University of Kaiserslautern
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Integrating UPnP technology with CAFM systems – automated device identification and device control in building operation and maintenance
Get PDFPurpose: Modern buildings use intelligent automation for comfort, efficiency and sustainability, impacting their construction and operation. Although building automation (BA) operates via bus lines and is controlled by sensors and actuators, computer-aided facility management (CAFM) systems often handle data redundantly. Current standards fail to detail effective systems integration, with a noticeable gap in practical network models and solutions. The purpose of this paper is to design a network model that integrates building services and networks at the automation level. The goal is to enable the CAFM side to control all electrical loads (such as lighting, blinds, pumps), climate control (HVAC) and security monitoring.
Design/methodology/approach: This paper explores the automatic discovery and integration of BA devices and centralized controls into CAFM systems, focusing on innovative networking models, system data provisioning, import functions and web operation. Established technologies such as Universal Plug and Play (UPnP) and Extensible Markup Language (XML) standards are utilized to develop new solutions.
Findings: The paper introduces a solution with a database and software module enabling bidirectional web-based coupling via LAN. The UPnP standard was enhanced to include facility management (FM)–specific information for device communication. The prototype effectively controls devices through CAFM systems, setting a foundation for future improvements in web-based BA. These results are crucial for developing standards for automated data processing between CAFM systems and BA.
Practical implications: This research benefits FM, especially in maintenance, operations, energy and compliance. In addition, the need for time-consuming on-site inspections to record device master data for maintenance management, in case of commissioning or changing facility service providers, can be eliminated. The principles of the developed software module enhance CAFM systems as high-performance building control tools.
Originality/value: The paper adapts existing technologies for specific FM applications and integrates them for the first time into key FM processes
Guided port injection of hydrogen as an approach for reducing cylinder-to-cylinder deviations in spark-ignited H2 engines – a numerical investigation
Get PDFThe reduction of anthropogenic greenhouse gas emissions and ever stricter regulations on pollutant emissions in the transport sector require research and development of new, climate-friendly propulsion concepts. The use of renewable hydrogen as a fuel for internal combustion engines promises to provide a good solution especially for commercial vehicles. For optimum efficiency of the combustion process, hydrogen-specific engine components are required, which need to be tested on the test bench and analysed in simulation studies. This paper deals with the simulation-based investigation and optimisation of fuel injection in a 6-cylinder PFI commercial vehicle engine, which has been modified for hydrogen operation starting from a natural gas engine concept. The focus of the study is on a CNG-derived manifold design which has been adapted with regard to the injector interface and is already equipped with so-called gas injection guiding tubes for targeted fuel injection in front of the intake runners of the individual cylinders. Significant deviations between the averaged cylinder pressure profiles of the individual cylinders observed on the test bench point to an issue with the equal distribution of the fuel supply to the individual cylinders. A subsequent 3D CFD simulation of the internal manifold flow showed geometry-induced turbulence of the fresh air flow in the area of the hydrogen supply outlet of several cylinders, which can lead to variations in cylinder-specific fuel quantities. In order to minimise the influence of the air flow in the manifold on the fuel injection, a dedicated injection guide concept for the gas injection tubes in the intake manifold has been designed with the aim of moving the position of hydrogen injection closer to the intake valves. In this study, this concept is analyzed based on first results obtained from a detailed 3D CFD simulation, especially in terms of the uniformity of hydrogen distribution between the cylinders, mixture formation and the effect on combustion
How to personalise cognitive-behavioural therapy for chronic primary pain using network analysis: study protocol for a single-case experimental design with multiple baselines
Get PDFIntroduction Cognitive–behavioural therapy (CBT) is an effective treatment for chronic primary pain (CPP), but effect sizes are small to moderate. Process orientation, personalisation, and data-driven clinical decision-making might address the heterogeneity among persons with CPP and are thus promising pathways to enhance the effectiveness of CBT for CPP. This study protocol describes one approach to personalise CBT for CPP using network analysis.
