Biogeochemical measurements of sediments collected at station MSM15/1_492-PUC9 (microbial mat 3) in the Black Sea during the MSM15/1 cruise in 2010

Biogeochemical measurements in sediment cores collected with the submersible JAGO (pusch cores) and a TV-MUC in the Black Sea during MSM15/1, Northwest Crimea (HYPOX Project), at water depths between 152-156 m. A series of microbial mats were sampled on the hypoxic region of the Crimean Shelf. Concentrations of organic carbon (Corg) and nitrogen (N) were measured on finely powdered, freeze-dried subsamples of sediment using a using a Fisons NA-1500 elemental analyzer. For organic carbon determination samples were pre-treated with 12.5% HCl to remove carbonates. Chlorophyll a (chl a), phaeopigments (PHAEO) and chloroplastic pigment equivalents (CPE) was measured according to Schubert et al., (2005) and total hydrolyzable amino acids (THAA) and single amino acid: ASP, GLU, SER, HIS, GLY, THR, ARG, ALA, TYR, MET, VAL, PHE, ILE, LEU, LYS following Dauwe et al., 1998.

Biogeochemical investigation of microbial mats from the hypoxic region of the Crimean Shelf (Black Sea)

Biogeochemical measurements in sediment cores collected with the submersible JAGO (pusch cores) and a TV-MUC in the Black Sea during MSM15/1, Northwest Crimea (HYPOX Project), at water depths between 152-156 m. A series of microbial mats were sampled on the hypoxic region of the Crimean Shelf. Concentrations of organic carbon (Corg) and nitrogen (N) were measured on finely powdered, freeze-dried subsamples of sediment using a using a Fisons NA-1500 elemental analyzer. For organic carbon determination samples were pre-treated with 12.5% HCl to remove carbonates. Chlorophyll a (chl a), phaeopigments (PHAEO) and chloroplastic pigment equivalents (CPE) was measured according to Schubert et al., (2005) and total hydrolyzable amino acids (THAA) and single amino acid: ASP, GLU, SER, HIS, GLY, THR, ARG, ALA, TYR, MET, VAL, PHE, ILE, LEU, LYS following Dauwe et al., 1998. High-resolution ex situ sulfide and pH microprofiles, were assessed only for station MSM15/1_492_PUC1. "in mat 1, 2 and 3" refers to 3 different profiles in 3 different spots of the microbial mat, whereas "outside mat", a profile outside the microbial mat.

Biogeochemical measurements of sediments collected at station MSM15/1_492-PUC1 (microbial mat 1) in the Black Sea during the MSM15/1 cruise in 2010

Biogeochemical measurements in sediment cores collected with the submersible JAGO (pusch cores) and a TV-MUC in the Black Sea during MSM15/1, Northwest Crimea (HYPOX Project), at water depths between 152-156 m. A series of microbial mats were sampled on the hypoxic region of the Crimean Shelf. Concentrations of organic carbon (Corg) and nitrogen (N) were measured on finely powdered, freeze-dried subsamples of sediment using a using a Fisons NA-1500 elemental analyzer. For organic carbon determination samples were pre-treated with 12.5% HCl to remove carbonates. Chlorophyll a (chl a), phaeopigments (PHAEO) and chloroplastic pigment equivalents (CPE) was measured according to Schubert et al., (2005) and total hydrolyzable amino acids (THAA) and single amino acid: ASP, GLU, SER, HIS, GLY, THR, ARG, ALA, TYR, MET, VAL, PHE, ILE, LEU, LYS following Dauwe et al., 1998.

Biogeochemical measurements of sediments collected at station MSM15/1_492-PUC6 (reference site 3) in the Black Sea during the MSM15/1 cruise in 2010

Biogeochemical measurements in sediment cores collected with the submersible JAGO (pusch cores) and a TV-MUC in the Black Sea during MSM15/1, Northwest Crimea (HYPOX Project), at water depths between 152-156 m. A series of microbial mats were sampled on the hypoxic region of the Crimean Shelf. Concentrations of organic carbon (Corg) and nitrogen (N) were measured on finely powdered, freeze-dried subsamples of sediment using a using a Fisons NA-1500 elemental analyzer. For organic carbon determination samples were pre-treated with 12.5% HCl to remove carbonates. Chlorophyll a (chl a), phaeopigments (PHAEO) and chloroplastic pigment equivalents (CPE) was measured according to Schubert et al., (2005) and total hydrolyzable amino acids (THAA) and single amino acid: ASP, GLU, SER, HIS, GLY, THR, ARG, ALA, TYR, MET, VAL, PHE, ILE, LEU, LYS following Dauwe et al., 1998.

