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A benchmark analysis of Long Range (LoRaTM) Communication at 2.45 Ghz for safety applications
(2014)
The demand of wireless solutions in industrial applications increases since the early nineties. This trend is not only ongoing, it is further pushed by developments in the area of software stacks like the latest Bluetooth Low Energy Stack. It is also pushed by new chip-designs and powerful and highly integrated electronic hardware. The acceptance of wireless technologies as a possible solution for industrial applications, has overcome the entry barrier [1]. The first step to see wireless as standard for many industrial applications is almost accomplished. Nevertheless there is nearly none acceptance of wireless technology for Safety applications. One highly challenging and demanding requirement is still unsolved: The aspect safety and robustness. Those topics have been addressed in many cases but always in a similar manner. WirelessHART as an example addresses this topic with redundant so called multiple propagation paths and frequency hopping to handle with interferences and loss of network participants. So far the pure peer to peer link is rarely investigated and there are less safety solutions available. One product called LoRa™ can be seen as one possible solution to address this lack of safety within wireless links. This paper focuses on the safety performance evaluation of a modem-chip-design. The use of diverse and redundant wireless technologies like LoRa can lead to an increase acceptance of wireless in safety applications. Many measurements in real industrial application have been carried out to be able to benchmark the new chip in terms of the safety aspects. The content of this research results can help to raise the level of confidence in wireless. In this paper, the term “safety” is used for data transmission reliability.
Gamification is increasingly successful in the field of education and health. However, beyond call-centers and applications in human resources, its utilization within companies remains limited. In this paper, we examine the acceptance of gamification in a large company (with over 17,000 employees) across three generations, namely X, Y, and Z. Furthermore, we investigate which gamification elements are suited for business contexts, such as the dissemination of company principles and facts, or the organization of work tasks. To this end, we conducted focus group discussions, developed the prototype of a gamified company app, and performed a large-scale evaluation with 367 company employees. The results reveal statistically significant intergenerational disparities in the acceptance of gamification: younger employees, especially those belonging to Generation Z, enjoy gamification more than older employees and are most likely to engage with a gamified app in the workplace. The results further show a nuanced range of preferences regarding gamification elements: avatars are popular among all generations, badges are predominantly appreciated by Generations Z and Y, while leaderboards are solely liked by Generation Z. Drawing upon these insights, we provide recommendations for future gamification projects within business contexts. We hope that the results of our study regarding the preferences of the gamification elements and understanding generational differences in acceptance and usage of gamification will help to create more engaging and effective apps, especially within the corporate landscape.
Inadequate mechanical compliance of orthopedic implants can result in excessive strain of the bone interface, and ultimately, aseptic loosening. It is hypothesized that a fiber-based biometal with adjustable anisotropic mechanical properties can reduce interface strain, facilitate continuous remodeling, and improve implant survival under complex loads. The biometal is based on strategically layered sintered titanium fibers. Six different topologies are manufactured. Specimens are tested under compression in three orthogonal axes under 3-point bending and torsion until failure. Biocompatibility testing involves murine osteoblasts. Osseointegration is investigated by micro-computed tomography and histomorphometry after implantation in a metaphyseal trepanation model in sheep. The material demonstrates compressive yield strengths of up to 50 MPa and anisotropy correlating closely with fiber layout. Samples with 75% porosity are both stronger and stiffer than those with 85% porosity. The highest bending modulus is found in samples with parallel fiber orientation, while the highest shear modulus is found in cross-ply layouts. Cell metabolism and morphology indicate uncompromised biocompatibility. Implants demonstrate robust circumferential osseointegration in vivo after 8 weeks. The biometal introduced in this study demonstrates anisotropic mechanical properties similar to bone, and excellent osteoconductivity and feasibility as an orthopedic implant material.
The Paper presents the design and development of a blended learning concept for an engineering course in the field of color representation and display technologies. A suitable learning environment is crucial for the success of the teaching scenario. A mixture of theoretical lectures and hands-on activities with practical applications and experiments, combined with the advantages of modern digital media is the main topic of the paper. Blended learning describes the didactical change of attendance periods and online periods. The e-learning environment for the online period is designed toward an easy access and interaction. Present digital media extends the established teaching scenarios and enables the presentation of videos, animations and augmented reality (AR). Visualizations are effective tools to impart learning contents with lasting effect. The preparation and evaluation of the theoretical lectures and the hands-on activities are stimulated and affects positively the attendance periods. The tasks and experiments require the students to work independently and to develop individual solution strategies. This engages and motivates the students, deepens the knowledge. The authors will present their experience with the implemented blended learning scenario in this field of optics and photonics. All aspects of the learning environment will be introduced.
Due to a controversial enrollment policy in most engineering programs at German Universities of Applied Sciences (UAS), many freshmen show very low school grades in key subjects like Math and Physics. Nevertheless they expect to be entertained in the lectures and get demotivated easily. Despite initial reservations, a cheer-and-challenge approach was developed for teaching Mechanics to freshmen having very diverse school grades. When tested, it showed astonishing results.