Methods and analysis A single-case experimental design with multiple baselines will be combined with ecological momentary assessment (EMA). Feasibility and acceptance of the study procedure will be demonstrated on a sample of n=12 adults with CPP in an outpatient clinic. In phase A, participants complete 21 days of EMA, followed by the standard diagnostic phase of routine clinical care (phase B). Person-specific, process-based networks are estimated based on EMA data. Treatment targets are selected using mean ratings, strength and out-strength centrality. After a second, randomised baseline (phase A'), participants will receive 1 out of 10 CBT interventions, selected by an algorithm matching targets to interventions, in up to 10 sessions (phase C). Finally, another EMA phase of 21 days will be completed to estimate a post-therapy network.
Tau-U and Hedges’ g are used to indicate individual treatment effects. Additionally, conventional pain disability measures (Pain Disability Index and the adapted Quebec Back Pain Disability Scale) are assessed prior, post, and 3 months after phase C.
Ethics and dissemination Ethical considerations were made with regard to the assessment-induced burden on the participants. This proof-of- concept study may guide future studies aiming at personalisation of CBT for CPP as it outlines methodological decisions that need to be considered step by step. The project was approved by the local ethics committee of the psychology department of University Kaiserslautern-Landau (#LEK-457).
Participants gave their written informed consent prior to any data assessment and app installation. The results of the project will be published, presented at congresses, and relevant data will be made openly accessible via the Open Science Framework (OSF)
Gröbner Basis Algorithms in Service of Algebraic Set Decomposition
Get PDFAlgebraic sets, i.e. solution sets of polynomial systems of equations,model a wide variety of nonlinear problems, both in applied and pure mathematics. One of the most foundational results in algebraic geometry sais that every algebraic set has a unique decomposition into irreducible algebraic sets and a frequent task is to decompose such an algebraic set into its irreducible components, or to produce some kind of coarser decomposition of the algebraic set in question. This task comes up for example in certain problems in robotics on the applied side and enumerative geometry on the pure side. In this thesis, we present a series of algorithms solving such decomposition problems for algebraic sets. All of these algorithms use Gröbner bases for polynomial ideals at their core. Gröbner bases are an ubiquitous tool in symbolic computation. They form the core of many higher level algorithms and are implemented in all prominent computer algebra systems. Three of these algorithms produce so-called equidimensional decompositions of an algebraic set, i.e. they partition a given algebraic set dimension-by-dimension. They are designed to avoid potentially costly elimination operations and, partially, use features of so-called {\em signature-based} Gröbner basis algorithms. Our software implementations of these algorithms showcase their practical efficiency compared to state-of-the-art computer algebra systems on examples of interest. Another set of algorithms (respectively based on the F4 algorithm and the FGLM algorithm use Hensel lifting methods in a novel way to compute Gröbner bases for generic fibers of polynomial ideals. We outline how these algorithms can be used as a core piece in known algorithms for equidimensional or irreducible decomposition of an algebraic set and exhibit their quasi-linear complexity in the precision up to which certain power series are computed. Finally, we give an extension of generic fiber techniques for equidimensional decomposition of algebraic sets to compute Whitney stratifications of singular algebraic sets, improving on the state of the art. A Whitney stratification partitions a singular algebraic set into smooth pieces in a desirable way and has applications, for example, in physics. We, in addition, give an algorithm to minimize a given Whitney stratification
New insights into the influence of pre-culture on robust solvent production of C. acetobutylicum
Get PDFClostridia are known for their solvent production, especially the production of butanol. Concerning the projected depletion of fossil fuels, this is of great interest. The cultivation of clostridia is known to be challenging, and it is difficult to achieve reproducible results and robust processes. However, existing publications usually concentrate on the cultivation conditions of the main culture. In this paper, the influence of cryo-conservation and pre-culture on growth and solvent production in the resulting main cultivation are examined. A protocol was developed that leads to reproducible cultivations of Clostridium acetobutylicum. Detailed investigation of the cell conservation in cryo-cultures ensured reliable cell growth in the pre-culture. Moreover, a reason for the acid crash in the main culture was found, based on the cultivation conditions of the pre-culture. The critical parameter to avoid the acid crash and accomplish the shift to the solventogenesis of clostridia is the metabolic phase in which the cells of the pre-culture were at the time of inoculation of the main culture; this depends on the cultivation time of the pre-culture. Using cells from the exponential growth phase to inoculate the main culture leads to an acid crash. To achieve the solventogenic phase with butanol production, the inoculum should consist of older cells which are in the stationary growth phase. Considering these parameters, which affect the entire cultivation process, reproducible results and reliable solvent production are ensured
