Application of active coke in processes of SO2- and NOx-removal from flue gases

In the field of flue gas cleaning, active coke plays an important role as adsorbant and catalyst. In the temperature range usually prevailing downstream of the air preheater of power plants, SO₂ becomes adsorbed on carbonaceous materials and in a consecutive step is catalysed by the carbonaceous surface and converted to sulphuric acid. The quality demands for a cyclic regenerative process for SO₂ removal are fulfilled by the active coke which is used in the BF-process. The same active coke catalyses the reaction of NO with NH₃ to N₂ and steam. This is the basis for processes for simultaneous SO₂ and NO_x removal. By the addition of ammonia the SO₂ removal by active coke is improved. Two processes are described and results from the laboratory and from the demonstration plant for the BF-process are presented. These show that SO₂ removal efficiences exceed 95% and NO conversions of > 80% can be realized without problems. The cost of the processes using active coke with ammonia addition are comparable with those of wet flue gas desulphurization processes without any additional equipment should NO have to be removed.     

Rheology of cementitious paste with silica fume or limestone

The rheological behaviour of cementitious pastes where cement has increasingly been replaced by densified silica fume (SF), untreated SF or limestone has been studied. The effect of SF on the flow resistance, taken as the area under the flow curve, was found to depend on the dispersing ability of the plasticizer as illustrated by pastes with naphtalene sulphonate-formaldehyde condensate (SNF) and polyether grafted polyacrylate (PA).The gel strengths increased with increasing SF replacement of cement independently of plasticizer type. The cementitious gel strength was, however, depending on the type of SF since pastes with densified SF developed lower gel strengths than pastes with untreated SF. This phenomenon was attributed to agglomerates in the densified SF which remained unbroken by the mixing and measurement sequence.Both flow resistance and gel strength decreased with increasing limestone replacement. Thus, silica fume may have an advantage over limestone filler as stabilizing agent for self-compacting concrete preventing segregation upon standing and reduced form pressure due to a more rapid gel formation.     

A Python extension for the massively parallel multiphysics simulation framework waLBerla

We present a Python extension to the massively parallel HPC simulation toolkit waLBerla. waLBerla is a framework for stencil based algorithms operating on block-structured grids, with the main application field being fluid simulations in complex geometries using the lattice Boltzmann method. Careful performance engineering results in excellent node performance and good scalability to over 400,000 cores. To increase the usability and flexibility of the framework, a Python interface was developed. Python extensions are used at all stages of the simulation pipeline: they simplify and automate scenario setup, evaluation, and plotting. We show how our Python interface outperforms the existing text-file-based configuration mechanism, providing features like automatic nondimensionalization of physical quantities and handling of complex parameter dependencies. Furthermore, Python is used to process and evaluate results while the simulation is running, leading to smaller output files and the possibility to adjust parameters dependent on the current simulation state. C++ data structures are exported such that a seamless interfacing to other numerical Python libraries is possible. The expressive power of Python and the performance of C++ make development of efficient code with low time effort possible.     

Clinical applications of capillary electrophoresis coupled to mass spectrometry in biomarker discovery: Focus on bladder cancer

A major requirement in the application of proteins as clinical biomarkers is that they provide a highly sensitive and specific result in disease assessment. Since single biomarkers are generally of limited accuracy, a group or panel of well-characterized biomarkers appears appropriate, providing a more robust and sensitive MS-based analytical platform. CE coupled to MS has been successfully used in biomarker discovery and application, as it enables the selective detection of peptides and small proteins, combining the high separation capacity of CE with the advanced sensitivity of MS. CE-MS allows the characterization of highly complex samples (such as urine, plasma, and other biofluids) in a consistent and reproducible way. It has a range of applications, many focusing especially in studies on urinary peptide biomarkers in kidney and cardiovascular diseases. Another major field of interest has been malignancy of the genitourinary system. In the first part of this review, we cover technical aspects and performance characteristics of CE-MS, with special focus on the requirements for biomarker discovery and clinical application. In the second part, we review the potential and development of CE-MS in the management of genitourinary cancers, especially bladder cancer. CE-MS has been employed in several studies aimed at discovering biomarkers for bladder cancer that may be useful in diagnosis, monitoring for recurrence, and prediction of the risk for the muscle-invasive stage. In the last part of the review, we discuss current challenges and provide an outlook for ongoing and possible future developments.     

Realization strategies of dedicated path protection: A bandwidth cost perspective

Communication networks have to provide a high level of availability and instantaneous recovery after failures in order to ensure sufficient survivability for mission-critical services. Currently, dedicated path protection (or 1 + 1) is implemented in backbone networks to provide the necessary resilience and instantaneous recovery against single link failures with remarkable simplicity. However, in order to satisfy strict availability requirements, connections also have to be resilient against Shared Risk Link Group (SRLG) failures. In addition, switching matrix reconfigurations have to be avoided after a failure in order to guarantee instantaneous recovery. For this purpose, there are several possible realization strategies improving the characteristics of traditional 1 + 1 path protection by lowering reserved bandwidth while conserving all its favorable properties. These methods either utilize diversity coding, network coding, or generalize the disjoint-path constraint of 1 + 1.In this paper, we consider the cost aspect of the traditional and the alternative 1 + 1 realization strategies. We evaluate the bandwidth cost of different schemes both analytically and empirically in realistic network topologies. As the more complex realizations lead to NP-complete problems even in the single link failure case, we propose both Integer Linear Programming (ILP) based optimal methods, as well as heuristic and meta-heuristic approaches to solve them. Our findings provide a tool and guidelines for service providers for selecting the path protection method with the lowest bandwidth cost for their network corresponding to a given level of reliability.     