The idea of this game is to use a flashcard system to create a short story in a foreign language. The story is developed by a group of people by exchanging sentences via a flashcard system. This way, people can learn from each other without fear of making mistakes because the group members are anonymous.
Printed electronics (PE) is a fast-growing field with promising applications in wearables, smart sensors, and smart cards, since it provides mechanical flexibility, and low-cost, on-demand, and customizable fabrication. To secure the operation of these applications, true random number generators (TRNGs) are required to generate unpredictable bits for cryptographic functions and padding. However, since the additive fabrication process of the PE circuits results in high intrinsic variations due to the random dispersion of the printed inks on the substrate, constructing a printed TRNG is challenging. In this article, we exploit the additive customizable fabrication feature of inkjet printing to design a TRNG based on electrolyte-gated field-effect transistors (EGFETs). We also propose a printed resistor tuning flow for the TRNG circuit to mitigate the overall process variation of the TRNG so that the generated bits are mostly based on the random noise in the circuit, providing a true random behavior. The simulation results show that the overall process variation of the TRNGs is mitigated by 110 times, and the generated bitstream of the tuned TRNGs passes the National Institute of Standards and Technology - Statistical Test Suite. For the proof of concept, the proposed TRNG circuit was fabricated and tuned. The characterization results of the tuned TRNGs prove that the TRNGs generate random bitstreams at the supply voltage of down to 0.5 V. Hence, the proposed TRNG design is suitable to secure low-power applications in this domain.
Seismic data has often missing traces due to technical acquisition or economical constraints. A compete dataset is crucial in several processing and inversion techniques. Deep learning algorithms, based on convolutional neural networks (CNNs), have shown alternative solutions that overcome limitation of traditional interpolation methods e.g. data regularity, linearity assumption, etc. There are two different paradigms of CNN methods for seismic interpolation. The first one, so-called deep prior interpolation (DPI), trains a CNN to map random noise to a complete seismic image using only the decimated image itself. The second one, referred as standard deep learning method, trains a CNN to map a decimated seismic image into a complete one using a dataset of complete and artificially decimated images. Within this research, we systematically compare the performance of both methods for different quantities of regular and irregular missing traces using 4 datasets. We evaluate the results of both methods using 5 well-known metrics. We found that DPI method performs better than the standard method if the percentage of missing traces is low (10%) and otherwise if the level of decimation is high (50%).
Radio frequency identification (RFID) antennas are popular for high frequency (HF) RFID, energy transfer and near field communication (NFC) applications. Particularly for wireless measurement systems the RFID/NFC technology is a good option to implement a wireless communication interface. In this context, the design of corresponding reader and transmitter antennas plays a major role for achieving suitable transmission quality. This work proves the feasibility of the rapid prototyping of a RFID/NFC antenna, which is used for the wireless communication and energy harvesting at the required frequency of 13.56 MHz. A novel and low-cost direct ink writing (DIW) technology utilizing highly viscous silver nanoparticle ink is used for this process. This paper describes the development and analysis of low-cost printed flexible RFID/NFC antennas on cost-effective substrates for a microelectronic vital parameter measurement system. Furthermore, we compare the measured technical parameters with existing copper-based counterparts on a FR4 substrate.
The Raman spectra from the chemical compounds toluene and cyclohexane obtained using a Fourier Transform (FT)-Raman spectrometer prototype have been contrasted with the Raman spectra of these same materials collected with two different commercial FT-Raman devices. The FT-Raman spectrometer consist of a Michelson interferometer, a self-designed photon counter and a reference photo-detector. The evaluation methodology of the spectral information, contrary to the commercial devices that commonly use the zero-crossing method, is carried out by re-sampling the Raman scattering and by accurately extracting the optical path information of the Michelson interferometer. The FTRaman arrangement has been built using conventional parts without disregarding the spectral frequency precision that usually such a FTRaman instruments deliver. No additional complex hardware components or costly software modules have been included in this FT-Raman device. The main Raman lines from the spectra obtained with the three FT-Raman devices have been compared with the Raman lines from the standard Raman spectra of these two materials. The values obtained using the FT-Raman spectrometer prototype have shown a frequency accuracy comparable to that obtained with the commercial devices without facing the need for a large investment. Although the proposed FT-Raman prototype cannot be directly compared to the last generation of FT-Raman spectrometers from the commercial manufacturers, such a device could give an opportunity to users that require high frequency precision in their spectral analysis and are provided with rather scarce resources.
