifying particle emission factors from four types of wood found in South East Queensland forests: Spotted Gum (Corymbia citriodora), Red Gum (Eucalypt tereticornis), Blood Gum (Eucalypt intermedia), and Iron bark (Eucalypt decorticans); under controlled laboratory conditions. The experimental set up included a modified commercial stove connected to a dilution system designed for the conditions of the study. Measurements of particle number size distribution and concentration resulting from the burning of woods with a relatively homogenous moisture content (in the range of 15 to 26 %) and for different rates of burning were performed using a TSI Scanning Mobility Particle Sizer (SMPS) in the size range from 10 to 600 nm and a TSI Dust Trak for PM2.5. The results of the study in terms of the relationship between particle number size distribution and different condition of burning for different species show that particle number emission factors and PM2.5 mass emission factors depend on the type of wood and the burning rate; fast burning or slow burning. The average particle number emission factors for fast burning conditions are in the range of 3.3 x 1015 to 5.7 x 1015 particles/kg, and for PM2.5 are in the range of 139 to 217 mg/kg.

Comparison of ultrafine particle release from hardcopy devices in emission test chambers and office rooms

The release of ultrafine particles (UFP) from laser printers and office equipment was analyzed using a particle counter (FMPS; Fast Mobility Particle Sizer) with a high time resolution, as well as the appropriate mathematical models. Measurements were carried out in a 1 m³ chamber, a 24 m³ chamber and an office. The time-dependent emission rates were calculated for these environments using a deconvolution model, after which the total amount of emitted particles was calculated. The total amounts of released particles were found to be independent of the environmental parameters and therefore, in principle, they were appropriate for the comparison of different printers. On the basis of the time-dependent emission rates, “initial burst” emitters and constant emitters could also be distinguished. In the case of an “initial burst” emitter, the comparison to other devices is generally affected by strong variations between individual measurements. When conducting exposure assessments for UFP in an office, the spatial distribution of the particles also had to be considered. In this work, the spatial distribution was predicted on a case by case basis, using CFD simulation.

Comparison of emission rate values for odour and odorous chemicals derived from two sampling devices

Field and laboratory measurements identified a complex relationship between odour emission rates provided by the US EPA dynamic emission chamber and the University of New South Wales wind tunnel. Using a range of model compounds in an aqueous odour source, we demonstrate that emission rates derived from the wind tunnel and flux chamber are a function of the solubility of the materials being emitted, the concentrations of the materials within the liquid; and the aerodynamic conditions within the device – either velocity in the wind tunnel, or flushing rate for the flux chamber. The ratio of wind tunnel to flux chamber odour emission rates (OU m-2 s) ranged from about 60:1 to 112:1. The emission rates of the model odorants varied from about 40:1 to over 600:1. These results may provide, for the first time, a basis for the development of a model allowing an odour emission rate derived from either device to be used for odour dispersion modelling.

Infrared and infrared emission spectroscopy of gallium oxide α-GaO(OH) nanostructures

Infrared spectroscopy has been used to study nano to micro sized gallium oxyhydroxide α-GaO(OH), prepared using a low temperature hydrothermal route. Rod-like α-GaO(OH) crystals with average length of ~2.5 μm and width of 1.5 μm were prepared when the initial molar ratio of Ga to OH was 1:3. β-Ga2O3 nano and micro-rods were prepared through the calcination of α-GaO(OH) The initial morphology of α-GaO(OH) is retained in the β-Ga2O3 nanorods. The combination of infrared and infrared emission spectroscopy complimented with dynamic thermal analysis were used to characterise the α-GaO(OH) nanotubes and the formation of β-Ga2O3 nanorods. Bands at around 2903 and 2836 cm-1 are assigned to the -OH stretching vibration of α-GaO(OH) nanorods. Infrared bands at around 952 and 1026 cm-1 are assigned to the Ga-OH deformation modes of α-GaO(OH). A significant number of bands are observed in the 620 to 725 cm-1 region and are assigned to GaO stretching vibrations.

Source location of acoustic emission waves for structural health monitoring of bridges

The process of structural health monitoring (SHM) involves monitoring a structure over a period of time using appropriate sensors, extracting damage sensitive features from the measurements made by the sensors and analysing these features to determine the current state of the structure. Various techniques are available for structural health monitoring of structures and acoustic emission (AE) is one technique that is finding an increasing use. Acoustic emission waves are the stress waves generated by the mechanical deformation of materials. AE waves produced inside a structure can be recorded by means of sensors attached on the surface. Analysis of these recorded signals can locate and assess the extent of damage. This paper describes preliminary studies on the application of AE technique for health monitoring of bridge structures. Crack initiation or structural damage will result in wave propagation in solid and this can take place in various forms. Propagation of these waves is likely to be affected by the dimensions, surface properties and shape of the specimen. This, in turn, will affect source localization. Various laboratory test results will be presented on source localization, using pencil lead break tests. The results from the tests can be expected to aid in enhancement of knowledge of acoustic emission process and development of effective bridge structure diagnostics system.

Structural health monitoring of bridges using acoustic emission technology and signal processing techniques

Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.

Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC—a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices—thus, supporting the PCA approach.