Detection of Bridge Dynamic Parameters using an Instrumented Vehicle

Highway structures such as bridges are subject to continuous degradation primarily due to ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure to provide adequate maintenance and guarantee the required levels of transport service and safety. In Europe, this is now a legal requirement - a European Directive requires all member states of the European Union to implement a Bridge Management System. However, the process is expensive, requiring the installation of sensing equipment and data acquisition electronics on the bridge. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges as an indicator of its structural condition. This approach eliminates the need for any on-site installation of measurement equipment. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the possibility of extracting the dynamic parameters of the bridge from the spectra of the vehicle accelerations. The effect of vehicle speed, vehicle mass and bridge span length on the detection of the bridge dynamic parameters are investigated. The algorithm is highly sensitive to the condition of the road profile and simulations are carried out for both smooth and rough profiles

Dynamic axle force and road profile identification using a moving vehicle

The axle forces applied by a vehicle through its wheels are a critical part of the interaction between vehicles, pavements and bridges. Therefore, the minimisation of these forces is important in order to promote long pavement life spans and ensure that bridge loads are small. Moreover, as the road surface roughness affects the vehicle dynamic forces, the monitoring of pavements for highways and bridges is an important task. This paper presents a novel algorithm to identify these dynamic interaction forces which involves direct instrumentation of a vehicle with accelerometers. The ability of this approach to predict the pavement roughness is also presented. Moving force identification theory is applied to a vehicle model in theoretical simulations in order to obtain the interaction forces and pavement roughness from the measured accelerations. The method is tested for a range of bridge spans in simulations and the influence of road roughness level on the accuracy of the results is investigated. Finally, the challenge for the real-world problem is addressed in a laboratory experiment.

Parametric study to extract bridge frequencies from the dynamic response of passing vehicles

A conventional way to identify bridge frequencies is utilizing vibration data measured directly from the bridge. A drawback with this approach is that the deployment and maintenance of the vibration sensors are generally costly and time-consuming. One way to cope with the drawback is an indirect approach utilizing vehicle vibrations while the vehicle passes over the bridge. In the indirect approach, however, the vehicle vibration includes the effect of road surface roughness, which makes it difficult to extract the bridge modal properties. One solution may be subtracting signals of two trailers towed by a vehicle to reduce the effect of road surface roughness. A simplified vehicle-bridge interaction model is used in the numerical simulation; the vehicle - trailer and bridge system are modeled as a coupled model. In addition, a laboratory experiment is carried out to verify results of the simulation and examine feasibility of the damage detection by the indirect method.

Targeting translocator protein (18Â kDa) (TSPO) dampens pro-inflammatory microglia reactivity in the retina and protects from degeneration

BACKGROUND: Reactive microglia are commonly seen in retinal degenerative diseases, and neurotoxic microglia responses can contribute to photoreceptor cell death. We and others have previously shown that translocator protein (18 kDa) (TSPO) is highly induced in retinal degenerations and that the selective TSPO ligand XBD173 (AC-5216, emapunil) exerts strong anti-inflammatory effects on microglia in vitro and ex vivo. Here, we investigated whether targeting TSPO with XBD173 has immuno-modulatory and neuroprotective functions in two mouse models of acute retinal degeneration using bright white light exposure.

METHODS: BALB/cJ and Cx3cr1 (GFP/+) mice received intraperitoneal injections of 10 mg/kg XBD173 or vehicle for five consecutive days, starting 1 day prior to exposure to either 15,000 lux white light for 1 h or 50,000 lux focal light for 10 min, respectively. The effects of XBD173 treatment on microglia and Müller cell reactivity were analyzed by immuno-stainings of retinal sections and flat mounts, fluorescence-activated cell sorting (FACS) analysis, and mRNA expression of microglia markers using quantitative real-time PCR (qRT-PCR). Optical coherence tomography (OCT), terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) stainings, and morphometric analyses were used to quantify the extent of retinal degeneration and photoreceptor apoptosis.