This paper provides a comprehensive overview of approaches to the determination of isocontours and isosurfaces from given data sets. Different algorithms are reported in the literature for this purpose, which originate from various application areas, such as computer graphics or medical imaging procedures. In all these applications, the challenge is to extract surfaces with a specific isovalue from a given characteristic, so called isosurfaces. These different application areas have given rise to solution approaches that all solve the problem of isocontouring in their own way. Based on the literature, the following four dominant methods can be identified: the marching cubes algorithms, the tessellation-based algorithms, the surface nets algorithms and the ray tracing algorithms. With regard to their application, it can be seen that the methods are mainly used in the fields of medical imaging, computer graphics and the visualization of simulation results. In our work, we provide a broad and compact overview of the common methods that are currently used in terms of isocontouring with respect to certain criteria and their individual limitations. In this context, we discuss the individual methods and identify possible future research directions in the field of isocontouring.
The need for the logistics sector to timely respond to the increasing requirements of a globalised and digitalised world relies greatly on the com- petences and skills of its labour force. It becomes therefore essential to reinforce the cooperation between universities and business partners in the logistics and supply chain management fields across the European region and to build a logistics knowledge cluster supported by a communication and collaboration platform to foster continuous learning, skill acquisition and experience sharing anytime anywhere. In this paper we focus on designing the conceptual and technical framework for a communication and collaboration platform with the aim to establish the communication pipelines between the partner institutions, facilitating user interactions and exchange, leading to the creation of new knowledge and innovation in the logistics field. This framework is based on the requirements of the three main stakeholders: students, lecturers and companies, and consists of four functional areas defined according to the platform opera- tional requirements. A working prototype of the platform was developed using the Moodle learning management system and its core tools to determine its applicability and possible enhancement requirements. In the next stages of the project some additional tools like a knowledge base and the integration of the partners’ learning management systems to form the logistics knowledge cluster will be implemented.
With the increasing share of renewable energies and the nuclear phase-out, the energy transition is accelerating. From the perspective of building technology, there is great potential to support this transition given its large share in total energy consumption and the increasing number of flexible and controllable components and storages. However, a question often asked at the plant level is: "How do we use this flexibility to support the regional grid?". In this work, a grid-supportive controller of a real-world building energy plant was developed using mathematical optimisation methods and its technical feasibility was demonstrated. The results could convince actors from the energy industry and academia about the practicality of these methods and offer tools for their implementation.
The monitoring of industrial environments ensures that highly automated processes run without interruption. However, even if the industrial machines themselves are monitored, the communication lines are currently not continuously monitored in todays installations. They are checked usually only during maintenance intervals or in case of error. In addition, the cables or connected machines usually have to be removed from the system for the duration of the test. To overcome these drawbacks, we have developed and implemented a cost-efficient and continuous signal monitoring of Ethernet-based industrial bus systems. Several methods have been developed to assess the quality of the cable. These methods can be classified to either passive or active. Active methods are not suitable if interruption of the communication is undesired. Passive methods, on the other hand, require oversampling, which calls for expensive hardware. In this paper, a novel passive method combined with undersampling targeting cost-efficient hardware is proposed.
A crack opening stress equation for in-phase and out-of-phase thermomechanical fatigue loading
(2016)
In this paper, a crack opening stress equation for in-phase and out-of-phase thermomechanical fatigue (TMF) loading is proposed. The equation is derived from systematic calculations of the crack opening stress with a temperature dependent strip yield model for both plane stress and plane strain, different load ratios and different ratios of the temperature dependent yield stress in compression and tension. Using a load ratio scaled by the ratio of the yield stress in compression and tension, the equation accounts for the effect of the temperature dependent yield stress and the constraint on the crack opening stress. Based on the scaling relation established in this paper, Newman's crack opening stress equation for isothermal loading is enabled to predict the crack opening stress under TMF loading.
This paper describes the use of the single-linkage hierarchical clustering method in outlier detection for manufactured metal work pieces. The main goal of the study is to group defects that occur 5 mm into a work piece from the edge, i.e., the border of the metal work piece. The goal is to remove defects outside the area of interest as outliers. According to the assumptions made for the performance criteria, the single-linkage method has achieved better results compared to other agglomeration methods.
Air traffic is by nature crossing borders and organizations. The supporting infrastructure represents a federative distributed system of independent Air Traffic Service Units, typically each with its own proprietary system architecture. Interaction between the centers is taking place over dedicated protocols, often organized as a mesh of 1:1 bilateral data exchanges.
This contribution gives an overview of the ongoing efforts to standardize this data exchange. At the core is a data-centric view, using a shared virtual Flight Object as the IT counterpart of a real flight. It permits a uniform way to access and update a flight’s static and dynamic attributes. A middleware is presented that implements this abstraction and maps it onto a physical level, employing DDS (Data Distribution Service) technology for the 1:N dissemination of flight data.
A platform of an electronic capsule is being developed for multi-task medical assistant application. It includes a near field telemetry unit for bidirectional communication system of 115 KHz low carrier frequency for inductive data transmission suited for human body energy transfer. The system triggers an actuator for drug delivery in various time and release forms via wireless external control, it has the ability to record temperature, measure pH of the body (additional sensors), and retrieve data to the outside. It consists of a 32bit processor, memory, external peripheries, and detection facility. The complete system is designed to fit small-size mass medical application with low power consumption, size of 7x25mm. The system is designed, simulated and emulated on FPGA. A final layout of the complete chip design is still under progress.