Short-term adaptation as a tool to improve bioethanol production using grass press-juice as fermentation medium
Get PDFGrass raw materials collected from grasslands cover more than 30% of Europe’s agricultural area. They are considered very attractive for the production of different biochemicals and biofuels due to their high availability and renewability. In this study, a perennial ryegrass (Lolium perenne) was exploited for second-generation bioethanol production. Grass press–cake and grass press-juice were separated using mechanical pretreatment, and the obtained juice was used as a fermentation medium. In this work, Saccharomyces cerevisiae was utilized for bioethanol production using the grass press-juice as the sole fermentation medium. The yeast was able to release about 11 g/L of ethanol in 72 h, with a total production yield of 0.38 ± 0.2 gEthanol/gsugars. It was assessed to improve the fermentation ability of Saccharomyces cerevisiae by using the short-term adaptation. For this purpose, the yeast was initially propagated in increasing the concentration of press-juice. Then, the yeast cells were re-cultivated in 100%(v/v) fresh juice to verify if it had improved the fermentation efficiency. The fructose conversion increased from 79 to 90%, and the ethanol titers reached 18 g/L resulting in a final yield of 0.50 ± 0.06 gEthanol/gsugars with a volumetric productivity of 0.44 ± 0.00 g/Lh. The overall results proved that short-term adaptation was successfully used to improve bioethanol production with S. cerevisiae using grass press-juice as fermentation medium
MICP treated sand: insights into the impact of particle size on mechanical parameters and pore network after biocementation
Get PDFMicrobiologically Induced Calcium Carbonate Precipitation (MICP) is a technology for improving soil characteristics, especially strength, that has been gaining increasing interest in literature during the last few years. Although a lot of influencing factors on the result of MICP are known, particle size and shape of the particles remain poorly understood. While destructive measuring of compressive strength or calcium carbonate content are important for the characterization of samples these methods give no insight into the internal structures and pore networks of the samples. X-ray microcomputed tomography (micro-CT) is a technique that is used to characterize the internals of rocks and to a certain degree MICP-treated soils. However, the impact of filtering and image processing of micro-CT Data depending on the type of MICP sample is poorly described in the literature. In this study, single fractions of local quarry were treated with MICP through the ureolytic microorganism Sporosarcina pasteurii to investigate the influence of particle size distribution on calcium carbonate content, unconfined compressive strength and the reduction of water permeability. Additionally, micro-CT was conducted to obtain insights into the resulting pore system. The impact of the Gauss filter und Non-local means filter on the resulting images and data on the pore network are discussed. The results show that particle size has a significant impact on the result of all tested parameters of biosandstone with lower particle size leading to higher strength and generally higher calcium carbonate content. Micro-CT data showed that the technology is feasible to gain valuable insights into the internal structures of biosandstone but the resolution and signal-to-noise ratio remain challenging, especially for samples with particle sizes smaller than 125 µm
Prädiktive Optimierung von Energieflüssen in Wohngebäuden mit Photovoltaik-Eigenstromerzeugung unter Berücksichtigung von Power-To-Heat (Wärmepumpe), Power-To-Power (Stromspeicher) und Vehicle-To-Building (bidirektionales Laden von Elektrofahrzeugen)
Get PDFDer Klimawandel und seine potenziellen Auswirkungen stellen eine ernstzunehmende Bedrohung für die Umwelt dar. Um diesem entgegenzuwirken, haben sich sowohl die Europäische Union als auch die Bundesrepublik Deutschland zu Maßnahmen verpflichtet, die u.a. zu einer zunehmenden Abkehr der Nutzung von fossilen Brennstoffen führen sollen. Die Maßnahmen beziehen sich hierbei auch auf den großflächigen Ausbau der Erneuerbaren Energien. Diese bringen zwar den großen Vorteil einer CO2-freien Energieerzeugung mit sich, unterliegen dafür aber einer starken Fluktuation, die sich an Wetterbedingungen orientiert und dabei v.a. von Solarstrahlung und Windgeschwindigkeit abhängig ist. Daher werden Speichermöglichkeiten in Zukunft stark an Relevanz gewinnen, zusätzlich sollten aber auf Verbraucherebene auch Flexibilitäten identifiziert werden, die auf die Volatilität in der Energieerzeugung reagieren können.