RESULTS: Four days after the mice were challenged with bright white light, a large number of amoeboid-shaped alerted microglia appeared in the degenerating outer retina, which was nearly completely prevented by treatment with XBD173. This treatment also down-regulated the expression of TSPO protein in microglia but did not change the TSPO levels in the retinal pigment epithelium (RPE). RT-PCR analysis showed that the microglia/macrophage markers Cd68 and activated microglia/macrophage whey acidic protein (Amwap) as well as the pro-inflammatory genes Ccl2 and Il6 were reduced after XBD173 treatment. Light-induced degeneration of the outer retina was nearly fully blocked by XBD173 treatment. We further confirmed these findings in an independent mouse model of focal light damage. Retinas of animals receiving XBD173 therapy displayed significantly more ramified non-reactive microglia and more viable arrestin-positive cone photoreceptors than vehicle controls.

CONCLUSIONS: Targeting TSPO with XBD173 effectively counter-regulates microgliosis and ameliorates light-induced retinal damage, highlighting a new pharmacological concept for the treatment of retinal degenerations.

Determining the Presence of Scour around Bridge Foundations Using Vehicle-Induced Vibrations

Bridge scour is the number one cause of failure in bridges located over waterways. Scour leads to rapid losses in foundation stiffness and can cause sudden collapse. Previous research on bridge health monitoring has used changes in natural frequency to identify damage in bridge beams. The possibility of using a similar approach to identifying scour is investigated in this paper. To assess if this approach is feasible, it is necessary to establish how scour affects the natural frequency of a bridge, and if it is possible to measure changes in frequency using the bridge dynamic response to a passing vehicle. To address these questions, a novel vehicle–bridge–soil interaction (VBSI) model was developed. By carrying out a modal study in this model, it is shown that for a wide range of possible soil states, there is a clear reduction in the natural frequency of the first mode of the bridge with scour. Moreover, it is shown that the response signals on the bridge from vehicular loading are sufficient to allow these changes in frequency to be detected.

Techno-Economic Feasibility of Selective CO2 Capture Processes from Biogas Streams using Ionic Liquids as Physical Absorbents

Biogas from anaerobic digestion of sewage sludge is a renewable resource with high energy content, which is formed mainly of CH4 (40-75 vol.%) and CO2 (15-60 vol.%) Other components such as water (H2O, 5-10 vol.%) and trace amounts of hydrogen sulfide and siloxanes can also be present. A CH4-rich stream can be produced by removing the CO2 and other impurities so that the upgraded bio-methane can be injected into the natural gas grid or used as a vehicle fuel. The main objective of this paper is to develop a new modeling methodology to assess the technical and economic performance of biogas upgrading processes using ionic liquids which physically absorb CO2. Three different ionic liquids, namely the 1-ethyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide, 1-hexyl-3-methylimidazoliumbis[(trifluoromethyl)sulfonyl]imide and trihexyl(tetradecyl)phosphonium bis[(trifluoromethyl)sulfonyl]imide, are considered for CO2 capture in a pressure-swing regenerative absorption process. The simulation software Aspen Plus and Aspen Process Economic Analyzer is used to account for mass and energy balances as well as equipment cost. In all cases, the biogas upgrading plant consists of a multistage compressor for biogas compression, a packed absorption column for CO2 absorption, a flash evaporator for solvent regeneration, a centrifugal pump for solvent recirculation, a pre-absorber solvent cooler and a gas turbine for electricity recovery. The evaluated processes are compared in terms of energy efficiency, capital investment and bio-methane production costs. The overall plant efficiency ranges from 71-86 % whereas the bio-methane production cost ranges from £6.26-7.76 per GJ (LHV). A sensitivity analysis is also performed to determine how several technical and economic parameters affect the bio-methane production costs. The results of this study show that the simulation methodology developed can predict plant efficiencies and production costs of large scale CO2 capture processes using ionic liquids without having to rely on gas solubility experimental data.