The Go programming language is an increasingly popular language but some of its features lack a formal investigation. This article explains Go's resolution mechanism for overloaded methods and its support for structural subtyping by means of translation from Featherweight Go to a simple target language. The translation employs a form of dictionary passing known from type classes in Haskell and preserves the dynamic behavior of Featherweight Go programs.
The aim of this study was to develop a biomechanically validated finite element model to predict the biomechanical behaviour of the human lumbar spine in compression.
For validation of the finite element model, an in vitro study was performed: Twelve human lumbar cadaveric spinal segments (six segments L2/3 and six segments L4/5) were loaded in axial compression using 600 N in the intact state and following surgical treatment using two different internal stabilisation devices. Range of motion was measured and used to calculate stiffness.
A finite element model of a human spinal segment L3/4 was loaded with the same force in intact and surgically altered state, corresponding to the situation of biomechanical in vitro study.
The results of the cadaver biomechanical and finite element analysis were compared. As they were close together, the finite element model was used to predict: (1) load-sharing within human lumbar spine in compression, (2) load-sharing within osteoporotic human lumbar spine in compression and (3) the stabilising potential of the different spinal implants with respect to bone mineral density.
A finite element model as described here may be used to predict the biomechanical behaviour of the spine. Moreover, the influence of different spinal stabilisation systems may be predicted.
In this paper, the influence of the material hardening behavior on plasticity-induced fatigue crack closure is investigated for strain-controlled loading and fully plastic, large-scale yielding conditions by means of the finite element method. The strain amplitude and the strain ratio are varied for given Ramberg–Osgood material properties representing materials with different hardening behavior. The results show a pronounced influence of the hardening behavior on crack closure, while no significant effect is found from the considered strain amplitude and strain ratio. The effect of the hardening behavior on the crack opening stress cannot be described by existing crack opening stress equations.
Multi-phase management is crucial for performance and durability of electrochemical cells such as batteries and fuel cells. In this paper we present a generic framework for describing the two-dimensional spatiotemporal evolution of gaseous, liquid and solid phases, as well as their interdependence with interfacial (electro-)chemistry and microstructure in a continuum description. The modeling domain consists of up to seven layers (current collectors, channels, electrodes, separator/membrane), each of which can consist of an arbitrary number of bulk phases (gas, liquid, solid) and connecting interfaces (two-phase or multi-phase boundaries). Bulk and interfacial chemistry is described using global or elementary kinetic reactions. Multi-phase management is coupled to chemistry and to mass and charge transport within bulk phases. The functionality and flexibility of this framework is demonstrated using four application areas in the context of post-lithium-ion batteries and fuel cells, that is, lithium-sulfur (Li-S) cells, lithium-oxygen (Li-O) cells, solid oxide fuel cells (SOFC) and polymer electrolyte membrane fuel cells (PEFC). The results are compared to models available in literature and properties of the generic framework are discussed.
6LoWPAN (IPv6 over Low Power Wireless Personal Area Networks) is gaining more and more attraction for the seamless connectivity of embedded devices for the Internet of Things. It can be observed that most of the available solutions are following an open source approach, which significantly leads to a fast development of technologies and of markets. Although the currently available implementations are in a pretty good shape, all of them come with some significant drawbacks. It was therefore decided to start the development of an own implementation, which takes the advantages from the existing solutions, but tries to avoid the drawbacks. This paper discussed the reasoning behind this decision, describes the implementation and its characteristics, as well as the testing results. The given implementation is available as open-source project under [15].
A Gamified and Adaptive Learning System for Neurodivergent Workers in Electronic Assembling Tasks
(2020)
Learning and work-oriented assistive systems are often designed to fit the workflow of neurotypical workers. Neurodivergent workers and individuals with learning disabilities often present cognitive and sensorimotor characteristics that are better accommodated with personalized learning and working processes. Therefore, we designed an adaptive learning system that combines an augmented interaction space with user-sensitive virtual assistance to support step-by-step guidance for neurodivergent workers in electronic assembling tasks. Gamified learning elements were also included in the interface to provide self-motivation and praise whenever users progress in their learning and work achievements.
