A new monitoring system for piping systems in fossil fired power plants

A CEC-funded project has been performed to tackle the problem of producing an advanced Life Monitoring System (LMS) which would calculate the creep and fatigue damage experienced by high temperature pipework components. Four areas were identified where existing Life Monitoring System technology could be improved:

1. 1. the inclusion of creep relaxation

2. 2. the inclusion of external loads on components

3. 3. a more accurate method of calculating thermal stresses due to temperature transients

4. 4. the inclusion of high cycle fatigue terms.

The creep relaxation problem was solved using stress reduction factors in an analytical in-elastic stress calculation. The stress reduction factors were produced for a number of common geometries and materials by means of non-linear finite element analysis. External loads were catered for by producing influence coefficients from in-elastic analysis of the particular piping system and using them to calculate bending moments at critical positions on the pipework from load and displacement measurements made at the convenient points at the pipework. The thermal stress problem was solved by producing a completely new solution based on Green's Function and Fast Fourier transforms. This allowed the thermal stress in a complex component to be calculated from simple non-intrusive thermocouple measurements made on the outside of the component. The high-cycle fatigue problem was dealt with precalculating the fatigue damage associated with standard transients and adding this damage to cumulative total when a transient occurred.

The site testing provided good practical experience and showed up problems which would not otherwise have been detected.     

Probabilistic analysis of a static frame model

This paper describes our efforts during our participation in the Sandia Validation Workshop. The focus of the paper is the calibration of material models and simulation of random fields to characterize the variations of material properties across spatial field. Both parametric and non-parametric methods were used to represent uncertainty. Part of the challenge of this problem is the small amount of data that is available for the necessary probabilistic analyses in support of calibration, validation, accreditation and prediction activities. The analysis methods and corresponding results are described.     

Impact of the addition of an enzyme pool on an activated sludge system treating dairy wastewater under fat shock loads

BACKGROUND: The application of lipase‐rich enzyme pools (such as the crude solid enzymatic preparation (SEP) obtained from Penicillium restrictum solid‐state fermentation of agro‐industrial wastes) to activated sludge systems may be an effective strategy for preventing various operational problems. The continuous addition of SEP to the treatment system can become cost‐prohibitive when in situ production and/or storage are factored in. The application of SEP to high‐fat wastewater treatment would only be justified as an emergency measure, such as a sudden increase in the fat content of the bioreactor influent. Therefore, the primary objective of this work was to investigate the efficiency of a crude SEP during fat shock loads, simulated through the periodic addition of dairy industry waste containing high fat concentrations to the feed stock of an activated sludge system, operated in continuous mode. RESULTS: The test bioreactor exhibited a higher average chemical oxygen demand (COD) removal efficiency than the control bioreactor (83% for control and 90% for test) and the fat accumulation in the biological flocs of the test bioreactor was 3.2 times lower than that in the control bioreactor. Turbidity was also lower in the effluent of the test bioreactor (123 and 66 FTU in control and test, respectively) and it had a shorter recovery time between shock loads, especially when the interval between loads was shorter than one month (biweekly and weekly shock loads). CONCLUSION: The addition of SEP during fat overloads in the reactor feed maintained efficient COD removal in the test bioreactor for 270 days without any operational problems. Copyright © 2008 Society of Chemical Industry     

Approach for Overcoming Numerical Inaccuracy Caused by Load Discontinuity

It was found that the discontinuity at the end of an impulse will lead to numerical inaccuracy as this discontinuity will result in an extra impulse and thus an extra displacement in the time history analysis. In addition, this extra impulse is proportional to the discontinuity value at the end of the impulse and the size of integration time step. To overcome this difficulty, an effective approach is proposed to reduce the extra impulse and hence the extra displacement. In fact, the novel approach proposed in this paper is to perform a single small time step immediately upon the termination of applied impulse, whereas other time steps can be conducted by using the step size determined from accuracy consideration in period. The feasibility of this approach is analytically explored. Further, analytical results are confirmed by numerical examples. Numerical studies also show that this approach can be applied to other step-by-step integration methods. It seems that to slightly complicate the programming of dynamic analysis codes is the only disadvantage of this approach.     

Sensitivity of generation reserve requirements in deregulated power systems

Since demand for power exhibits great variability the amount of firm energy to be purchased to meet real time demand based on forecasts is usually different from the realized demand for that period. The role of generation reserves is to meet the real time fluctuations of power demand. The predictable part of the demand is met through purchases of firm energy. In this paper a model is presented to determine optimal quantities of firm energy and generation reserves to meet random demands. The model is then parameterized introducing a set of factors to perform a sensitivity study. A full factorial experiment is designed to study the impact of five factors on the response variable (i.e., proportion of generation reserves on the total purchased quantity). An example consisting of 640 simulations corresponding to 2⁵ treatment combinations evaluated over 20 randomly generated mean demands is used to identify significant factors on the response variable. Results from the experiment suggest that generation reserve requirements should be adjusted considering changes in significant factors and in the mean demand over the dispatch interval.     

