Search

Wavy carbon nanotubes (CNTs) are ubiquitously present in high-aspect-ratio CNT arrays used in advanced device applications. This paper investigates the effective modulus and natural frequency of wavy CNTs that have random, sinusoidal, or helical structures. Parameters such as loading deviation angle, boundary condition, and low shear modulus are considered. It was found that loading deviation could cause 3–4 orders modulus reduction for sinusoidal and helical CNTs at small waviness ratio. In contrast, there is slight modulus enhancement by a small loading deviation for randomly wavy CNTs. By applying pined or fixed boundary condition at the loading end, the moduli of wavy CNTs may be enhanced by up to 4 orders in magnitude. As another critical parameter, low shear modulus (∼50 MPa) may cause significant modulus reduction only for helical CNTs, about 2 orders of magnitude due to large shear and torsional deformation. The natural frequencies of wavy CNTs were also computed, showing that helical CNTs generally have lower frequency than other wavy CNTs. Furthermore, very low shear modulus could result in significant frequency reduction for helical CNTs, but has limited effect on random or sinusoidal CNTs. With the high sensitivity to shear modulus, helical CNTs are thus more desirable in the electric-field-induced resonance testing used for CNT property characterization. The findings on the properties of wavy CNTs can provide fundamental guidelines for the design of CNT arrays or CNT-based composites.

Die-attach film failure during soldering reflow is of particular concern for reliability of 3D ultra-thin stacked-die chip scale packages (CSPs), as extremely high vapor pressure can be generated from vaporized moisture to cause severe damages. Under rapid heating, pressure-driven moisture vapor flow could become as significant as concentration-driven diffusion, and should be included in moisture transport models. In this study, a convection–diffusion (CD) model is presented for analyzing vapor pressure and moisture behavior of soft die-attach films for 3D CSPs, with both vapor flow and the effect of temperature on saturated moisture content considered. By using a 1D model according to experimental observations, the over-saturation phenomenon in the thin film and vapor pressure evolution are investigated. It is found that the reflow profiles and substrate thickness could have great impact on the magnitude of vapor pressure, which agrees well with the experimental results. Sensitivity analyses show that a high vapor permeability and a large porosity could lead to low vapor pressure. Being a vapor pressure-based model, the CD model is suitable to study multiple-material systems without discontinuity issue at the material boundary. It is concluded that the CD model could serve as an effective method for predicting vapor pressure and moisture behaviors during soldering reflow for 3D stacked-die CSPs.

This paper presents a comprehensive review and comparison of different theories and models for water vapor pressure under rapid heating in moisture permeable materials, such as polymers or polymer composites. Numerous studies have been conducted, predominately in microelectronics packaging community, to obtain the understanding of vapor pressure evolution during soldering reflow for encapsulated moisture. Henry's law-based models are introduced first. We have shown that various models can be unified to a general form of solution. Two key parameters are identified for determining vapor pressure: the initial relative humidity and the net heat of solution. For materials with nonlinear sorption isotherm, the analytical solutions for maximum vapor pressure are presented. The predicted vapor pressure, using either linear sorption isotherm (Henry's law) or nonlinear sorption isotherm, can be greater than the saturated water vapor pressure. Such an “unphysical” pressure solution needs to be further studied. The predicted maximum vapor pressure is proportional to the initial relative humidity, implying the history dependence. Furthermore, a micromechanics-based vapor pressure model is introduced, in which the vapor pressure depends on the state of moisture in voids. It is found that the maximum vapor pressure stays at the saturated vapor pressure provided that the moisture is in the mixed liquid/vapor phase in voids. And, the vapor pressure depends only on the current state of moisture condition. These results are contradictory to the model predictions with sorption isotherm theories. The capillary effects are taken into consideration for the vapor pressure model using micromechanics approach.