A report from the World Economic Forum (2019) stated loneliness as the third societal stressor in the world, mainly in western countries. Moreover, research shows that loneliness tends to be experienced more severely by young adults than other age groups (Rokach, 2000), which is the case of university students who face profound periods of loneliness when attending university in a new place (Diehl et al., 2018). Digital technology, especially mental health apps (MHapps), have been viewed as promising solutions to address this distress in universities, however, little evidence on this topic reveals uncertainty around how these resources impact individual well-being. Therefore, this research proposed to investigate how the gamified social mobile app Noneliness reduced loneliness rates and other associated mental health issues of students from a German university. As little work has focused on digital apps targeting loneliness, this project also proposed to describe and discuss the app’s design and development processes. A multimethod approach was adopted: literature review on high-efficacy MHapps design, gamification for mental health and loneliness interventions; User Experience Design and Human-centered Computing. Evaluations occurred according to the app’s development iterations, which assessed four versions (from prototype to Beta) through quantitative and qualitative studies with university students. The main results obtained regarding the design aspects were: users' preference for minimalistic interfaces; importance in maintaining privacy and establishing trust among users; students' willingness to use an online support space for emotional and educational support. Most used features were those related to group discussions, private chats and university social events. Preferred gamification elements were those that provided positive reinforcement to motivate social interactions (e.g. Points, Levels and Achievements). Results of a pilot randomized controlled trial with university students (N = 12), showed no statistically significant interactions in reducing loneliness among experimental group members (n = 7, x² = 3.500, p-value = 0.477, Cramer’s V = 0.27) who made continued use of the app for six weeks. On the other hand, the app showed effects of moderate magnitude on loneliness reduction in this group. The app also demonstrated relatively strong magnitude effects on other associated variables, such as depression and stress in the experimental group. In addition to motivating the conduct of further studies with larger samples, the findings point to a potential app effectiveness not only to reduce loneliness, but also other variables that may be associated with the distress.
Lithium-ion batteries exhibit slow voltage dynamics on the minute time scale that are usually associated with transport processes. We present a novel modelling approach toward these dynamics by combining physical and data-driven models into a Grey-box model. We use neural networks, in particular neural ordinary differential equations. The physical structure of the Grey-box model is borrowed from the Fickian diffusion law, where the transport domain is discretized using finite volumes. Within this physical structure, unknown parameters (diffusion coefficient, diffusion length, discretization) and dependencies (state of charge, lithium concentration) are replaced by neural networks and learnable parameters. We perform model-to-model comparisons, using as training data (a) a Fickian diffusion process, (b) a Warburg element, and (c) a resistor-capacitor circuit. Voltage dynamics during constant-current operation and pulse tests as well as electrochemical impedance spectra are simulated. The slow dynamics of all three physical models in the order of ten to 30 min are well captured by the Grey-box model, demonstrating the flexibility of the present approach.
A highly scalable IEEE802.11p communication and localization subsystem for autonomous urban driving
(2013)
The IEEE802.11p standard describes a protocol for car-to-X and mainly for car-to-car-communication. It has found its place in hardware and firmware implementations and is currently tested in various field tests. In the research project Ko-TAG, which is part of the research initiative Ko-FAS, cooperative sensor technology is developed for the support of highly autonomous driving. A secondary radar principle based on communication signals enables localization of objects with simultaneous data transmission. It mainly concentrates on the detection of pedestrians and other vulnerable road users (VRU), but also supports pre crash safety applications. Thus it is mainly targeted for the support of traffic safety applications in intra-urban scenarios. This contribution describes the Ko-TAG part of the overall initiative, which develops a subsystem to improve the real-time characteristics of IEEE802.11p needed for precise time of flight real-time localization. In doing this, it still fits into the regulatory schemes. It discusses the approach for definition and verification of the protocol design, while maintaining the close coexistence with existing IEEE802.11p subsystems. System simulations were performed and hardware was implemented. Test results are shown in the last part of the paper.
The IEEE802.11p standard describes a protocol for car-to-X and mainly for car-to-car-communication. It has found its place in hardware and firmware implementations and is currently tested in various field tests. In the research project Ko-TAG, which is part of the research initiative Ko-FAS, cooperative sensor technology is developed and its benefit for traffic safety applications is evaluated. A secondary radar principle based on communication signals enables localization of objects with simultaneous data transmission. It mainly concentrates on the detection of pedestrians and other vulnerable road users (VRU), but also supports pre crash safety applications. The Ko-TAG proposal enriches the current IEEE802.11p real-time characteristics needed for precise time-of-flight real-time localization. This contribution describes the development of a subsystem, which extends the functionality of IEEE802.11p and fits into the regulatory schemes. It discusses the approach for definition and verification of the protocol design, while maintaining the close coexistence with existing IEEE802.11p subsystems. System simulations were performed and hardware was implemented. The next step will be field measurements to verify the simulation results.