Biofiltration of toluene in the absence and the presence of ethyl acetate under continuous and intermittent loading

BACKGROUND: Two peat biofilters were used for the removal of toluene from air for one year. One biofilter was fed with pure toluene and the other received 1:1 (by weight) ethyl acetate:toluene mixture. RESULTS: The biofilters were operated under continuous loading: the toluene inlet load (IL) at which 80% removal occurred was 116 g m^?3 h^?1 at 57 s gas residence time. Maximum elimination capacity of 360 g m^?3 h^?1 was obtained at an IL of 745 g m^?3 h^?1. The elimination of toluene was inhibited by the presence of ethyl acetate. Intermittent loading, with pollutants supplied for 16 h/day, 5 days/week, did not significantly affect the removal efficiency (RE). Biomass was fully activated in 2 h after night closures, but 6 h were required to recover RE after weekend closures. Live cell density remained relatively constant over the operational period, while the dead cell fraction increased. Finally, a 15 day starvation period was applied and operation then re‐started. Performance was restored with similar re‐acclimatization period to that after weekend closures, and a reduction in dead cell fraction was observed. CONCLUSION: This study demonstrates the capacity of the system to handle intermittent loading conditions that are common in industrial practices, including long‐term starvation. Copyright © 2008 Society of Chemical Industry     

“Biaxiality Effect” on the Energy Dissipated by Elastoplastic Base-Isolators

A plane elastic-plastic solid body presenting kinematic hardening is used to simulate a pair of dampers at the base of a rigid structure and determine the energy dissipation under conditions of assigned, homogeneous cyclic loading. The well-known von Mises theory of plasticity is applied with the aim of obtaining analytical solutions to the problem. Such solutions are arrived at by first calculating the Odqvist parameter, which yields dimensionless relations that depend on the external loads and mechanical properties of the material. The results, in terms of dissipated energy, are given for the case of a sinusoidal process, represented with the help of dimensionless parameters useful for engineering applications.     

Improving human robot collaboration through Force/Torque based learning for object manipulation

Human–Robot Collaboration (HRC) is a term used to describe tasks in which robots and humans work together to achieve a goal. Unlike traditional industrial robots, collaborative robots need to be adaptive; able to alter their approach to better suit the situation and the needs of the human partner. As traditional programming techniques can struggle with the complexity required, an emerging approach is to learn a skill by observing human demonstration and imitating the motions; commonly known as Learning from Demonstration (LfD). In this work, we present a LfD methodology that combines an ensemble machine learning algorithm (i.e. Random Forest (RF)) with stochastic regression, using haptic information captured from human demonstration. The capabilities of the proposed method are evaluated using two collaborative tasks; co-manipulation of an object (where the human provides the guidance but the robot handles the objects weight) and collaborative assembly of simple interlocking parts. The proposed method is shown to be capable of imitation learning; interpreting human actions and producing equivalent robot motion across a diverse range of initial and final conditions. After verifying that ensemble machine learning can be utilised for real robotics problems, we propose a further extension utilising Weighted Random Forest (WRF) that attaches weights to each tree based on its performance. It is then shown that the WRF approach outperforms RF in HRC tasks.     

A robust critical path in an environment with hybrid uncertainty

In this article, we consider the project critical path problem in an environment with hybrid uncertainty. In this environment, the duration of activities are considered as random fuzzy variables that have probability and fuzzy natures, simultaneously. To obtain a robust critical path with this kind of uncertainty a chance constraints programming model is used. This model is converted to a deterministic model in two stages. In the first stage, the uncertain model is converted to a model with interval parameters by alpha-cut method and distribution function concepts. In the second stage, the interval model is converted to a deterministic model by robust optimization and min-max regret criterion and ultimately a genetic algorithm with a proposed exact algorithm are applied to solve the final model. Finally, some numerical examples are given to show the efficiency of the solution procedure.     

Interactive fuzzy stochastic multi-level 0–1 programming using tabu search and probability maximization

In this paper, we consider interactive fuzzy programming for multi-level 0–1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0–1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. For solving the transformed deterministic problems efficiently, we also introduce novel tabu search for general 0–1 programming problems. A numerical example for a three-level 0–1 programming problem is provided to illustrate the proposed method.