Modeling vapor pressure is crucial for studying the moisture reliability of microelectronics, as high vapor pressure can cause device failures in environments with high temperature and humidity. To minimize the impact of vapor pressure, a super-hydrophobic (SH) coating can be applied on the exterior surface of devices in order to prevent moisture penetration. The underlying mechanism of SH coating for enhancing device reliability, however, is still not fully understood. In this paper, we present several existing theories for predicting vapor pressure within microelectronic materials. In addition, we discuss the mechanism and effectiveness of SH coating in preventing water vapor from entering a device, based on experimental results. Two theoretical models, a micro-mechanics-based whole-field vapor pressure model and a convection-diffusion model, are described for predicting vapor pressure. Both methods have been successfully used to explain experimental results on uncoated samples. However, when a device was coated with an SH nanocomposite, weight gain was still observed, likely due to vapor penetration through the SH surface. This phenomenon may cast doubt on the effectiveness of SH coatings in microelectronic devices. Based on current theories and the available experimental results, we conclude that it is necessary to develop a new theory to understand how water vapor penetrates through SH coatings and impacts the materials underneath. Such a theory could greatly improve microelectronics reliability.

Moisture may cause many detrimental effects to polymers and their composites, thus inhibiting the applications of polymeric materials in hot and humid environments. In this article, a convection–diffusion porous media model is derived to better characterize rapid moisture transport in polymer composites at high temperatures. The model considers both continuum diffusion in solid and high-pressure convection taking place in the pore network. Coupling of convection and diffusion is achieved by combining the law of conservation of mass, Darcy's law, the liquid–vapor chemical equilibrium, and the ideal gas law. The presented model is validated by conducting experimental tests on an epoxy compound. It is found that the proposed convection–diffusion model is more effective than diffusion-only and convection-only models for interpreting rapid desorption tests at high temperatures. A numerical study is also performed to predict maximum vapor pressure during a rapid heating process. Vapor pressure is found to be as high as 6.5 MPa at a heating rate of 10 K/s. It is concluded that the convection–diffusion model is able to capture both vapor dynamics and diffusion mechanism in porous polymeric materials, and can be potentially used to further investigate polymer-moisture interactions. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2015, 53, 1440–1449

All electronic packages involve with a multi-material system, in which many of the materials or films are susceptible to moisture absorption. Despite dissimilar material properties, moisture transports in a multi-material system from a high "water activity" region to a low one, where water activity is a measure of water energy in a specific substance. This, however, has not been well recognized in electronic packaging industry. Furthermore, moisture concentration gradient is often deemed as the driving force for moisture transport, which inevitably poses a challenging discontinuity issue at interface for moisture diffusion in multi-material systems. Even though several normalization schemes have been developed in the literature, much confusion has existed on the fundamental principle of moisture diffusion. This paper derived an activity-based diffusion model using the concepts of chemical potential and water activity. We showed that the continuity of water activity at interface in dissimilar materials is warranted, and furthermore, many nonlinear water sorption isotherms can be applied in the activity-based model by using a new property called "generalized solubility". The activity-based model thus is capable to study complex moisture diffusion in multi-material system. Moreover, in this paper, the activity-based model was used to unify the different normalization theories, such as solubility-based and the so-called wetness normalization approaches. We also discussed how water sorption isotherm would affect the conventional moisture diffusivity, finding that only for some limiting cases (e.g., Henry sorption isotherm), the "effective moisture diffusivity" becomes independent of moisture concentration. We pointed out that the generalized solubility that are needed to solve the diffusion can be obtained using conventional terms such as saturated moisture concentration and solubility. As demonstration, a numerical example was performed in commercial finite element software to study the moisture diffusion through a bi-material interface under dynamic temperature and humidity conditions. The results from different nonlinear sorption isotherms were compared to demonstrate the capability and versatility of the model. We concluded that the activity-based moisture diffusion model is a unified and versatile approach to study and understand the moisture diffusion mechanism in IC packages.