Given the looming threats of climate change and the rapid worldwide urbanization, it is a necessity to prioritize the transition towards a carbon-free built environment. This research study provides a holistic digital methodology for parametric design of urban residential buildings with regard to the Mediterranean semi-arid climate zone of Morocco in the early design phase. The morphological parameters of the urban residential buildings, namely the buildings’ typology, the distance between buildings, the urban grid’s orientation, and the window-towall ratio, are evaluated in order to identify the key combinations of passive and active solar design strategies that determine the high energy performing configurations, based on the introduced Energy Performance Index (EPI), which is the ratio between solar BIPV production to maximum available installed BIPV capacity and the normalized thermal energy needs. Through an automated processing of 2187 iterations via Grasshopper, we simulate daylight autonomy, indoor thermal comfort and solar rooftop photovoltaic and building integrated photovoltaic (BIPV) energy potential. Then, we analyze the conflicting objectives of energy efficiency measures, active solar design strategies, and indoor visual comfort in the decision-making process that supports our goal of getting closer to net zero urban residential buildings. The digital workflow showed interesting trends in reaching a balanced equilibrium between performance metrics influenced by the contrasting impact of solar exposure on indoor daylight autonomy and thermal energy demand. Furthermore, the study’s findings indicate that it is possible to achieve an annual load match exceeding 66,56 % while simultaneously ensuring an acceptable visual indoor comfort (sDA higher than 0.4). The findings also highlight the important role of the BIPV system in shifting towards the net zero energy goal, by contributing up to 30 % of the overall solar energy output and covering up to 20 % of the yearly self-consumption. Moreover, the energy balance evaluation on an hourly basis indicates that BIPV system notably enhances the daily load cover factor by up to 5.5 %, particularly in the case of slab SN typology, throughout the different seasons. Graphical representations of the yearly, monthly and hourly load matches and the hourly energy balance of the best performing configurations provide a thorough understanding of the potential evolution of the urban energy system over time as a result of the gradual integration of active solar electricity production.
A Hybrid Optoelectronic Sensor Platform with an Integrated Solution‐Processed Organic Photodiode
(2021)
Hybrid systems, unifying printed electronics with silicon‐based technology, can be seen as a driving force for future sensor development. Especially interesting are sensing elements based on printed devices in combination with silicon‐based high‐performance electronics for data acquisition and communication. In this work, a hybrid system integrating a solution‐processed organic photodiode in a silicon‐based system environment, which enables flexible device measurement and application‐driven development, is presented. For performance evaluation of the integrated organic photodiode, the measurements are compared to a silicon‐based counterpart. Therefore, the steady state response of the hybrid system is presented. Promising application scenarios are described, where a solution‐processed organic photodiode is fully integrated in a silicon system.
In recent years, predictive maintenance tasks, especially for bearings, have become increasingly important. Solutions for these use cases concentrate on the classification of faults and the estimation of the Remaining Useful Life (RUL). As of today, these solutions suffer from a lack of training samples. In addition, these solutions often require high-frequency accelerometers, incurring significant costs. To overcome these challenges, this research proposes a combined classification and RUL estimation solution based on a Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) network. This solution relies on a hybrid feature extraction approach, making it especially appropriate for low-cost accelerometers with low sampling frequencies. In addition, it uses transfer learning to be suitable for applications with only a few training samples.
Uncontrollable manufacturing variations in electrical hardware circuits can be exploited as Physical Unclonable Functions (PUFs). Herein, we present a Printed Electronics (PE)-based PUF system architecture. Our proposed Differential Circuit PUF (DiffC-PUF) is a hybrid system, combining silicon-based and PE-based electronic circuits. The novel approach of the DiffC-PUF architecture is to provide a specially designed real hardware system architecture, that enables the automatic readout of interchangeable printed DiffC-PUF core circuits. The silicon-based addressing and evaluation circuit supplies and controls the printed PUF core and ensures seamless integration into silicon-based smart systems. Major objectives of our work are interconnected applications for the Internet of Things (IoT).
We propose secure multi-party computation techniques for the distributed computation of the average using a privacy-preserving extension of gossip algorithms. While recently there has been mainly research on the side of gossip algorithms (GA) for data aggregation itself, to the best of our knowledge, the aforementioned research line does not take into consideration the privacy of the entities involved. More concretely, it is our objective to not reveal a node's private input value to any other node in the network, while still computing the average in a fully-decentralized fashion. Not revealing in our setting means that an attacker gains only minor advantage when guessing a node's private input value. We precisely quantify an attacker's advantage when guessing - as a mean for the level of data privacy leakage of a node's contribution. Our results show that by perturbing the input values of each participating node with pseudo-random noise with appropriate statistical properties (i) only a minor and configurable leakage of private information is revealed, by at the same time (ii) providing a good average approximation at each node. Our approach can be applied to a decentralized prosumer market, in which participants act as energy consumers or producers or both, referred to as prosumers.
The desire to connect more and more devices and to make them more intelligent and more reliable, is driving the needs for the Internet of Things more than ever. Such IoT edge systems require sound security measures against cyber-attacks, since they are interconnected, spatially distributed, and operational for an extended period of time. One of the most important requirements for the security in many industrial IoT applications is the authentication of the devices. In this paper, we present a mutual authentication protocol based on Physical Unclonable Functions, where challenge-response pairs are used for both device and server authentication. Moreover, a session key can be derived by the protocol in order to secure the communication channel. We show that our protocol is secure against machine learning, replay, man-in-the-middle, cloning, and physical attacks. Moreover, it is shown that the protocol benefits from a smaller computational, communication, storage, and hardware overhead, compared to similar works.
