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Current society heavily relies on software and software systems. Due to its increasing complexity, the design and operation of software systems are becoming challenging. In the last decades, a great deal of effort has been put into addressing software systems design, development, and maintenance challenges. Empirical evidence shows that one of the most critical success factors when developing software systems is their Software Architecture (SA). A SA describes software systems in terms of software components, their interactions, and critical quality attributes. Among other benefits, SAs improve the overall communication among different stakeholders, are the carriers of significant design decisions, promote the use of different abstraction levels, and allow for the early assessment of the software under development.

Dynamic stiffness is an important characteristic of production machinery, as it contributes to its ability to maintain the position of the tool centre point accurately and precisely under loads. For machine tools, it directly affects the geometric dimensions and surface properties of produced parts. This work presents a measurement procedure for identification of the full translational dynamic stiffness matrix for a single configuration of a machine tool under loaded conditions. The measurement procedure consists of inducing a static baseload with superimposed dynamic loads, which were controlled in magnitude and direction, at the tool centre point of the machine tool. The measurement procedure uses the Loaded Double Ball Bar and measures the dynamic displacement with three Non-Contact Capacitive Probes. The measurement procedure is implemented in a case study on a 5-axis machining centre. Finally, the manuscript concludes with a discussion on the utility value of the translational dynamic stiffness matrix for the design and operation of machine tools as well as the possibility to expand the measurement procedure to capture the dynamic stiffness using quasi-static movements of the machine tool., Part of proceedings: 978-0-9957751-9-0QC 20220330

The aim of this article is to study the hydrodynamic vibration of knife refiners. Such vibration occurs due to hydrodynamic processes during the operation of the mill. A mathematical model is proposed that describes hydrodynamic vibration. The hydrodynamic force that excites the mill oscillations consists of the following main components: Impact of the semi-finished product on the auger blades and headset knives; forward and reverse flow interactions; pressure on the knives of the headset. These forces depend on the design and operation of the mill. The error between theoretical and experimental studies does not exceed 20%. Vibration processes of hydrodynamic origin are mainly determined by the impact of the semi-finished product flow on the auger blades at the entrance to the mill. The proposed research technique can be used in other machines, for example, in centrifugal pumps. © 2020 Published under licence by IOP Publishing Ltd.

This paper conceptually introduces VF-KDO (Virtual Factories with Knowledge-Driven Optimization, a research profile of the University of Skovde, Sweden, which is underway from 2018-2026. The goal of this research profile is to deliver radical innovations in manufacturing research essential to the design and operation of next-generation manufacturing systems. A unique concept proposed in VF-KDO is: knowledge extracted for decision support is achieved through systematically exploring, e.g., using advanced, interactive data analytics techniques on optimal solutions generated via many-objective optimizations on virtual factory models. As the word 'driven' means 'motivated' or 'manipulated', so does KDO have some two-fold meanings: (1) optimizations that aim at generating knowledge, not only mathematically optimal solutions; (2) knowledge-controlled optimizations, instead of some blind/black-box processes. It is this concept of KDO, combining with modular, virtual factory models at different levels, which distinguishes VF-KDO from other related research efforts found internationally and in Sweden. The cutting-edge research topics involved in the research profile and their synergy with the digitalization efforts of the 7 partner companies, in form of the development of an intelligent decision support system, can be used to improve the competiveness of the Swedish manufacturing industry by supporting their holistic, optimal and sustainable decision making., CC BY-NC 4.0