East Asia is the largest source region of global anthropogenic mercury emissions, and contributes to atmospheric mercury concentration and deposition in other regions. Similarly, mercury from the global pool also plays a role in the chemical transport of mercury in East Asia. Annual simulations of atmospheric mercury in East Asia were performed using the STEM-Hg modeling system to study the mass budgets of mercury in the region. The model results showed strong seasonal variation in mercury concentration and deposition, with signals from large point sources. The annual mean concentrations for gaseous elemental mercury, reactive gaseous mercury and particulate mercury in central China and eastern coastal areas were 1.8 ng m(-3), 100 pg m(-3) and 150 pg m(-3), respectively. Boundary conditions had a strong influence on the simulated mercury concentration and deposition, contributing to 80% of the concentration and 70% of the deposition predicted by the model. The rest was caused by the regional emissions before they were transported out of the model domain. Using different oxidation rates reported for the Hg(0)-O(3) reaction (i.e., by Hall, 1995 vs. by Pal and Ariya, 2004) led to a 9% difference in the predicted mean concentration and a 40% difference in the predicted mean deposition. The estimated annual dry and wet deposition for East Asia in 2001 was in the range of 590-735 Mg and 482-696 Mg, respectively. The mercury mass outflow caused by the emissions in the domain was estimated to be 681-714 Mg yr(-1). This constituted 70% of the total mercury emission in the domain. The greatest outflow occurred in spring and early summer.

East Asia contributes to nearly 50% of the global anthropogenic mercury emissions into the atmosphere. Recently, there have been concerns about the long-range transport of mercury from East Asia, which may lead to enhanced dry and wet depositions in other regions. In this study, we performed four monthly simulations (January, April, July and October in 2005) using CMAQ-Hg v4.6 for a number of emission inventory scenarios in an East Asian model domain. Coupled with mass balance analyses, the chemical transport of mercury in East Asia and the resulted mercury emission outflow were investigated. The total annual mercury deposition in the region was estimated to be 821 Mg, with 396 Mg contributed by wet deposition and 425 Mg by dry deposition. Anthropogenic emissions were responsible for most of the estimated deposition (75%). The deposition caused by emissions from natural sources was less important (25%). Regional mercury transport budgets showed strong seasonal variability, with a net removal of RGM (7–15 Mg month−1) and PHg (13–21 Mg month−1) in the domain, and a net export of GEM (60–130 Mg month−1) from the domain. The outflow caused by East Asian emissions (anthropogenic plus natural) was estimated to be in the range of 1369–1671 Mg yr−1, of which 50–60% was caused by emissions from natural sources. The emission outflow represented about 75% of the total mercury emissions in the region, and would contribute to 20–30% of mercury deposition in remote receptors.

Speciated samples of PM2.5 were collected at the Big Bend site from July of 2003 to June 2006 and the McDonald Observatory site from July of 2003 to August of 2005 in southwestern Texas, respectively, by the US Environmental Protection Agency. A total of 175 samples for the Big Bend site and 105 samples for the McDonald Observatory site with 52 species were measured; however, 30 and 32 species from the Big Bend and McDonald Observatory sites, respectively, were excluded because of too much below-detection-limit data. Due to the laboratory change about November 1 of 2004 and possible analytical artifacts, phosphorous was excluded as well. Among the species excluded, 31 species are common to both sites. The two data sets were analyzed by positive matrix factorization to infer the sources of PM observed at the two sites. The analysis resolved five source-related factors for Big Bend and four for McDonald Observatory. Sulfate-rich secondary aerosol, coal burning, motor vehicle/road dust, and a mixed factor were identified as common sources to both sites. The other factor identified for Big Bend is related to soil. Sulfate mainly exists as ammonium salts. The sulfate-rich secondary aerosols account for about 62% and 66% of the PM2.5 mass concentration at the two sites, respectively. The highest concentration of Si associated with Ca, Fe, $${\text{SO}}_4^{2 - } $$ , and organic carbon at the two sites was possibly attributed to the coal-fired power plants in the region. Basically, the factor of sulfate and coal burning at the two sites showed similar chemical composition profiles and seasonal variation that reflect the regional characteristics of these sources. The regional factors of sulfate, coal burning, and soil showed predominantly low-frequency variations; however, the area-related and/or local factors showed both high and low frequency variations. The motor vehicle/road dust and the mixed factors were likely to be area-related and/or local source.