A Localization System Using Inertial Measurement Units from Wireless Commercial Handheld Devices
(2013)
This paper describes a newly developed technology for the calculation of trajectories of mobile objects, which is based on commercially available sensors being integrated into modern mobile phones and other gadgets. First, a step counting technique was implemented. Second, a novel step length estimator is proposed. These two algorithms utilize the data from accelerometer sensor only. Third, the heading information was obtained using a gyroscope with complementary filter in quaternion form. The combined algorithm was implemented on a low-power ARM processor to provide the trajectory points relative to an initial point. The proposed technique was tested by 10 subjects, in different shoes with different paces. The dependence of the performance of the technology on the attaching point of the mobile device is weak. The proposed algorithms have better balance and estimation accuracy and depend in less degree on the variety in physical parameters of people in comparison with the existing techniques. In experiments inertial measurement units were mounted in different places, i.e. in the hand, in trousers or in T-shirt pockets. The return position error did not exceed 5% of the total travelled distance for all performed tests.
A novel Bluetooth Low Energy advertising scan algorithm is presented for hybrid radios that are additionally capable to measure energy on Bluetooth channels, e.g. as they would need to be compliant with IEEE 802.15.4. Scanners applying this algorithm can achieve a low latency whilst consuming only a fraction of the power that existing mechanisms can achieve at a similar latency. Furthermore, the power consumption can scale with the incoming network traffic and in contrast to the existing mechanisms, scanners can operate without any frame loss given ideal network conditions. The algorithm does not require any changes to advertisers, hence, stays compatible with existing devices. Performance evaluated via simulation and experiments on real hardware shows a 37 percent lower power consumption compared to the best existing scan setting while even achieving a slightly lower latency which proves that this algorithm can be used to improve the quality of service of connection-less Bluetooth communication or reduce the connection establishment time of connection-oriented communication.
Cryptographic protection of messages requires frequent updates of the symmetric cipher key used for encryption and decryption, respectively. Protocols of legacy IT security, like TLS, SSH, or MACsec implement rekeying under the assumption that, first, application data exchange is allowed to stall occasionally and, second, dedicated control messages to orchestrate the process can be exchanged. In real-time automation applications, the first is generally prohibitive, while the second may induce problematic traffic patterns on the network. We present a novel seamless rekeying approach, which can be embedded into cyclic application data exchanges. Although, being agnostic to the underlying real-time communication system, we developed a demonstrator emulating the widespread industrial Ethernet system PROFINET IO and successfully use this rekeying mechanism.
In this paper, the multiaxial formulation of a mechanism-based model for fatigue life prediction is presented whichcan be applied to low-cycle fatigue (LCF) and thermomechanical fatigue (TMF) problems in which high-cycle fa-tigue loadings are superimposed. The model assumes that crack growth is the lifetime limiting mechanism and thatthe crack advance in a loading cycleda/dNcorrelates with the cyclic crack-tip opening displacement ΔCTOD.The multiaxial formulation makes use of fracture mechanics solutions and thus, does not need additional modelparameters quantifying the effect of the multiaxiality. Furthermore, the model includes contributions of HCF on ΔCTODand assesses the effect of the direction of the HCF loadings with respect to LCF or TMF loadings inthe life prediction. The model is implemented into the finite-element program ABAQUS. It is applied to predictthe fatigue life of a thermomechanically loaded notched specimen that should represent the situation between theinlet and outlet bore holes of cylinder heads. A good correlation of the predicted and the measured fatigue lives isobtained.
High temperature components in internal combustion engines and exhaust systems must withstand severe mechanical and thermal cyclic loads throughout their lifetime. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermomechanical fatigue (TMF) of the material. Analytical tools are increasingly employed by designers and engineers for component durability assessment well before any hardware testing. The DTMF model for TMF life prediction, which assumes that micro-crack growth is the dominant damage mechanism, is capable of providing reliable predictions for a wide range of high-temperature components and materials in internal combustion engines. Thus far, the DTMF model has employed a local approach where surface stresses, strains, and temperatures are used to compute damage for estimating the number of cycles for a small initial defect or micro-crack to reach a critical length. In the presence of significant gradients of stresses, strains, and temperatures, the use of surface field values could lead to very conservative estimates of TMF life when compared with reported lives from hardware testing. As an approximation of gradient effects, a non-local approach of the DTMF model is applied. This approach considers through-thickness fields where the micro-crack growth law is integrated through the thickness considering these variable fields. With the help of software tools, this method is automated and applied to components with complex geometries and fields. It is shown, for the TMF life prediction of a turbocharger housing, that the gradient correction using the non-local approach leads to more realistic life predictions and can distinguish between surface cracks that may arrest or propagate through the thickness and lead to component failure.
