Optical and Thermal Characterization of Dye Intercalated Montmorillonites and Rare Earth Doped Materials

Nondestructive photothermal methods as well as optical absorption and fluorescence spectroscopy are utilized to characterise three different materials, both thermally and optically. The possibility of using montmorillonite clay minerals, after textile waste-water treatment, is investigated for further applications. The laser induced luminescence studies and thermal characterisation of certain rare earth titanates prepared by self propagating high temperature synthesis method are also presented. Moreover, effort is made to characterise rare earth doped sol gel silica glasses with the help of these nondestructive techniques.

Towards robust night and day place recognition using visible and thermal imaging

The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Preparation, characterisation and thermal properties of hydrazinium derivatives. Part III

Hydrazinium acetate, metavanadate, sulfite, sulphamate and thiocyanate have been prepared by the reaction of corresponding ammonium salts with hydrazine hydrate. The compounds were characterised by chemical analysis and infrared spectra. Thermal behaviour of these hydrazinium derivatives have been investigated using thermogravimetry and differential thermal analysis.

Preparation, Characterisation and Thermal Properties of Hydrazinium Magnesium Sulfate

Hydrazinium magnesium sulfate, (N2H5)2Mg(SO4)2, has been prepared by dissolving magnesium powder in a solution of ammonium sulfate in hydrazine hydrate, by the reaction of ammonium magnesium sulfate with hydrazine hydrate, and by the cocrystallisation of dihydrazinium sulfate and magnesium sulfate. The product has been characterized by chemical analysis and infrared spectra. Thermal analysis of (N2H5)2Mg(SO4)2 by TG and DTA show exothermic decomposition at 302°C giving Mg(N2H4)SO4 as an intermediate and an endother-mic decomposition at 504°C producing MgSO4.

Synthesis, characterisation and thermal analysis of copper (II) and chromium (II, III) hydrazine carboxylates

Copper(II) hydrazine carboxylate monohydrate, Cu(N2H3COO)2·H2O and chromium (II, III) hydrazine carboxylate hydrates, Cu(N2H3COO)2·H2O and Cu(N2H3COO)2·3H2O have been prepared and characterised by chemical analysis, IR, visible spectra and magnetic measurements. Thermal analysis of the copper complex yields a mixture of copper metal and copper oxide. Chromium complexes on thermal decomposition yield Cr2O3 as residue. Decomposition of chromium(HI) complex under hydrothermal conditions yield CrOOH, a precursor to CrO2.

Accuracy of turbulence models and CFD for thermal characterisation of electronic systems

A major percentage of the heat emitted from electronic packages can be extracted by air cooling whether by means of natural or forced convection. This flow of air throughout an electronic system and the heat extracted is highly dependable on the nature of turbulence present in the flow field. This paper will discuss results from an investigation into the accuracy of turbulence models to predict air cooling for electronic packages and systems.

Synthesis, characterisation and thermal behaviour of solid state compounds of 4-methylbenzylidenepyruvate with some bivalent metal ions

Solid state M-4-Me-BP compounds, where M stands for bivalent Mn, Fe, Co, Ni, Cu, Zn, Pb and 4-Me-BP is 4-methylbenzylidenepyruvate, have been synthesized. Simultaneous thermogravimetry-differential thermal analysis (TG-DTA), differential scanning calorimetry (DSC), X-ray powder diffractometry, infrared spectroscopy, elemental analysis, and complexometry were used to characterise and to study the thermal behaviour of these compounds. The results led to information about the composition, dehydration, thermal stability and thermal decomposition of the isolated complexes. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Synthesis, characterisation and thermal behaviour of solid state compounds of 4-methylbenzylidenepyruvate with heavier trivalent lanthanides and yttrium(III)

Solid state Ln-4-Me-BP compounds, where Ln stands for heavier trivalent lanthanides (gadolinium to lutetium) and yttrium(III) and 4-Me-BP is 4-methylbenzylidenepyruvate (CH3-C6H4-CH=CH-COCOO-), have been synthesized. Elemental analysis, complexometry, X-ray powder diffractometry, infrared spectroscopy and simultaneous thermogravimetry-differential thermal analysis (TG-DTA), have been used to characterise and to study the thermal behaviour of these compounds. The results provided information concerning the stoichiometry, crystallinity, ligand's denticity, thermal stability and thermal decomposition. © 2002 Elsevier Science B.V. All rights reserved.

