Engineering microfluidic papers: effect of fiber source and paper sheet properties on capillary-driven fluid flow

In the present study, we introduce a novel approach to control and modulate fluid transport inside microfluidic papers using lab-engineered paper sheets. Lab-sheets consisting of different fiber sources (eucalyptus sulfate and cotton linters pulp) and varying porosities were designed and further modified with small millimeter-scaled channels using hydrophobic barriers consisting of fiber-attached, hydrophobic polymers. The capillary-driven transport of an aqueous solution was monitored visually, and the influence of parameters such as fiber source, paper grammage, and channel width on the flow rates through the channel was investigated. The experimental results were compared with those obtained with commercially available filter papers. Our findings suggest that accurate control of fluid transport processes with standard filter papers is complex. Additionally, if the channel width is smaller than the mean fiber length, flow rates become dependent on the geometric parameters of the channel because of the formation of dead-end pores at the hydrophobic barriers. Finally, control of the paper sheets porosity, by varying the fiber density of the lab-made paper, affords the fabrication of chemically identical sheets whereby capillary flow is largely influenced and can be modulated accordingly by simple papermaking processes.     

An architecture modeling framework for probabilistic prediction

In the design phase of business and IT system development, it is desirable to predict the properties of the system-to-be. A number of formalisms to assess qualities such as performance, reliability and security have therefore previously been proposed. However, existing prediction systems do not allow the modeler to express uncertainty with respect to the design of the considered system. Yet, in contemporary business, the high rate of change in the environment leads to uncertainties about present and future characteristics of the system, so significant that ignoring them becomes problematic. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (P²AMF), capable of advanced and probabilistically sound reasoning about business and IT architecture models, given in the form of Unified Modeling Language class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, P²AMF adds a probabilistic inference mechanism. The paper introduces P²AMF, describes its use for system property prediction and assessment and proposes an algorithm for probabilistic inference.     

Fluidized Bed Air Drying: Experimental Study and Model Development

The presented study describes the processes and mechanisms of batch fluidized bed drying. The influencing factors of hot air drying are theoretically and experimentally examined, in order to present the relations between temperature and humidity profiles and all other drying parameters. A physical model is presented to facilitate the calculation of the drying processes under defined conditions. Three succeeding drying stages are therefore modeled. Mass and energy balances including all components taking part in the process are formulated. The model clarities the drying process under the assumption of pure heat transfer mechanisms. It does not contain adaptive parameters and takes into account an inactive bypass fraction of the fluidization and drying medium. The evaluation of the model was successful for two fluidized bed plants with nominal widths of 100 mm and 400 mm. The experiments showed sufficient accuracy and transferability of the model to equipment of application‐oriented dimensions.     

Detailed Molecular Structure Modeling – A Path Forward to Designing Application Properties of ldPE

Summary: This paper describes a step on the ambitious aim to “design” application properties of ldPE by first simulating the detailed molecular structure of a high‐pressure tubular reactor product. The reactor of a certain configuration produces under well‐defined operating conditions. The next step is to correlate the structure with the application properties. Finally, the sequence will be reversed in order to deduce the operating conditions, which lead to the desired product quality. Two‐dimensional distributions, in molecular weight and branching frequency, as well a two compartment models with a core and a shell stream were simulated and compared with experimental results. Therefore, CFD simulations were carried out to discretize the reaction medium. Samples were taken from both pilot and commercial plants. The TREF‐SEC analytical method was successfully applied in order to measure the microscopic structure of the material. The tremendous numerical problems were solved with the help of the software PREDICI .

Detailed MWD for a pilot scale reactor product.     

An enterprise architecture framework for multi-attribute information systems analysis

Enterprise architecture is a model-based IT and business management discipline. Enterprise architecture analysis concerns using enterprise architecture models for analysis of selected properties to provide decision support. This paper presents a framework based on the ArchiMate metamodel for the assessment of four properties, viz., application usage, system availability, service response time and data accuracy. The framework integrates four existing metamodels into one and implements these in a tool for enterprise architecture analysis. The paper presents the overall metamodel and four viewpoints, one for each property. The underlying theory and formalization of the four viewpoints is presented. In addition to the tool implementation, a running example as well as guidelines for usage makes the viewpoints easily applicable.     

Automatic data collection for enterprise architecture models

Enterprise Architecture (EA) is an approach used to provide decision support based on organization-wide models. The creation of such models is, however, cumbersome as multiple aspects of an organization need to be considered, making manual efforts time-consuming, and error prone. Thus, the EA approach would be significantly more promising if the data used when creating the models could be collected automatically—a topic not yet properly addressed by either academia or industry. This paper proposes network scanning for automatic data collection and uses an existing software tool for generating EA models (ArchiMate is employed as an example) based on the IT infrastructure of enterprises. While some manual effort is required to make the models fully useful to many practical scenarios (e.g., to detail the actual services provided by IT components), empirical results show that the methodology is accurate and (in its default state) require little effort to carry out.     

Optimizing wheel profiles and suspensions for railway vehicles operating on specific lines to reduce wheel wear: a case study

Multibody System Dynamics - The selection of a wheel profile is a topic of great interest as it can affect running performances and wheel wear, which needs to be determined based on the actual...     

A New Research Infrastructure for Investigating Flow Hydraulics and Process Equipment at Critical Fluid Properties

An optimized equipment design for natural gas processing and liquefaction plants becomes increasingly difficult with changing process conditions: Particularly low values of surface tension create rising challenges on the design of phase separators and column internals. The TERESA test rig at HZDR was designed to allow the investigation of multiphase thermohydraulics and phase separator performance under critical fluid properties in industrial dimensions. A versatile pipe test section is available in DN200 and equipment internals may be tested in a sectional DN300/DN500 test separator. The applied test fluid shows a high vapor-liquid density difference between 1470 and 940 kg m⁻³, viscosity as low as 0.12 mm²s⁻¹, and surface tension down to 1.3 mN m⁻¹. Volumetric liquid and vapor flow rates may be varied up to 9 and 530 m³h⁻¹ in the test rig, respectively.     

Impact of processing conditions and sizing on the thermomechanical and morphological properties of polypropylene/carbon fiber composites fabricated by material extrusion additive manufacturing

For the 3D printed composites, fiber alignment is affected by the direction of melt-flow during extrusion of filaments and subsequently through the printing nozzle. The resulting fibers orientation and the fiber-matrix compatibility have a direct correlation with mechanical properties. This study investigates the impact of processing conditions on the state of the carbon fiber types and their orientation on the mechanical properties of 3D-printed composites. Short and long carbon fibers were used as starting reinforcing materials, and the state of fibers at the beginning and on the printed parts were evaluated. Strong anisotropy in terms of mechanical properties (flexural and impact properties) was observed for the samples printed with different printing orientations. Interestingly, the number of voids in the printed composites was found to be correlated with the fiber types. The present work provides a step towards the optimization of tailored composite properties by additive manufacturing.