A laboratory assessment of the impact of brewery wastewater discharge on sulfide and methane production in a sewer

The impact of brewery wastewater discharge on sulfide and methane production in a sewer was assessed. Experiments were carried out on laboratory scale sewer reactors consisting of both an experimental and a control reactor. The control reactor was intermittently fed with real fresh sewage while the experimental reactor was fed with a mixture of brewery and domestic wastewater at two different proportions (10 and 25% v/v). 10% v/v discharge of brewery wastewater increased the H2S and CH4 production rates in the sewer reactor by 40% and 30%, respectively. When the brewery wastewater fraction was increased to 25% v/v, the H2S production rate of the experimental reactor decreased to the level of the control reactor. In contrast, the CH4 production rate maintained at a level that was 30% higher than that in the control reactor. These results indicate that the discharge of brewery wastewater into sewers can give negative impacts in relation to odour and corrosion management of the systems and will increase the greenhouse gas emissions from sewers. The study also reveals that the impact of trade waste on the biological reactions in sewers is complex, and requires careful experimental assessment in each case.     

Licence de brevet et partage du risque: Résultats de simulation

Annals of Telecommunications - Le partage du risque est une des raisons les plus souvent avancées pour expliquer les clauses financières des contrats de licence. Pour autant, aucune...     

Classical and variational multiscale LES of the flow around a circular cylinder on unstructured grids

The effects of numerical viscosity, subgrid scale (SGS) viscosity and grid resolution are investigated in LES and VMS-LES simulations of the flow around a circular cylinder at Re=3900 on unstructured grids. The separation between the largest and the smallest resolved scales in the VMS formulation is obtained through a variational projection operator and finite-volume cell agglomeration. Three different non-dynamic eddy-viscosity SGS models are used both in classical and in VMS-LES. The so-called small-small formulation is used in VMS-LES, i.e. the SGS viscosity is computed as a function of the smallest resolved scales. Two different grid resolutions are considered. It is found that, for each considered SGS model, the amount of SGS viscosity introduced in the VMS-LES formulation is significantly lower than in classical LES. This, together with the fact that in the VMS formulation the SGS viscosity only acts on the smallest resolved scales, has a strong impact on the results. However, a significant sensitivity of the results to the considered SGS model remains also in the VMS-LES formulation. Moreover, passing from classical LES to VMS-LES does not systematically lead to an improvement of the quality of the numerical predictions.     

Measurement of enterprise knowledge by state characterization

Abstract: Enterprise production is becoming more and more knowledge oriented nowadays and knowledge management is playing a key role in making commercial profit and maintaining enterprise competence. Knowledge characterization and measurement are the bases of knowledge management, and this paper aims to develop a method for characterizing and measuring knowledge in a comprehensive and practical way. Knowledge in its static state is modelled as a vector, whose values vary with the situation, and changes in state are modelled as a finite state machine.     

The undirected capacitated arc routing problem with profits

A profit and a demand are associated with each edge of a set of profitable edges of a given graph. A travel time is associated with each edge of the graph. A fleet of capacitated vehicles is given to serve the profitable edges. A maximum duration of the route of each vehicle is also given. The profit of an edge can be collected by one vehicle only that also serves the demand of the edge. The objective of this problem, which is called the undirected capacitated arc routing problem with profits (UCARPP), is to find a set of routes that satisfy the constraints on the duration of the route and on the capacity of the vehicle and maximize the total collected profit. We propose a branch-and-price algorithm and several heuristics. We can solve exactly instances with up to 97 profitable edges. The best heuristics find the optimal solution on most of instances where it is available.     

The strategic value of IT insourcing: An IT-enabled business process perspective

Although research on the business impact of IT outsourcing abounds, little is known about the relative strategic value of IT outsourcing and IT insourcing. Drawing upon the knowledge-based view of the firm, this study postulates that, compared with IT outsourcing, IT insourcing is more effective for developing IT-enabled business processes (IEBP), which subsequently lead to superior firm performance. Our analysis of the data from InformationWeek and Compustat shows that IT insourcing is positively associated with IEBP, while the relationship between IT outsourcing and IEBP is not statistically significant. We also find that IEBP have a significant influence on firm performance. Finally, the effect of IT sourcing mechanisms on IEBP and the effect of IEBP on firm performance are both moderated by the type of innovation related to IEBP. The results suggest that in order to improve their performance firms should consider IT an integral part of their strategic core and should be proactively involved in the internal development of IT resources. We conclude with managerial implications and directions for future research.     

nSPARQL: A navigational language for RDF

Navigational features have been largely recognized as fundamental for graph database query languages. This fact has motivated several authors to propose RDF query languages with navigational capabilities. In this paper, we propose the query language nSPARQL that uses nested regular expressions to navigate RDF data. We study some of the fundamental properties of nSPARQL and nested regular expressions concerning expressiveness and complexity of evaluation. Regarding expressiveness, we show that nSPARQL is expressive enough to answer queries considering the semantics of the RDFS vocabulary by directly traversing the input graph. We also show that nesting is necessary in nSPARQL to obtain this last result, and we study the expressiveness of the combination of nested regular expressions and SPARQL operators. Regarding complexity of evaluation, we prove that given an RDF graph G and a nested regular expression E, this problem can be solved in time O(|G||E|).     

Combined planning and scheduling in a divergent production system with co-production: A case study in the lumber industry

Many research initiatives carried out in production management consider process planning and operations scheduling as two separate and sequential functions. However, in certain contexts, the two functions must be better integrated. This is the case in divergent production systems with co-production (i.e. production of different products at the same time from a single product input) when alternative production processes are available. This paper studies such a context and focuses on the case of drying and finishing operations in a softwood lumber facility. The situation is addressed using a single model that simultaneously performs process planning and scheduling. We evaluate two alternative formulations. The first one is based on mixed integer programming (MIP) and the second on constraint programming (CP). We also propose a search procedure to improve the performance of the CP approach. Both approaches are compared with respect to their capacity to generate good solutions in short computation time.     

Reliability versus performance for critical applications

Applications implemented on critical systems are subject to both safety critical and real-time constraints. Classically, applications are specified as precedence task graphs that must be scheduled onto a given target multiprocessor heterogeneous architecture. We propose a new method for simultaneously optimizing two objectives: the execution time and the reliability of the schedule. The problem is decomposed into two successive steps: a spatial allocation during which the reliability is maximized (randomized algorithm), and a scheduling during which the makespan is minimized (list scheduling algorithm). It allows us to produce several trade-off solutions, among which the user can choose the solution that best fits the application’s requirements. Reliability is increased by replicating adequate tasks onto well chosen processors. Our fault model assumes that processors are fail-silent, that they are subject to transient failures, and that the occurrences of failures follow a constant parameter Poisson law. We assess and validate our method by running extensive simulations on both random graphs and actual application graphs. They show that it is competitive, in terms of makespan, compared to existing reference scheduling methods for heterogeneous processors (HEFT), while providing a better reliability.