This paper conceptually introduces VF-KDO (Virtual Factories with Knowledge-Driven Optimization, a research profile of the University of Skovde, Sweden, which is underway from 2018-2026. The goal of this research profile is to deliver radical innovations in manufacturing research essential to the design and operation of next-generation manufacturing systems. A unique concept proposed in VF-KDO is: knowledge extracted for decision support is achieved through systematically exploring, e.g., using advanced, interactive data analytics techniques on optimal solutions generated via many-objective optimizations on virtual factory models. As the word 'driven' means 'motivated' or 'manipulated', so does KDO have some two-fold meanings: (1) optimizations that aim at generating knowledge, not only mathematically optimal solutions; (2) knowledge-controlled optimizations, instead of some blind/black-box processes. It is this concept of KDO, combining with modular, virtual factory models at different levels, which distinguishes VF-KDO from other related research efforts found internationally and in Sweden. The cutting-edge research topics involved in the research profile and their synergy with the digitalization efforts of the 7 partner companies, in form of the development of an intelligent decision support system, can be used to improve the competiveness of the Swedish manufacturing industry by supporting their holistic, optimal and sustainable decision making., CC BY-NC 4.0

Stiffness is an important characteristic of production machinery, as it contributes to its ability to precisely maintain the pose between a tool centre point with respect to a workpiece under loads. For machine tools, it directly affects the geometric dimensions and surface properties of the parts, i.e. how closely the parts match their design drawings. This work presents an efficient measurement procedure to measure and identify the full translational stiffness matrices of machine tools. The measurement procedure consists of inducing static loads, which vary in magnitude and direction, at the tool centre point of the machine tool using the Loaded Double Ball Bar and measures the displacement with three Linear Variable Differential Transformers. The main components of the uncertainty budget related to the measurement of the cross compliance are also summarized. The measurement procedure is implemented in a case study on a 5-axis machining centre. Finally, the manuscript concludes with a discussion on the utility value of the translational stiffness matrix for the design and operation of machine tools as well as the possibility to expand the measurement procedure to capture the quasi-static and dynamic compliance., QC 20201202

This paper conceptually introduces VF-KDO (Virtual Factories with Knowledge-Driven Optimization, a research profile of the University of Skovde, Sweden, which is underway from 2018-2026. The goal of this research profile is to deliver radical innovations in manufacturing research essential to the design and operation of next-generation manufacturing systems. A unique concept proposed in VF-KDO is: knowledge extracted for decision support is achieved through systematically exploring, e.g., using advanced, interactive data analytics techniques on optimal solutions generated via many-objective optimizations on virtual factory models. As the word 'driven' means 'motivated' or 'manipulated', so does KDO have some two-fold meanings: (1) optimizations that aim at generating knowledge, not only mathematically optimal solutions; (2) knowledge-controlled optimizations, instead of some blind/black-box processes. It is this concept of KDO, combining with modular, virtual factory models at different levels, which distinguishes VF-KDO from other related research efforts found internationally and in Sweden. The cutting-edge research topics involved in the research profile and their synergy with the digitalization efforts of the 7 partner companies, in form of the development of an intelligent decision support system, can be used to improve the competiveness of the Swedish manufacturing industry by supporting their holistic, optimal and sustainable decision making., CC BY-NC 4.0

This paper conceptually introduces VF-KDO (Virtual Factories with Knowledge-Driven Optimization, a research profile of the University of Skovde, Sweden, which is underway from 2018-2026. The goal of this research profile is to deliver radical innovations in manufacturing research essential to the design and operation of next-generation manufacturing systems. A unique concept proposed in VF-KDO is: knowledge extracted for decision support is achieved through systematically exploring, e.g., using advanced, interactive data analytics techniques on optimal solutions generated via many-objective optimizations on virtual factory models. As the word 'driven' means 'motivated' or 'manipulated', so does KDO have some two-fold meanings: (1) optimizations that aim at generating knowledge, not only mathematically optimal solutions; (2) knowledge-controlled optimizations, instead of some blind/black-box processes. It is this concept of KDO, combining with modular, virtual factory models at different levels, which distinguishes VF-KDO from other related research efforts found internationally and in Sweden. The cutting-edge research topics involved in the research profile and their synergy with the digitalization efforts of the 7 partner companies, in form of the development of an intelligent decision support system, can be used to improve the competiveness of the Swedish manufacturing industry by supporting their holistic, optimal and sustainable decision making., CC BY-NC 4.0

