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.     

Verformungsverhalten nanostrukturierter HPPMS‐Hartstoffschichten

Elastic‐Plastic Deformation Behavior of Nanostructured HPPMS Hard Coatings Nitride hard coatings deposited via HPPMS (High Power Pulsed Magnetron Sputtering) or HiPIMS (High Power Impulse Magnetron Sputtering) are widely used in tribological applications due to their promising wear and corrosion resistance. During the application, the coated tools or components may be exposed to significant mechanical loads. Therefore, investigations on deformation behavior of the coatings under mechanical loading are of great importance. The objective of the present study was a comprehensive investigation on deformation behavior of nitride hard coatings from the coating system M‐Al‐O‐N (M = Cr, V) using nanoindentation und nanoscratch tests. In this regard, both nanoscale multilayer (nanolaminate) and monolayer coatings were investigated. All the coatings were deposited using HPPMS technology. Contrary to the expectations regarding a brittle behavior of ceramic‐like coatings, the results depict a considerable plastic deformation of the investigated hard coatings. Furthermore, in addition to a high strength, the applied coatings show a high crack resistance under mechanical loading.     

Time dependent voiding mechanisms in polyamide 6 submitted to high stress triaxiality: experimental characterisation and finite element modelling

Double notched round bars made of semi-crystalline polymer polyamide 6 (PA6) were submitted to monotonic tensile and creep tests. The two notches had a root radius of 0.45 mm, which imposes a multiaxial stress state and a state of high triaxiality in the net (minimal) section of the specimens. Tests were carried out until the failure occurred from one of the notches. The other one, unbroken but deformed under steady strain rate or steady load, was inspected using the Synchrotron Radiation Computed Tomography (SRCT) technique. These 3D through thickness inspections allowed the study of microstructural evolution at the peak stress for the monotonic tensile test and at the beginning of the tertiary creep for the creep tests. Cavitation features were assessed with a micrometre resolution within the notched region. Spatial distributions of void volume fraction (\(\mathit{Vf}\)) and void morphology were studied. Voiding mechanisms were similar under steady strain rates and steady loads. The maximum values of \(\mathit{Vf}\) were located between the axis of revolution of the specimens and the notch surface and voids were considered as flat cylinders with a circular basis perpendicular to the loading direction. A model, based on porous plasticity, was used to simulate the mechanical response of this PA6 material under high stress triaxiality. Both macroscopic behaviour (loading curves) and voiding micro-mechanisms (radial distributions of void volume fraction) were accurately predicted using finite element simulations.     

Metamaterial-based graphene thermal emitter

A thermal emitter composed of a frequency-selective surface metamaterial layer and a hexagonal boron nitride-encapsulated graphene filament is demonstrated. The broadband thermal emission of the metamaterial (consisting of ring resonators) was tailored into two discrete bands, and the measured reflection and emission spectra agreed well with the simulation results. The high modulation frequencies that can be obtained in these devices, coupled with their operation in air, confirm their feasibility for use in applications such as gas sensing.

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Distinguishing attacks on stream ciphers based on arrays of pseudo-random words

In numerous modern stream ciphers, the internal state consists of a large array of pseudo-random words, while the output key-stream is a relatively simple function of the state. It has been heuristically shown in several situations [3], [8], [9], [10], [11] and [14] that this structure may lead to distinguishing attacks on the cipher. In this note we present a more rigorous treatment of this structural attack. First, we present a rigorous proof of the main probabilistic claim behind it in the basic cases. We then apply it concretely to the cipher sn3 [12], and demonstrate that the heuristic assumptions of the attack are remarkably precise in more complicated cases.     

Expert-driven genetic algorithms for simulating evaluation functions

In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropriate expert (or mentor), we can evolve a program that is on par with top tournament-playing chess programs, outperforming a two-time World Computer Chess Champion. This performance gain is achieved by evolving a program that mimics the behavior of a superior expert. The resulting evaluation function of the evolved program consists of a much smaller number of parameters than the expert’s. The extended experimental results provided in this paper include a report on our successful participation in the 2008 World Computer Chess Championship. In principle, our expert-driven approach could be used in a wide range of problems for which appropriate experts are available.