Sodium sulfate: Deposition and dissolution of silica

The hot-corrosion process for SiO₂-protected materials involves deposition of Na₂SO₄ and dissolution of the protective SiO₂ scale. Dew points for Na ₂SO₄ deposition are calculated as a function of pressure, sodium content, and sulfur content. Expected dissolution regimes for SiO₂ are calculated as a function of Na₂SO₄ basicity, hence generated by fuels with 0.5% and 0.05% S. Controlled-condition burner-rig tests on quartz verify some of these predicted dissolution regimes. However, the basicity of Na₂SO₄ is not always a simple function of (Na₂O) show that carbon creates basic conditions in Na₂SO₄, which explains the extensive corrosion of SiO₂-protected materials containing carbon, such as SiC.     

Runout effects in milling: Surface finish, surface location error, and stability

This paper investigates the effect of milling cutter teeth runout on surface topography, surface location error, and stability in end milling. Runout remains an important issue in machining because commercially-available cutter bodies often exhibit significant variation in the teeth/insert radial locations; therefore, the chip load on the individual cutting teeth varies periodically. This varying chip load influences the machining process and can lead to premature failure of the cutting edges. The effect of runout on cutting force and surface finish for proportional and non-proportional tooth spacing is isolated here by completing experiments on a precision milling machine with 0.1 μm positioning repeatability and 0.02 μm spindle error motion. Experimental tests are completed with different amounts of radial runout and the results are compared with a comprehensive time-domain simulation. After verification, the simulation is used to explore the relationships between runout, surface finish, stability, and surface location error. A new instability that occurs when harmonics of the runout frequency coincide with the dominant system natural frequency is identified.     

Solving linear generalized Nash equilibrium problems numerically

This paper considers the numerical solution of linear generalized Nash equilibrium problems (LGNEPs). Since many methods for nonlinear problems require the nonsingularity of some second-order derivative, standard convergence conditions are not satisfied in our linear case. We provide new convergence criteria for a potential reduction algorithm (PRA) that allow its application to LGNEPs. Furthermore, we discuss a projected subgradient method (PSM) and a penalty method that exploit some known Nikaido–Isoda function-based constrained and unconstrained optimization reformulations of the LGNEP. Moreover, it is shown that normalized Nash equilibria of an LGNEP can be obtained by solving a single linear program. All proposed algorithms are tested on randomly generated instances of economic market models that are introduced and analysed in this paper and that lead to LGNEPs with shared and with non-shared constraints. It is shown that these problems have some favourable properties that can be exploited to obtain their solutions. With the PRA and in particular with the PSM we are able to compute solutions with satisfying precision even for problems with up 10,000 variables.     

Increased biogas production in a wastewater treatment plant by anaerobic co-digestion of fruit and vegetable waste and sewer sludge - a full scale study

Anaerobic digestion is a well established technology for the reduction of organic matter and stabilization of wastewater. Biogas, a mixture of methane and carbon dioxide, is produced as a useful by-product of the process. Current solid waste management at the city of Prince George is focused on disposal of waste and not on energy recovery. Co-digestion of fresh fruit and vegetable waste with sewer sludge can improve biogas yield by increasing the load of biodegradable material. A six week full-scale project co-digesting almost 15,000 kg of supermarket waste was completed. Average daily biogas production was found to be significantly higher than in previous years. Digester operation remained stable over the course of the study as indicated by the consistently low volatile acids-to-alkalinity ratio. Undigested organic material was visible in centrifuged sludge suggesting that the waste should have been added to the primary digester to prevent short circuiting and to increase the hydraulic retention time of the freshly added waste.     

Application of the Soil and Water Assessment Tool for six watersheds of Lake Erie: Model parameterization and calibration

The Soil and Water Assessment Tool (SWAT), a physically-based watershed-scale model, holds promise as a means to predict tributary sediment and nutrient loads to the Laurentian Great Lakes. In the present study, model performance is compared across six watersheds draining into Lake Erie to determine the applicability of SWAT to watersheds of differing characteristics. After initial model parameterization, the Huron, Raisin, Maumee, Sandusky, Cuyahoga, and Grand SWAT models were calibrated (1998-2001) and confirmed, or validated (2002-2005), individually for stream water discharge, sediment loads, and nutrient loads (total P, soluble reactive P, total N, and nitrate) based on available datasets. SWAT effectively predicted hydrology and sediments across a range of watershed characteristics. SWAT estimation of nutrient loads was weaker although still satisfactory at least two-thirds of the time across all nutrient parameters and watersheds. SWAT model performance was most satisfactory in agricultural and forested watersheds, and was less so in urbanized settings. Model performance was influenced by the availability of observational data with high sampling frequency and long duration for calibration and confirmation evaluation. In some instances, it appeared that parameter adjustments that improved calibration of hydrology negatively affected subsequent sediment and nutrient calibration, suggesting trade-offs in calibrating for hydrologic vs. water quality model performance. Despite these considerations, SWAT accurately predicted average stream discharge, sediment loads, and nutrient loads for the Raisin, Maumee, Sandusky, and Grand watersheds such that future use of these SWAT models for various scenario testing is reasonable and warranted.     