In this study, the model response in terms of simulated mercury concentration and deposition to boundary condition (BC), initial condition (IC), model grid resolution (12 km versus 36 km), and two alternative Hg(II) reduction mechanisms, was investigated. The model response to the change of gaseous elemental mercury (GEM) concentration from 0 to 2 ng m−3 in IC/BC is found to be very linear (r2>0.99) based on the results of sensitivity simulations in July 2001. An increase of 1 ng m−3 of GEM in BC resulted in an increase of 0.81 ng m−3 in the monthly average of total mercury concentration, and 1270 ng m−2 in the monthly total deposition. IC has similar but weaker effects compared to those of BC. An increase of 1 ng m−3 of GEM in IC resulted in an increase of 0.14 ng m−3 in the monthly average of total mercury concentration, and 250 ng m−2 in the monthly total deposition. Varying reactive gaseous mercury (RGM) or particulate mercury (PHg) in BC/IC has much less significant impact. Simulation results at different grid resolutions show good agreement (slope=0.950–1.026, r=0.816–0.973) in mercury concentration, dry deposition, and total deposition. The agreement in wet deposition is somewhat weaker (slope=0.770–0.794, r=0.685–0.892) due to the difference in emission dilution and simulated precipitation that subsequently change reaction rates in the aqueous phase. Replacing the aqueous Hg(II)-HO2 reduction by either RGM reduction by CO (5×10−18 cm3 molecule−1 s−1) or photoreduction of RGM (1×10−5 s−1) gives significantly better model agreement with the wet deposition measured by Mercury Deposition Network (MDN). Possible ranges of the reduction rates are estimated based on model sensitivity results. The kinetic estimate requires further verification by laboratory studies.

Speciated samples of PM2.5 were collected at the Bayland Park and Orange sites in Southeastern Texas by US EPA (Environmental Protection Agency) from July 2003 to August 2005. A total of 256 samples for the Bayland Park site and 293 samples for the Orange site with 52 species were measured; however, 22 species were excluded because of too many below-detection-limit data. Among the 22 species excluded, 19 species are common to both sites. The two data sets were analyzed by positive matrix factorization (PMF) to infer the sources of PM observed at the two sites. The analysis identified ten common source-related factors: sulphate-rich secondary aerosol I, sulphate-rich secondary aerosol II, cement/carbon-rich, wood smoke, motor vehicle/road dust, nitrate-rich secondary aerosol, metal processing, soil, sea salt, and chloride-depleted marine aerosol. sulphate and nitrate mainly exist as ammonium salts. The two sulphate-rich secondary aerosols account for about 59% and 54% of the PM2.5 mass concentration at the two sites, respectively. The factor containing highest concentrations of Cl and Na was attributed to sea salt due to the proximity of the monitoring sites to the Gulf of Mexico. The chloride-depleted marine aerosol was related to the sea salt aerosol but was identified separately due to the chlorine replacement reactions. Basically, the factor of sulphate, nitrate, and soil at the two sites showed similar chemical composition profiles and seasonal variation that reflect the regional characteristics of these sources. The regional factors showed predominantly low frequency variations, however, the area-related and local factors showed both high and low frequency variations. Motor vehicle/road dust, sea salt, and chloride-depleted marine aerosol were likely to be area-related factors. Cement/carbon-rich, wood smoke, and metal processing factor were likely to be the local sources. Des echantillons d'especes de PM25 ont ete recueillis aux sites de Bayland Park et Orange dans le sud-est du Texas par l'US EPA (Environmental Protection Agency) entre juillet 2003 et aout 2005. En tout, 256 echantillons de Bayland Park et 293 echantillons d'Orange avec 52 especes ont ete mesures; cependant, 22 especes ont ete exclues en raison d'un trop grand nombre de donnees en dessous de la limite de detection. Parmi les 22 especes exclues, 19 especes sont communes aux deux sites. Les deux ensembles de donnees ont ete analyses par factorisation a matrice positive (PMF) pour en deduire les sources de PM observees dans les deux sites. L'analyse a permis d'identifier dix facteurs relies aux sources communes: aerosol secondaire I riche en sulfate, aerosol secondaire II riche en sulfate, espece riche en ciment/carbone, fumee de bois, poussiere de route/vehicule a moteur, aerosol secondaire riche en nitrate, traitement des metaux, sol, sel de mer et aerosol marin appauvri en chlorure. Le sulfate et le nitrate existent principalement comme sels d'ammonium. Les deux aerosols secondaires riches en sulfate representent 59% et 54% de la concentration massique de PM25 aux deux sites, respectivement. Le facteur contenant les plus hautes concentrations de Cl et Na est attribue au sel de mer en raison de la proximite des sites de surveillance du Golfe du Mexique. L'aerosol marin appauvri en chlorure est relie a l'aerosol de sel de mer mais a ete identifie separement du fait des reactions de remplacement du chlorure. Essentiellement, le facteur de sulfate, de nitrate et de sol aux deux sites montre des profils de composition chimiques et une variation saisonniere qui refletent les caracteristiques regionales de ces sources. Les facteurs regionaux montrent de facon predominante de faibles variations de frequence; cependant, les facteurs lies a la region et les facteurs locaux montrent a la fois des variations de frequences elevees et faibles. La poussiere de route/vehicule a moteur, le sel de mer et l'aerosol marin appauvri en chlorure sont probablement des facteurs relies a la region. L'espece riche en ciment/carbone, la fumee de bois et le facteur de traitement des metaux sont probablement des sources locales.

