A case study on the methane explosion in the excavation chamber of an EPB-TBM and lessons learnt including some recent accidents

This study is related to a case concerning a methane explosion occurred inside the excavation chamber of an EPB-TBM in Silivri-Istanbul on the 20th of May in 2010. The authors of the paper were nominated as official inspectors of the court. A literature survey is first carried out in order to review similar accidents happened worldwide. Causes and effects of the explosion are analyzed later in detail. Precautions against methane emission are also summarized. It is concluded that a methane explosion inside the excavation chamber of an EPB-TBM is a very rare case and was not reported in the literature as the authors’ best knowledge. Oxygen necessary for methane explosion came from the foam used in the excavation chamber. Explosion occurred probably due to sparking caused by friction between screw conveyor and its casing. It is recommended that further research studies should focus on producing more secure foams being functional without oxygen, a methane detector should also placed inside the chamber with a power cut-off system.     

Scenario analysis using Bayesian networks: A case study in energy sector

This paper provides a general overview of creating scenarios for energy policies using Bayesian Network (BN) models. BN is a useful tool to analyze the complex structures, which allows observation of the current structure and basic consequences of any strategic change. This research will propose a decision model that will support the researchers in forecasting and scenario analysis fields. The proposed model will be implemented in a case study for Turkey. The choice of the case is based on complexities of a renewable energy resource rich country. Turkey is a heavy energy importer discussing new investments. Domestic resources could be evaluated under different scenarios aiming the sustainability. Achievements of this study will open a new vision for the decision makers in energy sector.     

Simultaneous heterotrophic and sulfur-oxidizing autotrophic denitrification process for drinking water treatment: control of sulfate production

A long-term performance of a packed-bed bioreactor containing sulfur and limestone was evaluated for the denitrification of drinking water. Autotrophic denitrification rate was limited by the slow dissolution rate of sulfur and limestone. Dissolution of limestone for alkalinity supplementation increased hardness due to release of Ca²⁺. Sulfate production is the main disadvantage of the sulfur autotrophic denitrification process. The effluent sulfate concentration was reduced to values below drinking water guidelines by stimulating the simultaneous heterotrophic and autotrophic denitrification with methanol supplementation. Complete removal of 75 mg/L NO₃-N with effluent sulfate concentration of around 225 mg/L was achieved when methanol was supplemented at methanol/NO₃-N ratio of 1.67 (mg/mg), which was much lower than the theoretical value of 2.47 for heterotrophic denitrification. Batch studies showed that sulfur-based autotrophic NO₂-N reduction rate was around three times lower than the reduction rate of NO₃-N, which led to NO₂-N accumulation at high loadings.     

Failure mechanism of FBGA solder joints in memory module subjected to harmonic excitation

This paper investigates the failure mechanism of Fine-pitch Ball Grid Array (FBGA) solder joints of memory modules due to harmonic excitation by the experiments and the finite element method. A finite element model of the memory module was developed, and the natural frequencies and modes were calculated and verified by experimental modal testing. Modal damping ratios are also obtained and used in the forced vibration analysis. The experimental setup was developed to monitor resistance variation of FBGA solder joints due to the harmonic excitation under Joint Electron Devices Engineering Council (JEDEC) standard service conditions. Experiments showed that the failure of the solder joints of the memory module under vibration mainly occurs due to resonance. Forced vibration analysis was performed to determine the solder joints having high stress concentration under harmonic excitation. It showed that failure occurs due to the relative displacement between PCB and package and solder joints are the most vulnerable part of the memory module under vibration. It also showed that cracked solder joints in the experiments match those in the simulations with the highest stress concentration.     