Relationships Between Satellite Observed Lit Area and Water Footprints

Global water resources are vulnerable to depletion due to the increasing demand of an ever-increasing human population. A country’s water footprint is a measure of the total volume of water needed to produce the goods and services consumed by the country, including water originating beyond its own borders. The water footprint can be a critical indicator of global water resource use, but its practical application is hindered by a lack of comparable data across national boundaries. The purpose of this article is to test the applicability of the nighttime imagery products produced by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) for the assessment of the global water footprint. To accomplish this purpose, the average areal extent of nighttime lighting (lit area) is calculated from 1997 to 2001. Next, lit area is regressed on the total water footprint for each country, as indicated by the Water Footprint Network (WFN), to estimate that country’s total water footprint using nighttime imagery. Model residuals are analyzed at the national scale to understand the appropriateness of nighttime imagery for assessing water consumption. Results indicate strong positive correlations between lit area and total water footprint (TWF), domestic water withdrawal (DWW), and industrial water consumption (IWC) at the national scale. Overall, the analyses reveal that the rate of agricultural water consumption to total water footprint (AWCR) and population density can affect the precision of estimates when lit area is selected as a proxy to estimate water footprints.     

Development of a new indicator of pollutant loads and its application to the Chesapeake Bay watershed

Pollutant load reductions are often required to restore aquatic ecosystems experiencing eutrophication. Loads can be estimated using watershed models or data from monitoring stations, however data availability can limit the timeliness or comprehensiveness of the load estimates. We developed an approach to address this challenge that used watershed model results to estimate the proportion of annual nonpoint source nitrogen (N), phosphorus (P) and sediment (Sed) loads derived from unmonitored catchments. This proportion was multiplied by the nonpoint portion of United States Geological Survey (USGS) estimated annual river loads to account for annual variation in hydrologic conditions. Total loads were calculated as the sum of measured river loads, reported point sources from unmonitored areas and the estimated nonpoint source loads from unmonitored catchments. We applied this approach to the Chesapeake Bay because of its socio‐economic and ecological importance. Median watershed loads for N, P and Sed were 140, 6.4 and 3030 Mg year^?1, respectively (1990–2004). Nonpoint source loads from the monitored areas constituted the greatest source of N, P and Sed (55, 47 and 74% respectively) to the Bay. The high N, P and Sed yield rates (7.3, 0.38 and 99 kg ha^?1 year^?1, respectively) from nonpoint loads originating from unmonitored areas near the Bay resulted in 25, 32 and 26% (N, P and Sed, respectively) of the Bay's total loads (excluding direct atmospheric deposition, shoreline erosion and oceanic inputs). Disproportionately high loads of P and Seds were associated with years that experienced elevated discharge whereas N loads were directly related to discharge. Error estimates indicated that our methods were most reliable for N (±6%) but reasonable for P (±22%) and provide an effective technique for the timely estimation of pollutant loads from watersheds with unmonitored catchments. Management strategies that decrease N deposition and reduce runoff to control P and Sed transport will effectively reduce pollutant loads. Published in 2010 by John Wiley & Sons, Ltd.     

Finding the number of clusters in ordered dissimilarities

As humans, we have innate faculties that allow us to efficiently segment groups of objects. Computers, to some degree, can be programmed with similar categorical capabilities, which stem from exploratory data analysis. Out of the various subsets of data reasoning, clustering provides insight into the structure and relationships of input samples situated in a number of distributions. To determine these relationships, many clustering methods rely on one or more human inputs; the most important being the number of distributions, c, to seek. This work investigates a technique for estimating the number of clusters from a general type of data called relational data. Several numerical examples are presented to illustrate the effectiveness of the proposed method.     

Real-time simulation of time-of-flight sensors

Today’s time-of-flight (TOF) sensors measure full-range distance information by estimating the elapsed time between emission and receiving of active light in real-time. Such sensors are inexpensive, compact, and they have a high performance, which especially fits real-time applications, e.g. in the fields of automotive, robotics, 3D imaging, and visualization. The simulation of such sensors is an essential building block for hardware design and application development. Therefore, the simulation data must capture the major sensor characteristics.This paper introduces a simulation approach, which is motivated by physics, for the Photonic Mixing Device (PMD) sensor which is a specific type of time-of-flight sensor. Dynamic motion blurring and resolution artifacts such as flying pixels as well as the typical deviation error are prominent effects of real world systems. Flying pixels arise when an area of inhomogeneous depth is covered by a single PMD-pixel whereas the deviation error is based on the anharmonic properties of the optical signal. The modeling of these artifacts is essential for an authentic simulation approach. We present a detailed comparison between a real PMD-device and the simulation data regarding the sensor characteristics.The proposed algorithms are implemented in a hardware accelerated solution which makes use of the programmability of modern Graphics Processing Units (GPUs). This way, an interactive simulation feedback is provided for applications and further data processing. The simulation takes place in real-time and thus all required control mechanisms are accessible in real-time, too.