Review of industrial temperature measurement technologies and research priorities for the thermal characterisation of the factories of the future

As the largest source of dimensional measurement uncertainty, addressing the challenges of thermal variation is vital to ensure product and equipment integrity in the factories of the future. While it is possible to closely control room temperature, this is often not practical or economical to realise in all cases where inspection is required. This article reviews recent progress and trends in seven key commercially available industrial temperature measurement sensor technologies primarily in the range of 0 °C–50 °C for invasive, semi-invasive and non-invasive measurement. These sensors will ultimately be used to measure and model thermal variation in the assembly, test and integration environment. The intended applications for these technologies are presented alongside some consideration of measurement uncertainty requirements with regard to the thermal expansion of common materials. Research priorities are identified and discussed for each of the technologies as well as temperature measurement at large. Future developments are briefly discussed to provide some insight into which direction the development and application of temperature measurement technologies are likely to head.

Numerical investigation of mechanical and thermal dynamic properties of the industrial transformer

Industrial transformer is one of the most critical assets in the power and heavy industry. Failures of transformers can cause enormous losses. The poor joints of the electrical circuit on transformers can cause overheating and results in stress concentration on the structure which is the major cause of catastrophic failure. Few researches have been focused on the mechanical properties of industrial transformers under overheating thermal conditions. In this paper, both mechanical and thermal properties of industrial transformers are jointly investigated using Finite Element Analysis (FEA). Dynamic response analysis is conducted on a modified transformer FEA model, and the computational results are compared with experimental results from literature to validate this simulation model. Based on the FEA model, thermal stress is calculated under different temperature conditions. These analysis results can provide insights to the understanding of the failure of transformers due to overheating, therefore are significant to assess winding fault, especially to the manufacturing and maintenance of large transformers.

Energetic and thermal properties of tilt grain boundaries in graphene/hexagonal boron nitride heterostructures

Graphene/hexagonal boron nitride (G/h-BN) heterostructure has attracted tremendous research efforts owing to its great potential for applications in nano-scale electronic devices. In such hybrid materials, tilt grain boundaries (GBs) between graphene and h-BN grains may have unique physical properties, which have not been well understood. Here we have conducted non-equilibrium molecular dynamics simulations to study the energetic and thermal properties of tilt GBs in G/h-BN heterostructures. The effect of misorientation angles of tilt GBs on both GB energy and interfacial thermal conductance are investigated.

Water and thermal regimes for field pea in Australia and their implications for breeding.

There is a large gap between the refined approaches to characterise genotypes and the common use of location and season as a coarse surrogate for environmental characterisation of breeding trials. As a framework for breeding, the aim of this paper is quantifying the spatial and temporal patterns of thermal and water stress for field pea in Australia. We compiled a dataset for yield of the cv. Kaspa measured in 185 environments, and investigated the associations between yield and seasonal patterns of actual temperature and modelled water stress. Correlations between yield and temperature indicated two distinct stages. In the first stage, during crop establishment and canopy expansion before flowering, yield was positively associated with minimum temperature. Mean minimum temperature below similar to 7 degrees C suggests that crops were under suboptimal temperature for both canopy expansion and radiation-use efficiency during a significant part of this early growth period. In the second stage, during critical reproductive phases, grain yield was negatively associated with maximum temperature over 25 degrees C. Correlations between yield and modelled water supply/demand ratio showed a consistent pattern with three phases: no correlation at early stages of the growth cycle, a progressive increase in the association that peaked as the crop approached the flowering window, and a progressive decline at later reproductive stages. Using long-term weather records (1957-2010) and modelled water stress for 104 locations, we identified three major patterns of water deficit nation wide. Environment type 1 (ET1) represents the most favourable condition, with no stress during most of the pre-flowering phase and gradual development of mild stress after flowering. Type 2 is characterised by increasing water deficit between 400 degree-days before flowering and 200 degree-days after flowering and rainfall that relieves stress late in the season. Type 3 represents the more stressful condition with increasing water deficit between 400 degree-days before flowering and maturity. Across Australia, the frequency of occurrence was 24% for ET1, 32% for ET2 and 43% for ET3, highlighting the dominance of the most stressful condition. Actual yield averaged 2.2 t/ha for ET1, 1.9 t/ha for ET2 and 1.4 t/ha for ET3, and the frequency of each pattern varied substantially among locations. Shifting from a nominal (i.e. location and season) to a quantitative (i.e. stress type) characterisation of environments could help improving breeding efficiency of field pea in Australia.