Mercury emissions from coal-fired power plants have been a great environmental and regulatory concern due to the toxic nature of mercury and the significant amount of emissions from these plants. An effective method for controlling mercury emission is to employ activated carbon to adsorb mercury from the combustion flue gas. In this study, an activated carbon mercury sorption model was applied to simulate a confined-bed mercury emission control process. Model simulations were performed to generate dynamic mercury concentration profiles and the corresponding profiles of mercury uptake by activated carbon at various bed locations under various process conditions. The simulation parameters included flue gas flow rate, inlet mercury concentration, and adsorption bed temperature. The study has demonstrated the applicability of the model for simulating the process and provided insights into the mercury control process especially the effects of flue gas flow rate, inlet mercury concentration, and activated carbon bed temperature on the process. Such information is critically needed in the design and operation of a mercury emission control process involving activated carbon adsorption.

Speciated samples of PM2.5 were collected at a site in Jefferson County, Texas by US EPA (Environmental Protection Agency) from July of 2003 to August of 2005. A total of 269 samples with 52 species were measured; however, 22 species were excluded in this study because of too many below-detection-limit data. The data set was analyzed by positive matrix factorization (PMF) to infer the sources of PM observed at the site. The analysis identified ten sources: sulfate-rich secondary aerosol I (35.9%), sulfate-rich secondary aerosol II (21.0%), cement/carbon-rich (11.7%), wood smoke (8.8%), metal processing (6.3%), motor vehicle/road dust (5.7%), nitrate-rich secondary aerosol (3.3%), soil (3.2%), sea salt (2.6%), and chloride depleted marine aerosol (1.6%). Sulfate and nitrate mainly exist as salts. The two sulfate-rich secondary aerosols account for almost 57% of the PM2.5 mass concentration. The factor containing highest concentrations of Cl and Na was attributed to sea salt due to the proximity of the monitoring site to the Gulf of Mexico. The chloride depleted marine aerosol was related to the sea salt aerosol. Cement/carbon-rich, wood smoke, metal processing, and motor vehicle/road dust factor were likely to be the local sources.

Heat stress on workers working outdoors in the power industry may result in fatigue and deterioration in task performance. This research collected and analyzed data on task performance of workers working indoors and outdoors with and without a cooling suit. The task performance was compared on the basis of heart rate, oxygen consumption, tympanic temperature, subjective responses, productivity, and error rates. Based on One-Way Analysis Of Variance (ANOVA) results, a significantly lower estimated working oxygen consumption was observed (p < .001) when the cooling suit was worn. The productivity was higher while workers wore the cooling suit as compared to no cooling suit (p = .011) whereas the error rates were significantly lower (p < .001). Also a significantly lower self-reported discomfort was observed in the neck and shoulders while working wearing the cooling suit (p = .004). This study concluded that wearing a cooling suit while working outdoors was associated with physiological benefits as well as improved task performance of the study participants. heat stress energy expenditure task performance cooling suit