The power usage effectiveness (PUE) is commonly used as the key performance indicator to evaluate the energy performance of data centers. However, using only PUE cannot enable a fair comparison when data centers are operating in different regions, due to the unneglectable impacts of climatic conditions on the power consumption of cooling systems. To solve this problem, a new indicator, coefficient of PUE (COPUE), is proposed, which is defined as the ratio of the measured PUE of real data centers to the local benchmark PUE. The benchmark PUE is reckoned based on the current most commonly used cooling technology, which consists of water-cooled chillers and water cooling towers. A simplified method for calculating benchmark PUE is also developed. The degree hour of water cooling is introduced to consider the impacts of local climatic conditions. It presents the annual accumulated hours, in which chilled water is needed to satisfy the cooling demand of data centers. Through several case studies, COPUE has been proved to be an effective indicator for comparing the energy performance of data centers. When the same cooling technology is adopted, it can reflect how good the design and operation are; while, when different cooling technologies are adopted, it can be used to demonstrate which one is superior.

This paper conceptually introduces VF-KDO (Virtual Factories with Knowledge-Driven Optimization, a research profile of the University of Skovde, Sweden, which is underway from 2018-2026. The goal of this research profile is to deliver radical innovations in manufacturing research essential to the design and operation of next-generation manufacturing systems. A unique concept proposed in VF-KDO is: knowledge extracted for decision support is achieved through systematically exploring, e.g., using advanced, interactive data analytics techniques on optimal solutions generated via many-objective optimizations on virtual factory models. As the word 'driven' means 'motivated' or 'manipulated', so does KDO have some two-fold meanings: (1) optimizations that aim at generating knowledge, not only mathematically optimal solutions; (2) knowledge-controlled optimizations, instead of some blind/black-box processes. It is this concept of KDO, combining with modular, virtual factory models at different levels, which distinguishes VF-KDO from other related research efforts found internationally and in Sweden. The cutting-edge research topics involved in the research profile and their synergy with the digitalization efforts of the 7 partner companies, in form of the development of an intelligent decision support system, can be used to improve the competiveness of the Swedish manufacturing industry by supporting their holistic, optimal and sustainable decision making., CC BY-NC 4.0

The aim of this article is to study the hydrodynamic vibration of knife refiners. Such vibration occurs due to hydrodynamic processes during the operation of the mill. A mathematical model is proposed that describes hydrodynamic vibration. The hydrodynamic force that excites the mill oscillations consists of the following main components: Impact of the semi-finished product on the auger blades and headset knives; forward and reverse flow interactions; pressure on the knives of the headset. These forces depend on the design and operation of the mill. The error between theoretical and experimental studies does not exceed 20%. Vibration processes of hydrodynamic origin are mainly determined by the impact of the semi-finished product flow on the auger blades at the entrance to the mill. The proposed research technique can be used in other machines, for example, in centrifugal pumps. © 2020 Published under licence by IOP Publishing Ltd.

Use of reactive filter media (RFM) is an emerging technology in small-scale wastewater treatment to improve phosphorus (P) removal and filter material longevity for making this technology sustainable. In this study, long-term sorption kinetics and the spatial dynamics of sorbed P distribution were simulated in replaceable P-filter bags filled with 700 L of reactive material and used in real on-site treatment systems. The input data for model calibration were obtained in laboratory trials with Filtralite P®, Polonite® and Top16. The P concentration breakthrough threshold value was set at an effluent/influent (C/C 0 ) ratio of 1 and simulations were performed with P concentrations varying from 1 to 25 mg L -1 . The simulation results showed that influent P concentration was important for the breakthrough and longevity, and that Polonite performed best, followed by Top16 and Filtralite P. A 100-day break in simulated intermittent flow allowed the materials to recover, which for Polonite involved slight retardation of P saturation. The simulated spatial distribution of P accumulated in the filter bags showed large differences between the filter materials. The modelling insights from this study can be applied in design and operation of on-site treatment systems using reactive filter materials., QC 20190815