Gerade der Gebäudesektor stellt dabei eine zentrale Herausforderung für das Gelingen der Energiewende dar, da er für etwa 50 % des Endenergiebedarfs in Deutschland zuständig ist. Ein Großteil davon entfällt auf das Beheizen der Gebäude. Die Wärmepumpe ist dabei eine der wichtigsten Technologien für eine nachhaltige Wärmebereitstellung, da sie (zunehmend erneuerbaren) Strom mit einer guten Effizienz in thermische Energie umwandeln kann. Da die Wärmeerzeugung in der Regel mit einem thermischen Speicher verknüpft ist, stellt gerade der Betrieb von Wärmepumpen eine Flexibilitätsoption dar, die mit Hilfe eines intelligenten Regelungssystems in optimale Zeiträume verschoben werden kann.
In dieser Arbeit wird unter diesem Hintergrund ein prädiktives Optimierungssystem entwickelt, das regelbasierte Entscheidungen trifft und somit Stromflüsse im Gebäude gezielt regeln soll. Standardmäßig wird in der Optimierung dafür eine Photovoltaik-Anlage zu Eigenstromerzeugung, eine Wärmepumpe als Wärmeerzeuger und ein Wassertank als Wärmespeicher benötigt. Zudem können ein Haushaltsstromspeicher und ein E-Auto, das bidirektional geladen werden kann, modular hinzugefügt werden. Die Modelle des thermischen Speichers, der PV-Anlage, des Stromspeichers und der E-Batterie sind zudem in ihrer Dimensionierung variabel und der Einfluss unterschiedlicher Größen wird ebenso analysiert wie verschiedene Innentemperaturen. Die Betrachtung wird anhand eines realen Gebäudes, das vier Ferienwohnungen umfasst, durchgeführt. Die Optimierung ist dabei so ausgelegt, dass sie v.a. den Netzbezug des Gebäudes reduzieren und somit zur Netzentlastung beitragen soll.
Die Ergebnisse der Arbeit zeigen, dass die entwickelte Optimierung auf Simulationsebene im Vergleich zu einer Referenzbetrachtung in über 1000 untersuchten Szenarien immer zu einer Reduzierung des Netzbezugs führt. Die maximalen Einsparungen liegen bei über 1000 kWh bzw. 35 %, im Mittel kann der Netzbezug um ca. 560 kWh bzw. 16 % reduziert werden. Somit kann die prädiktive Optimierung dafür eingesetzt werden, Flexibilität auf Gebäudeebene gezielt auszunutzen, um den Netzbezug zu reduzieren und somit potenziell einen Beitrag zum Gelingen der Energiewende leisten.Climate change and its consequences pose a catastrophic threat to the environment. To counteract this, the European Union and the Federal Republic of Germany have committed themselves to measures that should lead to an increasing departure from the use of fossil fuels. The measures also include large-scale expansion of renewable energies. Although the latter have a great advantage in terms of CO2-free energy generation, they are subject to strong fluctuations based on weather conditions such as solar radiation and wind speed. Storage options will therefore become increasingly relevant in the future. Additionally, flexibility that can react to the volatility in energy generation must be detected at the consumer level.