Emission inventory is one of the required inputs to air quality models. To assist in the urban and regional modeling efforts, United States Environmental Protection Agency (EPA) has compiled a National Emission Inventory (NEI) for criterion pollutants, and the precursors of ozone and particulate matter (PM). In December 2002, EPA released the 1999 NEI estimates (NEI99), which represent the most recent national emission data. However, the data sets are not in model-ready format for air quality simulations. This present work converts the NEI99 Final Version 2 data sets into Inventory Data Analyzer (IDA) format and processes the data using the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system to generate a gridded emission inventory in a domain covering the west Gulf Coast Region, USA. The spatial and diurnal emission characteristics of the gridded emission inventories are then assessed and compared with those of the National Emission Trend 1996 (NET96). The NEI99 database contains more complete emission records in both area and point sources. It is also found that NEI99 data exhibit greater emissions with respect to point and mobile sources but smaller emissions with respect to area sources when compared to the corresponding gridded NET96 data in the same study domain. The most distinct differences between the NEI99 and NET96 databases are CO emission of mobile sources, SO2 emissions of point sources, and VOC/PM/NH3/NOx emissions of area and non-road sources. The gridded NEI99 data show low VOC/NOx ratios (

Air pollutant emission is one of the predominant factors affecting urban air quality such as ground-level ozone formation. This paper assesses the impact of changing emission inventory scenarios, based on combinations of point, mobile, area/non-road and biogenic sources, on the tropospheric ozone concentration in two southeast Texas urban areas, i.e. Houston-Galveston and Beaumont-Port Arthur, during the rapid ozone formation event (ROFE) on August 25, 2000. The EPA's Community Multiscale Air Quality (CMAQ) modeling system with 1999 national emission inventory (NEI99) estimates and updated SAPRC99 chemical mechanism are used in the sensitivity analysis for twelve different emission scenarios. Based on model results, it is found that the point source emission of NOx and VOC contributes the greatest ozone peak in the ROFE. Removing Texas point sources of VOC and NOx emission from the inventory results in a reduction in peak O3 concentration by 128 and 70 ppbv in Houston urban area, respectively. Similar but less drastic impact from point source is also observed in the Beaumont-Port Arthur area. The effect on peak ozone concentration due to mobile, area and non-road sources emissions are less significant compared to that of point source emission. Reducing VOC emission appears to be more effective than reducing NOx emission in lowering peak O3 concentration in the studied region. Although biogenic emission can contribute up to 37 ppbv of peak ozone level over a large area, the affected area is away from the urban region of concern, and should not be the main cause for O3 non-attainment in the two urban areas. Removing CO emission from mobile sources does not lead to significant reduction (

An effective method for controlling elemental mercury emission is to employ activated carbon (AC) to adsorb mercury from the combustion flue gas. An environmental concern regarding the process is the low sorption capacity of AC. The mercury control practice, therefore, will need a large quantity of fresh AC and generate an equally large quantity of spent AC contaminated with various forms of mercury. A practical solution to this problem is to regenerate the AC for reuse. In this study, an activated carbon mercury sorption/desorption model was developed for simulating the mercury sorption/desorption process at various temperatures under both the fixed and fluidized bed conditions. Mercury sorption experiments were carried out to determine the best-fit model parameter and the parameter-fitted model was then used to simulate the mercury desorption processes under various conditions. The simulation results have indicated that both the desorption temperature and the fluidization condition affect significantly the mercury desorption rates.