Increasing the usefulness of additive spline models by knot removal

Modern techniques for fitting generalized additive models mostly rely on basis expansions of covariates using a large number of basis functions and penalized estimation of parameters. For example, a mixed model approach is used to fit a model for children’s lung function that allows for non-linear influence of several covariates available in a substantial data set. While the resulting model is expected to have good prediction performance, its handling beyond simple visual presentation is problematic. It is shown how the number basis functions of the underlying B-spline representation can be reduced by knot removal techniques without refitting, while preserving the shape of the fitted functions. The condition for exact knot removal is extended towards approximate knot removal by incorporating the covariance matrix of the initial parameter estimates, resulting in considerable simplification of the model. Covariance matrices for the transformed parameter estimates are provided. It is demonstrated that enforcing the knot removal condition during estimation leads to the difference penalties employed in the P-spline approach for estimation of B-spline coefficients, and therefore provides a further justification for this type of penalty. A final transform to a truncated power basis provides a simple equation for the model. This increases transportability, while retaining properties of the initial fit such as good prediction performance.     

A knowledge-based approach to manage information systems interoperability

Interoperability is a key property of enterprise applications, which is hard to achieve due to the large number of interoperating components and semantic heterogeneity. The inherent complexity of interoperability problems implies that there exists no silver bullet to solve them. Rather, the knowledge about how to solve wicked interoperability problems is hidden in the application cases that expose those problems. The paper addresses the question of how to organise and use method knowledge to resolve interoperability problems. We propose the structure of a knowledge-based system that can deliver situation-specific solutions, called method chunks. Situational Method Engineering promotes modularisation and formalisation of method knowledge in the form of reusable method chunks, which can be combined to compose a situation-specific method. The method chunks are stored in a method chunk repository. In order to cater for management and retrieval, we introduce an Interoperability Classification Framework, which is used to classify and tag method chunks and to assess the project situation in which they are to be used. The classification framework incorporates technical as well as business and organisational aspects of interoperability. This is an important feature as interoperability problems typically are multifaceted spanning multiple aspects. We have applied the approach to analyse an industry case from the insurance sector to identify and classify a set of method chunks.     

A case study comparing defect profiles of a reused framework and of applications reusing it

The benefits of software reuse have been studied for many years. Several previous studies have observed that reused software has a lower defect density than newly built software. However, few studies have investigated empirically the reasons for this phenomenon. To date, we have only the common sense observation that as software is reused over time, the fixed defects will accumulate and will result in high-quality software. This paper reports on an industrial case study in a large Norwegian Oil and Gas company, involving a reused Java class framework and two applications that use that framework. We analyzed all trouble reports from the use of the framework and the applications according to the Orthogonal Defect Classification (ODC), followed by a qualitative Root Cause Analysis (RCA). The results reveal that the framework has a much lower defect density in total than one application and a slightly higher defect density than the other. In addition, the defect densities of the most severe defects of the reused framework are similar to those of the applications that are reusing it. The results of the ODC and RCA analyses reveal that systematic reuse (i.e. clearly defined and stable requirements, better design, hesitance to change, and solid testing) lead to lower defect densities of the functional-type defects in the reused framework than in applications that are reusing it. However, the different “nature” of the framework and the applications (e.g. interaction with other software, number and complexity of business logic, and functionality of the software) may confound the causal relationship between systematic reuse and the lower defect density of the reused software. Using the results of the study as a basis, we present an improved overall cause–effect model between systematic reuse and lower defect density that will facilitate further studies and implementations of software reuse.

Evidence for Glass–glass Interfaces in a Columnar Cu–Zr Nanoglass

Comprehensive analyses of the atomic structure using advanced analytical transmission electron microscopy-based methods combined with atom probe tomography confirm the presence of distinct glass–glass interfaces in a columnar Cu-Zr nanoglass synthesized by magnetron sputtering. These analyses provide first-time in-depth characterization of sputtered film nanoglasses and indicate that glass–glass interfaces indeed present an amorphous phase with reduced mass density as compared to the neighboring amorphous regions. Moreover, dedicated analyses of the diffusion kinetics by time-of-flight secondary ion mass spectroscopy (ToF SIMS) prove significantly enhanced diffusivity, suggesting fast transport along the low density glass–glass interfaces. The present results further indicate that sputter deposition is a feasible technique for reliable production of nanoglasses and that some of the concepts proposed for this new class of glassy materials are applicable.