Accurate performance prediction is necessary when designing/optimising wind propulsion systems (WPS). An independent, trustworthy prediction of the energy-saving potential is also needed to support the ship owner's decision to invest in new technology. By using weather statistics along with a mathematical model of ship performance, route simulations can estimate the time and power required for transit of a route. Such simulations are commonly used today to optimise the design and operation of conventional ships. The introduction of WPS poses additional challenges for route simulations. WPS performance must be predicted at all points along the route, with wind of differing velocity and direction. The apparent wind will vary vertically (twist), due to the interaction between the ship velocity and the atmospheric boundary layer. Also, many proposed concepts use multiple WPS, introducing additional complexity, such as independent spin ratios/ sheeting angles. 3D CFD simulations capture the complex physics, including vortex formation and interaction effects, providing accurate performance prediction and an understanding of the flow. However, 3D CFD is costly, and it would not be possible to simulate all conditions at a reasonable cost. We present simplified approaches to modelling of WPS, using a limited number of CFD simulations, either in 2D or 3D, which are then extrapolated such that 3D effects are represented, and all conditions covered. The methodology is demonstrated on rotor sails and wing sails., QC 20211005

Use of reactive filter media (RFM) is an emerging technology in small-scale wastewater treatment to improve phosphorus (P) removal and filter material longevity for making this technology sustainable. In this study, long-term sorption kinetics and the spatial dynamics of sorbed P distribution were simulated in replaceable P-filter bags filled with 700 L of reactive material and used in real on-site treatment systems. The input data for model calibration were obtained in laboratory trials with Filtralite P®, Polonite® and Top16. The P concentration breakthrough threshold value was set at an effluent/influent (C/C 0 ) ratio of 1 and simulations were performed with P concentrations varying from 1 to 25 mg L -1 . The simulation results showed that influent P concentration was important for the breakthrough and longevity, and that Polonite performed best, followed by Top16 and Filtralite P. A 100-day break in simulated intermittent flow allowed the materials to recover, which for Polonite involved slight retardation of P saturation. The simulated spatial distribution of P accumulated in the filter bags showed large differences between the filter materials. The modelling insights from this study can be applied in design and operation of on-site treatment systems using reactive filter materials., QC 20190815

Use of reactive filter media (RFM) is an emerging technology in small-scale wastewater treatment to improve phosphorus (P) removal and filter material longevity for making this technology sustainable. In this study, long-term sorption kinetics and the spatial dynamics of sorbed P distribution were simulated in replaceable P-filter bags filled with 700 L of reactive material and used in real on-site treatment systems. The input data for model calibration were obtained in laboratory trials with Filtralite P®, Polonite® and Top16. The P concentration breakthrough threshold value was set at an effluent/influent (C/C 0 ) ratio of 1 and simulations were performed with P concentrations varying from 1 to 25 mg L -1 . The simulation results showed that influent P concentration was important for the breakthrough and longevity, and that Polonite performed best, followed by Top16 and Filtralite P. A 100-day break in simulated intermittent flow allowed the materials to recover, which for Polonite involved slight retardation of P saturation. The simulated spatial distribution of P accumulated in the filter bags showed large differences between the filter materials. The modelling insights from this study can be applied in design and operation of on-site treatment systems using reactive filter materials., QC 20190815