Dissolved organic carbon concentrations, amino sugar concentrations and highly significantly correlating FT-ICR mass peak magnitudes obtained from solid phase extracted marine dissolved organic matter during POLARSTERN cruise ANT-XXV/1

Dissolved organic matter (DOM) was extracted with solid phase extraction (SPE) from 137 water samples from different climate zones and different depths along an Eastern Atlantic Ocean transect. The extracts were analyzed with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) with electrospray ionization (ESI). D14C analyses were performed on subsamples of the SPE-DOM. In addition, the amount of dissolved organic carbon was determined for all water and SPE-DOM samples as well as the yield of amino sugars for selected samples. Linear correlations were observed between the magnitudes of 43% of the FT-ICR mass peaks and the extract D14C values. Decreasing SPE-DOM D14C values went along with a shift in the molecular composition to higher average masses (m/z) and lower hydrogen/carbon (H/C) ratios. The correlation was used to model the SPE-DOM D14C distribution for all 137 samples. Based on single mass peaks a degradation index was developed to compare the degradation state of marine SPE-DOM samples analyzed with FT-ICR MS. A correlation between D14C, degradation index, DOC values and amino sugar yield supports that SPE-DOM analyzed with FT-ICR MS reflects trends of bulk DOM. A relative mass peak magnitude ratio was used to compare aged SPE-DOM and fresh SPE-DOM regarding single mass peaks. The magnitude ratios show a continuum of different reactivities for the single compounds. Only few of the compounds present in the FT-ICR mass spectra are expected to be highly degraded in the oldest water masses of the Pacific Ocean. All other compounds should persist partly thermohaline circulation. Prokaryotic (bacterial) production, transformation and accumulation of this very stable DOM occurs probably primarily in the upper ocean. This DOM is an important contribution to very old DOM, showing that production and degradation are dynamic processes.

d13C and d15N stable isotopes values, total nitrogen and C/N ratios of sediment core GeoB4801-1

Rising stable nitrogen isotope ratios (d15N) in dated sediment records of the German Bight/SE North Sea track river-induced coastal eutrophication over the last 2 centuries. Fully exploiting their potential for reconstructions of pristine conditions and quantitative analysis of historical changes in the nitrogen cycle from these sediment records requires knowledge on processes that alter the isotopic signal in non-living organic matter (OM) of sinking particles and sediments. In this study, we analyze the isotopic composition of particulate nitrogen (PN) in the water column during different seasons, in surface sediments, and in sediment cores to assess diagenetic influences on the isotopic composition of OM. Amino acid (AA) compositions of suspended matter, surface sediments, and dated cores at selected sites of the German Bight serve as indicators for quality and degradation state of PN. The d15N of PN in suspended matter had seasonal variances caused by two main nitrate sources (oceanic and river) and different stages of nitrate availability during phytoplankton assimilation. Elevated d15N values (> 20 per mil) in suspended matter near river mouths and the coast coincide with a coastal water mass receiving nitrate with elevated isotope signal (d15N > 10 per mil) derived from anthropogenic input. Particulate nitrogen at offshore sites fed by oceanic nitrate having a d15N between 5 and 6 per mil had low d15N values (< 2 per mil), indicative of an incipient phytoplankton bloom. Surface sediments along an offshore-onshore transect also reflect the gradient of low d15N of nitrate in offshore sites to high values near river mouths, but the range of values is smaller than between the end members listed above and integrates the annual d15N of detritus. Sediment cores from the coastal sector of the gradient show an increasing d15N trend (increase of 2.5 per mil) over the last 150 years. This is not related to any change in AA composition and thus reflects eutrophication. The d15N signals from before AD 1860 represent a good estimation of pre-industrial isotopic compositions with minimal diagenetic overprinting. Rising d13C in step with rising d15N in these cores is best explained by increasing productivity caused by eutrophication.

Bearing fault prognosis based on health state probability estimation

In condition-based maintenance (CBM), effective diagnostic and prognostic tools are essential for maintenance engineers to identify imminent fault and predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedule of production if necessary. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of bearings based on health state probability estimation and historical knowledge embedded in the closed loop diagnostics and prognostics system. The technique uses the Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation process to provide long term prediction. To validate the feasibility of the proposed model, real life fault historical data from bearings of High Pressure-Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life (RUL). The results obtained were very encouraging and showed that the proposed prognosis system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

State-of-the-art : track degradation at bridge transitions

Transition zones between bridge decks and rail tracks suffer early failure due to poor interaction between rail vehicles and sudden changes of stiffness. This has been an ongoing problem to rail industry and yet still no systematic studies appear to have been taken to maintain a gradually smoothening transmission of forces between the bridge and its approach. Differential settlement between the bridge deck and rail track in the transition zone is the fundamental issue, which negatively impacts the rail industry by causing passenger discomfort, early damage to infrastructure and vehicle components, speed reduction, and frequent maintenance cycles. Identification of mechanism of the track degradation and factors affecting is imperative to design any mitigation method for reducing track degradation rate at the bridge transition zone. Unfortunately this issue is still not well understood, after conducting a numbers of reviews to evaluate the key causes, and introducing a wide range of mitigation techniques. In this study, a comprehensive analysis of the available literature has been carried out to develop either a novel design framework or a mitigation technique for the bridge transition zone. This paper addresses three critical questions in relation to the track degradation at transition zone: (1) what are the causes of bridge transition track degradation?; (2) what are the available mitigation techniques in reducing the track degradation rate?; (3) what are the factors affecting on poor performance of the existing mitigation techniques?. It is found that the absence of soil-water response, dynamic loading response, and behaviour of geotechnical characteristics under long-term conditions in existing track transition design frameworks critically influence on the failures of existing mitigation techniques. This paper also evaluates some of the existing design frameworks to identify how each design framework addresses the track degradation at the bridge transition zone.