The building sector represents a key challenge for the success of the energy transition, as it is responsible for around 50 % of the final energy demand in Germany. A large proportion of the energy demand is used to heat buildings. The heat pump is one of the most important technologies for sustainable heat supply, as it can convert (increasingly renewable) electricity into thermal energy with good efficiency. Since heat generation is usually linked to a thermal storage system, the operation of heat pumps represents a flexible option that can be shifted to optimal periods with the help of an intelligent control system.
This thesis develops a predictive optimization system that makes rule-based decisions and thus regulates electricity flows in the building in a systematic approach. By default, the optimization requires a photovoltaic system to generate its own electricity, a heat pump as a heat generator and a water tank as a heat storage unit. Furthermore, a household electricity storage unit and an electric car with bidirectional charging can be added on a modular basis. The models of the thermal storage unit, the PV system, the electricity storage unit and the e-battery are variable in their dimensioning. This work analyses the influence of different sizes and indoor temperatures. The analysis is carried out using a real building containing four vacation apartments. The optimization is aimed at reducing the grid consumption of the building, thereby contributing to grid relief.
The results of the simulation show that the developed optimization leads to a reduction in grid consumption in over 1000 examined scenarios in comparison to a reference model. The maximum savings are over 1000 kWh or 35 %. On average, grid consumption can be reduced by approximately 560 kWh or 16 %. The predictive optimization can therefore be used to make systematic use of flexibility at building level to reduce grid consumption and potentially contribute to the success of the energy transition
Uncertainty-aware Visual Analytics and Its Applications
Get PDFEffective communication of uncertainty is crucial for informed decision-making in data analysis workflows to estimate the reliability of available data and resulting insights. Here, visual analytics is a modern process combining algorithmic data analysis techniques and interactive visualization to extract insights from datasets. Integrating uncertainty in visual analytics is not trivial, and the growing field of uncertainty-aware visual analytics applications shows the importance of integrating uncertainty information for decision-making. Still, there is no general systematic model and guideline to integrate uncertainty in visual analytics applications to assist application designers.
This raised the questions "How to define an uncertainty-aware visual analytics process?" and "Which steps are necessary to map a visual analytics process to an uncertainty-aware visual analytics process?".
Accordingly, this thesis addresses these questions in three steps. First, an uncertainty-aware visual analytics process describes all components and transitions when dealing with data containing uncertainty, providing a model to check for compatibility of an application. A guideline for creating a compatible uncertainty-aware application delivers detailed development steps that allow converting existing applications and creating new ones from scratch. At last, multiple uncertainty-aware visual analytics applications are showcased to provide realizations of the uncertainty-aware visual analytics process. Those examples either represent a post hoc mapping to the uncertainty-aware visual analytics process or deliver design decisions for recreating an existing application using the guideline.
In the end, the research questions and their solutions are discussed, closing with open challenges and future research directions
Characterizing localization effects in an ultracold disordered Fermi gas by diffusion analysis
Get PDFDisorder can fundamentally modify the transport properties of a system. A striking example is Anderson localization, suppressing transport due to destructive interference of propagation paths. In inhomogeneous many-body systems, not all particles are localized for finite-strength disorder, and the system can become partially diffusive. Unraveling the intricate signatures of localization from such observed diffusion is a longstanding problem. Here, we experimentally study a degenerate, spin-polarized Fermi gas in a disorder potential formed by an optical speckle pattern. We record the diffusion through the disordered potential upon release from an external confining potential. We compare different methods to analyze the resulting density distributions, including a new approach to capture particle dynamics by evaluating absorption-image statistics. Using standard observables, such as diffusion exponent and coefficient, localized fraction, or localization length, we find that some show signatures for a transition to localization above a critical disorder strength, while others show a smooth crossover to a modified diffusion regime. In laterally displaced disorder, we spatially resolve different transport regimes simultaneously, which allows us to extract the subdiffusion exponent expected for weak localization. Our work emphasizes that the transition toward localization can be investigated by closely analyzing the system's diffusion, offering ways of revealing localization effects beyond the signature of exponentially decaying density distribution