An intelligent emissions controller for fuel lean gas reburn in coal-fired power plants

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NOx) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NOx reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach. Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NOx emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

Aquatic Plant and Dissolved Oxygen Changes in a Reference‐Condition Prairie Stream Subjected to Experimental Nutrient Enrichments

Effects of controlled nutrient additions on a prairie stream were studied using a before‐after‐control‐impact paired design. The site is in a reference condition with low soluble nitrate (NO₃) and phosphate (soluble reactive phosphorus [SRP]) in summer (3 μg NO₃‐N/L, 4 μg SRP/L). Nutrients were added to two reaches over the growing season at two levels (Low Dose — 39 μg NO₃‐N/L and 4.4 SRP/L; High Dose — 119 μg NO₃‐N/L and 15.6 μg SRP/L). Continuously measured dissolved oxygen (DO) and changes in aquatic flora were compared to an upstream Control. Enrichment led microalgae and filamentous algae to increase in density, areal coverage, and thickness, and the magnitude of the changes were largely concordant with dosing (more in the High Dose); algal growth also suppressed macrophytes in the High Dose. Enrichment caused significant increases in diel DO swings whose magnitudes were consistent with dosing level. In the High Dose, benthic algae flourished in the growing season and then senesced en masse in fall. The decomposing algae led DO to crash (ca. 0 mg/L on the bottom), but DO impacts were out‐of‐sync with peak algal growth and photosynthesis, which occurred weeks earlier. This finding provides a plausible explanation as to why high DO delta in streams impacts aquatic life even when concurrently measured DO is not low. When DO crashed, DO was longitudinally patchy, some areas having low DO near the bottom, others near saturation. Geomorphology and exposure to wind may have caused this pattern.     

The role of affective experience in work motivation: Test of a conceptual model

The purpose of this paper was to contribute to understanding of the crucial role of emotion in work motivation by testing a conceptual model developed by Seo, Barrett, and Bartunek (2004) that predicted the impacts of core affect on three behavioral outcomes of work motivation, generative-defensive orientation, effort, and persistence. We tested the model using an Internet-based investment simulation combined with an experience sampling procedure. Consistent with the predictions of the model, pleasantness was positively related to all three of the predicted indices. For the most part, these effects occurred indirectly via its relationships with expectancy, valence, and progress judgment components. Also as predicted by the model, activation was directly and positively related to effort.     

Moving on out: when are employees willing to follow their organization during corporate relocation?

This research examines the willingness of employees to follow their organization when the entire business unit is geographically relocating. The site for the study was a large government defense agency moving from a major U.S. northeastern metropolitan area to a rural area south of Washington, D.C. The study participants were 380 employees who were deciding within the next 6 months if they would relocate, too. Attachment to the present community, attachment to the current organization, and availability of job market alternatives are the factors most significantly associated with willingness to move during corporate relocation. © 1998 John Wiley & Sons, Ltd.     

Mentor–protege diversity and its impact on international internship experiences

This research examines demographic diversity between mentors and proteges on international internships. Using a sample of 138 interns on six‐month overseas assignments, the results indicate that interns who are different in nationality and gender from their mentors are much less likely to receive task‐related, social‐related, and career‐related support from them. Moreover, this deficit in mentoring is associated with poorer socialization to internship assignments, lower levels of learning about international business, lower likelihoods of receiving and accepting job offers from internship employers, and lower perceived career instrumentality of the internships. The implications of the results for future research on mentor–protege diversity and the design of international internships are discussed as well. Copyright © 1999 John Wiley & Sons, Ltd.     

Can Labor Out-Migration Reduce Firewood Consumption by Rural Households in Western Mountainous China

Abstract

The relationship between out-migration of labor in the Qinling mountain area and households’ firewood consumption is explored. Migration and remittances reduce households’ firewood consumption due to increases in both income and opportunity cost of firewood collection. Previous studies have been equivocal because they ignored uncertainty in household economy, which is widespread in forest areas of less developed countries. This study provides additional insight by considering vulnerability and subjective assessment of poverty generated by unstable income and an uncertain future. We provide evidence that the amount of firewood consumed depends on income and opportunity cost of firewood collection, but also on a prudent consumption strategy, due to farmers’ subjective assessment of their future possible poverty. We also find out-migration of labor can reduce per capita firewood consumption but subjective poverty also acts against reduction of firewood consumption.     

Analyzing alternative bio-waste feedstocks for potential biodiesel production using time domain (TD)-NMR

Production of biodiesel is currently limited due to lack of economically beneficial feedstocks. Suitability of municipal wastewater sludge and olive mill waste as feedstocks for biodiesel production was evaluated. The various bio-waste sources were analyzed for their oil content and fatty acid composition using conventional analyses complemented with time domain (TD)-NMR analysis. TD-NMR, a rapid non-destructive method newly applied in this field, yielded good correlations with conventional methods. Overall biodiesel yields obtained by TD-NMR analysis were 7.05% and 9.18% (dry wt) for olive mill pomace and liquid wastes, and 11.92%, 7.07%, and 4.65% (dry wt) for primary, secondary, and anaerobically stabilized sludge, respectively. Fatty acid analysis indicated fundamental suitability of these agro-industrial waste resources for biodiesel production. Evaluation of bio-waste materials by TD-NMR revealed the potential of this tool to identify waste-oil sources cost effectively and quickly, supporting expansion of a sustainable biodiesel industry in Israel and other regions.