An investigation of multiphase CFD modelling of a lateral sloshing tank

A near-resonant, sway-induced sloshing flow in a rectangular tank is used to compare a homogeneous and inhomogeneous multiphase approach for fluid density and viscosity in a commercial CFD code. Dimensional analysis of the relative motion between the phases suggests the application of an inhomogeneous multiphase model whereas previous published work has used the computationally cheaper homogeneous (or average property) approach. The comparison between the computational and experimental results shows that the homogeneous model tends to underestimate the experimental peak pressures by up to 50%. The inhomogeneous multiphase model gives good agreement with the experimental pressure data. Examination of the relative velocity at the fluid interface confirms that the inhomogeneous model is the appropriate model to use for the simulation of a violent sloshing flow.     

Robust Cardiac Function Assessment in 4D PC‐MRI Data of the Aorta and Pulmonary Artery

Four‐dimensional phase‐contrast magnetic resonance imaging (4D PC‐MRI) allows the non‐invasive acquisition of time‐resolved, 3D blood flow information. Stroke volumes (SVs) and regurgitation fractions (RFs) are two of the main measures to assess the cardiac function and severity of valvular pathologies. The flow rates in forward and backward direction through a plane above the aortic or pulmonary valve are required for their quantification. Unfortunately, the calculations are highly sensitive towards the plane's angulation since orthogonally passing flow is considered. This often leads to physiologically implausible results. In this work, a robust quantification method is introduced to overcome this problem. Collaborating radiologists and cardiologists were carefully observed while estimating SVs and RFs in various healthy volunteer and patient 4D PC‐MRI data sets with conventional quantification methods, that is, using a single plane above the valve that is freely movable along the centerline. By default it is aligned perpendicular to the vessel's centerline, but free angulation (rotation) is possible. This facilitated the automation of their approach which, in turn, allows to derive statistical information about the plane angulation sensitivity. Moreover, the experts expect a continuous decrease of the blood flow volume along the vessel course. Conventional methods are often unable to produce this behaviour. Thus, we present a procedure to fit a monotonous function that ensures such physiologically plausible results. In addition, this technique was adapted for the usage in branching vessels such as the pulmonary artery. The performed informal evaluation shows the capability of our method to support diagnosis; a parameter evaluation confirms the robustness. Vortex flow was identified as one of the main causes for quantification uncertainties.     

Active learning for extended finite state machines

We present a black-box active learning algorithm for inferring extended finite state machines (EFSM)s by dynamic black-box analysis. EFSMs can be used to model both data flow and control behavior of software and hardware components. Different dialects of EFSMs are widely used in tools for model-based software development, verification, and testing. Our algorithm infers a class of EFSMs called register automata. Register automata have a finite control structure, extended with variables (registers), assignments, and guards. Our algorithm is parameterized on a particular theory, i.e., a set of operations and tests on the data domain that can be used in guards.Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We also show that, under these conditions, our framework induces a generalization of the classical Nerode equivalence and canonical automata construction to the symbolic setting. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.     

Life Cycle of Smart Contracts in Blockchain Ecosystems

This paper discusses the life cycle of decentralized smart contracts, i.e. digital and executable representations of rights and obligations in a multi-party environment. The life cycle relies on blockchain technology, i.e. a distributed digital ledger, to ensure proper implementation and integrity of the smart contracts. The life cycle consists of four subsequent phases: Creation, freezing, execution, and finalization. For each phase actors and technological services are identified and explained in detail. With the life cycle at hand, risks and limitations of smart contracts and the underlying blockchain technology are briefly discussed.     