A Review on the Mechanical Modeling of Composite Manufacturing Processes

The increased usage of fiber reinforced polymer composites in load bearing applications requires a detailed understanding of the process induced residual stresses and their effect on the shape distortions. This is utmost necessary in order to have more reliable composite manufacturing since the residual stresses alter the internal stress level of the composite part during the service life and the residual shape distortions may lead to not meeting the desired geometrical tolerances. The occurrence of residual stresses during the manufacturing process inherently contains diverse interactions between the involved physical phenomena mainly related to material flow, heat transfer and polymerization or crystallization. Development of numerical process models is required for virtual design and optimization of the composite manufacturing process which avoids the expensive trial-and-error based approaches. The process models as well as applications focusing on the prediction of residual stresses and shape distortions taking place in composite manufacturing are discussed in this study. The applications on both thermoset and thermoplastic based composites are reviewed in detail.     

Active inference for dynamic Bayesian networks with an application to tissue engineering

In temporal domains, agents need to actively gather information to make more informed decisions about both the present and the future. When such a domain is modeled as a temporal graphical model, what the agent observes can be incorporated into the model by setting the respective random variables as evidence. Motivated by a tissue engineering application where the experimenter needs to decide how early a laboratory experiment can be stopped so that its possible future outcomes can be predicted within an acceptable uncertainty, we first present a dynamic Bayesian network (DBN) model of vascularization in engineered tissues and compare it with both real-world experimental data and agent-based simulations. We then formulate the question of “how early an experiment can be stopped to guarantee an acceptable uncertainty about the final expected outcome” as an active inference problem for DBNs and empirically and analytically evaluate several search algorithms that aim to find the ideal time to stop a tissue engineering laboratory experiment.     

Aerobic and anoxic biodegradation of benzoate: stability of biodegradative capability under endogenous conditions

Aromatic organic compounds are degraded by different enzyme systems under aerobic and anoxic conditions. This raises the question of how bacteria in biological nitrogen removal processes, which cycle bacteria between aerobic and anoxic environments, regulate their enzyme systems for degrading aromatic compounds. As a first step in answering that question, mixed microbial communities were grown on benzoate as sole carbon source in chemostats under fully aerobic and fully anoxic (nitrate as the electron acceptor) conditions and tested for their ability to degrade benzoate in batch reactors after exposure to aerobic or anoxic conditions in the absence of substrate. Aerobically grown biomass retained its ability to degrade benzoate without loss of activity after endogenous exposure to aerobic conditions for up to 8 h. However, when exposed to anoxic conditions, the biomass rapidly lost its aerobic benzoate degrading activity, retaining less than 20% of the initial activity after 8 h. Similarly, anoxically grown biomass retained its ability to degrade benzoate without loss of activity after endogenous exposure to anoxic conditions for up to 8 h. However, when anoxically grown biomass was exposed to aerobic conditions, only 20% of its initial activity was lost in the first 2 h, after which the remaining activity was retained for up to 8 h. Similar experiments with pyruvate showed that the 20% loss of activity was not due to loss of denitrifying enzymes, suggesting that it was due to loss of catabolic enzymes.     

Automated control and monitoring of thermal processing using high temperature, short time pasteurization

High temperature, short time pasteurization was used to evaluate a computer-based system for controlling the pasteurization process, acquiring data, and monitoring records. Software was used for the control of hot water temperature, flow rate through the centrifugal timing pump, and diversion of under-processed product. Three types of control strategies were conducted: single loop, cascade, and multivariable. The single loop control strategy showed the most rapid responses to temperature changes, but the temperature response curve was slowest to return to its set point. The cascade control strategy showed slower recoveries to temperature changes, but the temperature response curve was smoother. The multivariable control strategy responded slightly faster than the cascade control strategy, and the temperature response curve was slightly smoother than the cascade control strategy. The multivariable control strategy was able to control the flow diversion valve by the use of a lethality controller. The data acquisition system, used to monitor the data obtained from the high temperature, short-time pasteurization system, was within +/- 0.1 degree C of the temperature recorded by the safety thermal limit recorder. Reliability was determined by examining the changes in the position of the flow diversion valve to identify process deviations and by comparing the changes to the event marker on circular charts. The data acquisition system was an effective alternative for monitoring the completeness of data.