Quantifying the contribution of emission sources responsible for mercury deposition in specific receptor regions helps develop emission control strategies that alleviate the impact on ecosystem and human health. In light of the maximum available control technology (MACT) rules proposed by U.S. Environmental Protection Agency (EPA) and the ongoing intergovernmental negotiation coordinated by United Nations Environmental Programme (UNEP) for mercury, the Community Multiscale Air Quality Modeling System (CMAQ-Hg) was applied to estimate the source contribution in six subregions of the contiguous United States (CONUS). The considered source categories include electric generating units (EGU), iron and steel industry (IRST), other industrial point sources excluding EGU and IRST (OIPM), the remaining anthropogenic sources (RA), natural processes (NAT), and out-of-boundary transport (BC). It is found that, on an annual basis, dry deposition accounts for two-thirds of total annual deposition in CONUS (474 Mg yr(-1)), mainly contributed by reactive gaseous mercury (about 60% of total deposition). The contribution from large point sources can be as high as 75% near the emission sources (100 km), indicating that emission reduction may result in direct deposition decrease near the source locations. Out-of-boundary transport contributes from 68% (Northeast) to 91% (West Central) of total deposition. Excluding the contribution from out-of boundary transport, EGU contributes to about 50% of deposition in the Northeast, Southeast, and East Central regions, whereas emissions from natural processes are more important in the Pacific and West Central regions (contributing up to 40% of deposition). This suggests that the implementation of the new EPA MACT standards will significantly benefit only these three regions. Emission speciation is a key factor for local deposition. The source contribution exhibits strong seasonal variation. Deposition is greater in warm seasons due to stronger Hg0 oxidation. However, the contribution from anthropogenic sources is smaller in warm seasons because of larger emissions from natural processes and stronger vertical mixing that facilitates transport.

Metal capture experiments were performed in a 76 mm (3″) ID fluidized-bed combustor with limestone, sand and alumina serving as both the fluidized medium and metal capture sorbents. Wood pellets spiked with metal solutions were used to simulate the metal-containing combustible fuel. The tested metals were nitrate and chloride species of lead and cadmium. The experimental parameters included metal species and concentration, sorbent type and size, combustor temperature, air flow rate and combustion duration. Experimental results indicated that the technology is highly promising. In-furnace lead capture by limestone was observed to be as high as 95%. The capture efficiency, however, varied with experimental parameters and chemical additives. Most of the captured metals were observed to be TCLP nonleachable.

The United States Environmental Protection Agency (U.S.EPA) has reported that metals can account for almost all of the identified risks from a thermal treatment process. Fundamental research leading to better understanding of their behavior and improved control of their emissions is greatly needed. This paper reports our studies on metal volatilization and separation during incineration. Metal volatilization studies were carried out in two separate experiments. In the first experiment, the dynamic volatilization characteristics of various metals during the combustion of metal-containing wood pellets were investigated in a high-temperature electric furnace. In addition to uncontrolled volatilization, the potential of employing chemical additives to bind metals and prevent them from volatilizing during combustion was also investigated. The second experiment involved the investigation of metal volatilization characteristics during the thermal treatment of metal-contaminated clay in a fluidized bed unit. The metal species tested in both experiments were compounds of lead and cadmium. Metal capture/separation studies were also carried out in two separate experiments. The first involved the use of sorbents in the combustion chamber to capture metals during the fluidized bed incineration of metal-containing wood pellets. The second experiments, however, employed sorbents to absorb metal vapors in a fluidized-bed waste-heat boiler. The objective of both the experiments is to characterize the metal absorption efficiency associated with the processes.

In conventional quality control methods, where consequences are analyzed to determine actions, often provide the solution too late. Even if the process is initiated as soon as problems occur, small environmental changes might force the entire process to be redesigned. Without the ability to deal promptly with such situations, it is frequently too late to do anything. The Process Decision Program Chart (PDPC) is one of the methods used to solve problems in Operations Research during the design stage in Research and Development. PDPC is an effective means of moving promptly toward one's goal at the very stage of the process where we encounter an unexpected problem and define the solution process when we are dealing with problems that have more than one possible outcome. In this paper, we discuss the application of PDPC for Total Quality Control in the area of process planning. Object-Oriented Programming Technique is proposed in order to implement this method effectively.

In this paper, Object-Oriented Databases are proposed as being a new tool for Quality Function Deployment (QFD) and Taguchi Methods. Quality Function Deployment can help identify key product or process concerns with respect to customer requirements. Taguchi Methods, such as using Design of Experiments (DOE), can help identify what product or process relationships truly exist, their relative strengths and the nature of the relationship. In order to implement these two powerful quality control techniques for assuring that customer requirements are consistently met, a well organized information is required. Object-Oriented Databases are able to store, organize and manipulate both, the customer requirements and the product information for the performance of QFD and DOE.