On improving the efficiency of tensor voting

This paper proposes two alternative formulations to reduce the high computational complexity of tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. The first scheme consists of numerical approximations of the votes, which have been derived from an in-depth analysis of the plate and ball voting processes. The second scheme simplifies the formulation while keeping the same perceptual meaning of the original tensor voting: The stick tensor voting and the stick component of the plate tensor voting must reinforce surfaceness, the plate components of both the plate and ball tensor voting must boost curveness, whereas junctionness must be strengthened by the ball component of the ball tensor voting. Two new parameters have been proposed for the second formulation in order to control the potentially conflictive influence of the stick component of the plate vote and the ball component of the ball vote. Results show that the proposed formulations can be used in applications where efficiency is an issue since they have a complexity of order O(1). Moreover, the second proposed formulation has been shown to be more appropriate than the original tensor voting for estimating saliencies by appropriately setting the two new parameters.     

Symbolic Cache Analysis for Real-Time Systems

Caches impose a major problem for predicting execution times of real-time systems since the cache behavior depends on the history of previous memory references. Too pessimistic assumptions on cache hits can obtain worst-case execution time estimates that are prohibitive for real-time systems. This paper presents a novel approach for deriving a highly accurate analytical cache hit function for C-programs at compile-time based on the assumption that no external cache interference (e.g. process dispatching or DMA activity) occurs. First, a symbolic tracefile of an instrumented C-program is generated based on symbolic evaluation, which is a static technique to determine the dynamic behavior of programs. All memory references of a program are described by symbolic expressions and recurrences and stored in chronological order in the symbolic tracefile. Second, a cache hit function for several cache architectures is computed based on a cache evaluation technique. Our approach goes beyond previous work by precisely modelling program control flow and program unknowns, modelling large classes of cache architectures, and providing very accurate cache hit predictions. Examples for the SPARC architecture are used to illustrate the accuracy and effectiveness of our symbolic cache prediction.     

Case study on the implementation of deammonification for the process water treatment of Munich WWTPs

The two-staged WWTP 'Gut Grosslappen' has a capacity of 2 mio. PE. It comprises a pre-denitrification in the first stage using recirculation from the nitrifying second stage. A residual post-denitrification in a downstream sand filter is required in order to achieve the effluent standards. Presently the process water from sludge digestion is treated separately by nitrification/denitrification. Due to necessary reconstruction of the biological stages, the process water treatment was included in the future overall process concept of the WWTP. A case study was conducted comparing the processes nitritation/denitrititation and deammonification with nitrification/denitrification including their effect on the operational costs of the planned main flow treatment. Besides the different operating costs the investment costs required for the process water treatment played a significant role. Six cases for the process water treatment were compared. As a result, in Munich deammonification can only be recommended for long-term future developments, due to the high investment costs, compared with the nitritation/denitritation alternative realizable in existing tanks. The savings concerning aeration, sludge disposal and chemicals were not sufficient to compensate for the additional investment costs. Due to the specific circumstances in Munich, for the time being the use of existing tanks for nitritation/denitritation proved to be most economical.     

Evaluation of the origin of nitrate influencing the Klju? groundwater source, Serbia

This paper describes the use of the dual isotope method involving δ(15)N and δ(18)O measurements of dissolved nitrates to assess the origin and fate of groundwater nitrate at the Klju? groundwater source, Serbia. A sampling campaign was conducted in September 2007 during flow conditions obtaining groundwater from observation wells and river water fed by a shallow aquifer hosted in alluvial (sandy-gravel) sediments. Nitrate isotope ratios ranged from +5.3 to +16.9‰ and δ(18)O(NO(3)) values varied from -2.3 to +5.0‰. Two major contamination sources were identified with isotopic compositions characteristic for nitrate derived from nitrification of soil organic nitrogen (+5.3 to +7.8‰ for δ(15)N) resulting in nitrate concentrations of 33.6 and 78.8 mg/L and nitrate derived from animal wastes or human sewage, e.g. via septic systems, yielding δ(15)N values of +9.9 to +11.9‰ and elevated nitrate concentrations of 31.2-245.8 mg/L. The occurrence of nitrification and denitrification was also revealed based on concentration and isotope data for dissolved nitrate.