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In civil engineering the information about the quantitative ingress of harmful species like Cl⁻, Na⁺ and SO²⁻₄ is of great interest to evaluate the remaining life time of structures. These species are triggering different damage processes like the alkali-silica reaction (ASR) or the chloride-induced corrosion of the reinforcement. For the evaluation of the heterogeneous concrete it is necessary to discriminate between the different phases mainly cement matrix and aggregates. The transport processes are only proceeding in the cement matrix therefore the measured concentrations should be regarded to the cement content. For the 2D evaluation of element distributions different multivariate cluster-algorithms like k-means and Expectation-Maximization-algorithm (EM-algorithm) have been tested. The methods are compared and different figures of merit will be presented. After phase separation non-relevant information of the aggregates can be excluded. The ingress of harmful species is then quantified using chemometrics. Due to concrete cores from a parking deck the methods have been validated and verified with standard methods of wet-chemistry.
Concrete is often used in combination with steel as reinforced concrete. Environmental influences, especially the ingress of harmful ions in combination with the ingress of water, trigger different damage processes which reduce the designed lifetime of a structure. The ingress of chlorides from de-icing salt or sea water leads to corrosion of the reinforcement. Also the carbonation of the concrete may trigger the corrosion of the reinforcement. The ingress of alkalis from de-icing salts may cause the expansion of the amorphous silica aggregates (alkali-silica reaction) through formation of a swelling gel of calcium silicate hydrate if water is present. The ingress of sulfates may cause spalling of the concrete surface due to ettringite formation.
BAM has developed the LIBS technique for automated laboratory use with high numbers of samples to investigate transport processes of harmful species (Cl-, CO2, SO42- and alkalis) in concrete. Information about ingress depth and the quantitative values are important to estimate the remaining lifetime of the infrastructure. To get information about the ingress depth, a core has to be taken and cut in the middle. The measurements are carried out at the cross section. The main advantages of LIBS are the direct measurement on the surface of the concrete, fast analysis (sample rate 100 Hz) with a spatial resolution of up to 100 µm, the consideration of the heterogeneity of the concrete. The possibility of automated measurements saves a lot of manpower and time. At the same time a 2D-evaluation provides information about hot spots of elemental concentration which may not be found by standard methods.
Typical results of 2D investigation of concrete in laboratory will be presented. The performance is also demonstrated by examples for onsite applications using a mobile LIBS system. The road map to standardization is presented as well.
Phenotypic heterogeneity in disinfection: sources and consequences for antimicrobial resistance
(2022)
A summary of projects here at BAM which investigate the influence of phenotypic heterogeneity on the outcome of disinfection and the influence on antimicrobial resistance. This presentation was given in the Theory Seminar of the Quantitative and Theoretical Biology group of Prof. Oliver Ebenhöh at HHU Düsseldorf
Numerical simulators, such as finite element models, have become increasingly capable of predicting the behaviour of structures and components owing to more sophisticated underlying mathematical models and advanced computing power. A common challenge lies, however, in calibrating these models in terms of their unknown/uncertain parameters. When measurements exist, this can be achieved by comparing the model response against measured data. Besides uncertain model parameters, phenomena like damage can give rise to further uncertainties; in particular, quasi-brittle materials, like concrete, experience damage in a heterogeneous manner due to various imperfections, e.g. in geometry and boundary conditions. This hardens an accurate prediction of the damaged behaviour of real structures that comprise such materials.
In this study, which draws from a data-driven approach, we use the force-version of the finite element model updating method (FEMU-F) to incorporate measured displacements into the identification of the damage parameters, in order to cope with heterogeneity. In this method, instead of conducting a forward evaluation of the model and comparing the model response (displacements) against the data, we impose displacements to the model and compare the resulting force residuals with measured reaction forces. To account for uncertainties in the measurement of displacements, we endow this approach with a penalty term, which reflects the discrepancy between measured and imposed displacements, where the latter is assumed as unknown random variables to be identified as well. A Variational Bayesian approach is used as an approximating tool for computing posterior parameters. The underlying damage model considered in this work is a gradient-enhanced damage model.
We first establish the identification procedure through two virtual examples, where synthetic data (displacements) are generated over a certain spatially-dense set of points over the domain. The procedure is then validated on an experimental case-study; namely a 3-point bending experiment with displacement measurements resulting from a digital image correlation (DIC) analysis.
Glutaraldehyde is widely used as a disinfectant and preservative, but little is known about its effects on bacterial susceptibility to antibiotics and the selection of tolerant phenotypes. We found that short-term exposure to sub-inhibitory levels of glutaraldehyde makes E. coli resistant to high doses of bactericidal antibiotics from different classes. This tolerance is associated with delayed, heterogeneous regrowth dynamics and global transcriptome remodeling. We identified over 1200 differentially expressed genes, including those related to antibiotic efflux, metabolic processes, and the cell envelope. The cells entered a disrupted state likely due to the unspecific mode-of-action of glutaraldehyde. Despite this unregulated response, we identified several differentially expressed genes not previously associated with antibiotic tolerance or persistence that induce antibiotic tolerance when overexpressed alone. These findings highlight how the unspecific mode-of-action of disinfectants can make bacteria temporarily resistant to antibiotics. They have implications for settings where disinfectants and antibiotics are used in close proximity, such as hospitals and animal husbandry, and for the selection dynamics of tolerant pheno- and genotypes in fluctuating environments where microorganisms are exposed to these substances, such as sewage systems. A trade-off arises from overcoming the disrupted state as quickly as possible and maintaining antibiotic tolerance.
Glutaraldehyde is widely used as a disinfectant and preservative, but little is known about its effects on bacterial susceptibility to antibiotics and the selection of tolerant phenotypes. We found that short-term exposure to sub-inhibitory levels of glutaraldehyde makes E. coli resistant to high doses of bactericidal antibiotics from different classes. This tolerance is associated with delayed, heterogeneous regrowth dynamics and global transcriptome remodeling. We identified over 1200 differentially expressed genes, including those related to antibiotic efflux, metabolic processes, and the cell envelope. The cells entered a disrupted state likely due to the unspecific mode-of-action of glutaraldehyde. Despite this unregulated response, we identified several differentially expressed genes not previously associated with antibiotic tolerance or persistence that induce antibiotic tolerance when overexpressed alone. These findings highlight how the unspecific mode-of-action of disinfectants can make bacteria temporarily resistant to antibiotics. They have implications for settings where disinfectants and antibiotics are used in close proximity, such as hospitals and animal husbandry, and for the selection dynamics of tolerant pheno- and genotypes in fluctuating environments where microorganisms are exposed to these substances, such as sewage systems. A trade-off arises from overcoming the disrupted state as quickly as possible and maintaining antibiotic tolerance.