The objective of this study is to use sediment settling data to analyze and predict performance of 15 Confined Placement Areas (CPAs) as part of the 50 year dredged material management plan. Two modules of the Automated Dredging and Disposal Alternatives Management System (ADDAMS), DYECON and SETTLE, were used to design CPAs. Design variables for CPAs include dike height, weir length, surface area, flow path length and effluent total suspended solids (TSS) concentration requirements. After sensitivity analyses of design parameters were performed, design curves were developed and presented as formatted graphs showing the relationship among maximum dredged volume, dike height and effluent TSS concentration for all 15 CPAs. It was found that the number of hours of dredging per day and the re-suspension factor could result in sharp changes in projected effluent TSS concentrations. The influence of these design variables was not well understood by operation engineers and SETTLE users before.

A goal programming model was developed which attempts to achieve a number of objectives normally desired in the banking industry. The model incorporates objectives relative to providing sufficient liquidity, minimizing risk, maintaining adequate levels of capital, minimizing the cost of capital, maximizing profit and providing reasonable dividends. The constraints on the model relate to pledged assets required by the government, required reserves and limits on certain balance sheet items. Model validation is accomplished by utilizing data obtained from a commercial bank. The data includes financial information for 1982–1984. The 1982 actual data is utilized by the model to project 1983 and 1984 conditions. These projected numbers are then compared with actual financial data to compare the model's performance with results achieved by management without the use of the model. Total underachievement of several goals in banking is minimized within the limits of the actual decision environment.

Two predictive models for estimating the computer execution time required by two network flow based algorithms to solve the Time-Cost Trade-Off problem are presented. Fulkerson's Longest Path Algorithm and Phillips and Dessouky's Cut Search Algorithm are used. A comparison of performance of these two algorithms for different network structures is provided. The two algorithms are coded into Fortran programs, and it is found that the solution time increases linearly with the number of nodes and several other parameters. In addition, the Longest Path Algorithm is found to be computationally more efficient than the Cut Search Algorithm in solving the Time-Cost Trade-Off problem.

The paper presents some results of a research finalized to optimize the dynamic performances of a machining centre for HSM, in a virtual design approach. CNC software and the feedback chains to/from machine tool actuators and transducers are nowadays highly sophisticated. It is necessary to analyse, model and simulate the real complex algorithms for motion control, in order to define a true, realistic model of the functions of the CNC and interfaced digital modules mastering the machine tool dynamics. An in-depth study of their architecture and functions led to the development of a simulation module now operating inside the whole Mechatronic model of the machine tool. The analyses performed, the bottlenecks encountered and some simulation results, together with their experimental validation, are presented and discussed.

The article emphasizes clinical and prognostic significance of non-linear measures of the heart rate variability, applied on the group of patients with coronary heart disease (CHD) and age-matched healthy control group. Three different methods were applied: Hurst exponent (H), Detrended Fluctuation Analysis (DFA) and approximate entropy (ApEn). Hurst exponent of the R-R series was determined by the range rescaled analysis technique. DFA was used to quantify fractal long-range-correlation properties of heart rate variability. Approximate entropy measures the unpredictability of fluctuations in a time series. It was found that the short-term fractal scaling exponent (α 1) is significantly lower in patients with CHD (1.07 &plusmn ; ; ; 0.04 vs. 1.34 &plusmn ; ; ; 0.07 ; p < 0.001). The patients with CHD had lower Hurst exponent in each program of exercise test separately, as well as aproximate entropy than healthy control group (P < 0.001).

There are few important reasons for introduction of intelligent mobile agents model in telecommunications. These are, but not limited to: transport platform development which provides us with a high level of flexibility during communication process and &raquo ; ; softwaresation&laquo ; ; of telecommunications. Introduction of mobile agents generates search for appropriate formal system to develop their efficient formal specification. Here, we present formal model for specification of mobile agents in telecommunication network management. Network management can be perceived as process of decomposite problem solving where each network problem is decomposed to smaller ones called primary problems. Primary problems are then objects of problem solvers. Two aspects of formal specification of network mangement system based on mobile agents are considered here: static and dynamic.