Use of reactive filter media (RFM) is an emerging technology in small-scale wastewater treatment to improve phosphorus (P) removal and filter material longevity for making this technology sustainable. In this study, long-term sorption kinetics and the spatial dynamics of sorbed P distribution were simulated in replaceable P-filter bags filled with 700 L of reactive material and used in real on-site treatment systems. The input data for model calibration were obtained in laboratory trials with Filtralite P®, Polonite® and Top16. The P concentration breakthrough threshold value was set at an effluent/influent (C/C 0 ) ratio of 1 and simulations were performed with P concentrations varying from 1 to 25 mg L -1 . The simulation results showed that influent P concentration was important for the breakthrough and longevity, and that Polonite performed best, followed by Top16 and Filtralite P. A 100-day break in simulated intermittent flow allowed the materials to recover, which for Polonite involved slight retardation of P saturation. The simulated spatial distribution of P accumulated in the filter bags showed large differences between the filter materials. The modelling insights from this study can be applied in design and operation of on-site treatment systems using reactive filter materials., QC 20190815

A term systems of systems (SoS) refers to a setup in which a number of independent systems collaborate to create a value that each of them is unable to achieve independently. Complexity of a SoS structure is higher compared to its constitute systems that brings challenges in analyzing its critical properties such as security. An SoS can be seen as a set of connected systems or services that needs to be adequately protected. Communication between such systems or services can be considered as a service itself, and it is the paramount for establishment of a SoS as it enables connections, dependencies, and a cooperation. Given that reliable and predictable communication contributes directly to a correct functioning of an SoS, communication as a service is one of the main assets to consider. Protecting it from malicious adversaries should be one of the highest priorities within SoS design and operation. This study aims to investigate the attack propagation problem in terms of service-guarantees through the decomposition into sub-services enriched with preconditions and postconditions at the service levels. Such analysis is required as a prerequisite for an efficient SoS risk assessment at the design stage of the SoS development life cycle to protect it from possibly high impact attacks capable of affecting safety of systems and humans using the system.

Use of reactive filter media (RFM) is an emerging technology in small-scale wastewater treatment to improve phosphorus (P) removal and filter material longevity for making this technology sustainable. In this study, long-term sorption kinetics and the spatial dynamics of sorbed P distribution were simulated in replaceable P-filter bags filled with 700 L of reactive material and used in real on-site treatment systems. The input data for model calibration were obtained in laboratory trials with Filtralite P®, Polonite® and Top16. The P concentration breakthrough threshold value was set at an effluent/influent (C/C 0 ) ratio of 1 and simulations were performed with P concentrations varying from 1 to 25 mg L -1 . The simulation results showed that influent P concentration was important for the breakthrough and longevity, and that Polonite performed best, followed by Top16 and Filtralite P. A 100-day break in simulated intermittent flow allowed the materials to recover, which for Polonite involved slight retardation of P saturation. The simulated spatial distribution of P accumulated in the filter bags showed large differences between the filter materials. The modelling insights from this study can be applied in design and operation of on-site treatment systems using reactive filter materials., QC 20190815

Application of modern information technologies in different stages of the lifecycle of cogeneration turbines is considered as one of possible ways for improving their competitiveness. Specific features relating to rendering information support for steam turbine units during the periods of their design and operation, which are the main stages of their life cycle, are presented. Three-dimension modeling, adaptive, and parametric design technologies are applied in the equipment design stages. Information support technologies developed by the authors are applied during the operation stage. Information is integrated by using a product lifecycle management (PLM) system. © 2013 Pleiades Publishing, Ltd.

New R&D collaboration on "Design and Operation of Power Systems with Large Amounts of Wind Power Production" has been formed in IEA Wind. The R&D task will collect and share information on the experience gained and the studies made on power system impacts of wind power, and review methodologies, tools and data used. This paper outlines the power system impacts of wind power, the national studies published and on-going and describes the goals of the international collaboration. There are dozens of studies made and ongoing related to cost of wind integration, however, the results are not easy to compare. An in-depth review of the studies is needed to draw conclusions on the range of integration costs for wind power. State-of-the art review process will seek for reasons behind the wide range of results for costs of wind integration - definitions for wind penetration, reserves and costs; different power system and load characteristics and operational rules; underlying assumptions on variability of wind etc., QC 20141106