This paper presents a streaming-based E-Learning environment where closer integration between learning and work is achieved by integrating multimedia services into manufacturing processes. It contains a comprehensive and detailed explanation of the proposed E-Learning streaming framework, especially the adaption of streaming services to mobile environments. We first analyze several scenarios where E-Learning streaming services can be integrated into manufacturing processes. To allow systematic and tailor-made integration, we develop a model and a specification language for E-Learning streaming services and apply the model using practical scenarios from real manufacturing processes. Adaption of multimedia streaming services to mobile devices is discussed based on Synchronized Multimedia Integration Language (SMIL). Last, we comment on the benefits of using E-Learning streaming services as part of manufacturing processes and analyze the acceptance of the developed system. The key components of our E-Learning environment are 1) an xml based streaming service specification language, 2) adaption of multimedia E-Learning services to mobile environments, and 3) Web Services for searching, registration, and creation of E-Learning streaming services.
This paper presents a method for supporting the application of Additive Tooling (AT)-based validation environments in integrated product development. Based on a case study, relevant process steps, activities and possible barriers in the realisation of an injection-moulded product are identified and analysed. The aim of the method is to support the target-oriented application of Additive Tooling to obtain physical prototypes at an early stage and to shorten validation cycles.
When designing and installing Indoor Positioning Systems, several interrelated tasks have to be solved to find an optimum placement of the Access Points. For this purpose, a mathematical model for a predefined number of access points indoors is presented. Two iterative algorithms for the minimization of localization error of a mobile object are described. Both algorithms use local search technique and signal level probabilities. Previously registered signal strengths maps were used in computer simulation.
Quantifying the midsole material characteristics of athletic footwear is a standard task in footwear research and development. Current material testing protocols primarily focus on the determination of cushioning properties of the heel region or the quantification of the midsole properties as one assembly. However, midsoles possess different spatial material properties that have not been quantified from previous methodologies. Therefore, new material testing methods are required to quantify the local material response of athletic footwear. We developed a cyclical force-controlled material testing protocol for the determination of non-homogeneously distributed material stiffness with a high spatial resolution. In five prototype shoes varying in their stiffness distribution, we found that the material properties can be reliably measured across the midsole. Furthermore, we observed a characteristic non-linear material response regardless of the midsole location. We found that the material stiffness increased with an increase of the applied force and that this effect is further intensified by higher testing cycles. Additionally, the obtained midsole stiffness depends on the geometry of the midsole. We explored different approaches to reduce the measurement time of the testing protocol and found that the number of measurements can be reduced by 70% using 2 D-interpolation procedures. Determining the spatial material properties of midsoles needs to be considered to understand foot-shoe interactions. Furthermore, this measurement protocol can be used for quality control within the footwear and can be adapted for considering the effects of different running styles or speeds on ground force application characteristics.
In 4D printing an additively manufactured component is given the ability to change its shape or function under the influence of an external stimulus. To achieve this, special smart materials are used that are able to react to external stimuli in a specific way. So far, a number of different stimuli have already been investigated and initial applications have been impressively demonstrated, such as self-folding bodies and simple grippers. However, a methodical specification for the selection of the stimuli and their implementation was not yet in the foreground of the development.
The focus of this work is therefore to develop a methodical approach with which the technology of 4DP can be used in a solution- and application-oriented manner. The developed approach is based on the conventional design methodology for product development to solve given problems in a structured way. This method is extended by specific approaches under consideration of the 4D printing and smart materials.
To illustrate the developed method, it is implemented in practice using a problem definition in the form of an application example. In this example, which represents the recovery of an object from a difficult-to-access environment, the individual functions of positioning, gripping and extraction are implemented using 4D printing. The material extrusion process is used for additive manufacturing of all components of the example. Finally, the functions are successfully tested. The developed approach offers an innovative and methodical approach to systematically solve technical complex problems using 4DP and smart materials.
Uptakes of 9.2 mmol g−1 (40.5 wt %) for CO2 at 273 K/0.1 MPa and 15.23 mmol g−1 (3.07 wt %) for H2 at 77 K/0.1 MPa are among the highest reported for metal–organic frameworks (MOFs) and are found for a novel, highly microporous copper‐based MOF (see picture; Cu turquoise, O red, N blue). Thermal analyses show a stability of the flexible framework up to 250 °C.
Metal–organic frameworks (MOFs) as highly porous materials have gained increasing interest because of their distinct adsorption properties.1–3 They exhibit a high potential for applications in gas separation and storage,4 as sensors5 as well as in heterogeneous catalysis.6 In the last few years, the H2 storage capacity of MOFs has been considerably increased. Mesoporous MOFs show high adsorption capacities for CH4, CO2, and H2 at high pressures.2, 3, 7–10 To increase the uptake of H2 and CO2 by physisorption at ambient pressure, adsorbents with small micropores as well as high specific surface areas and micropore volumes are required.11, 12 Such microporous materials seem to be more appropriate for gas‐mixture separation by physisorption than mesoporous materials. For gas separation in MOFs the interactions between the fluid adsorptive and “open metal sites” (coordinatively unsaturated binding sites) or the ligands are regarded as important.13 Industrial processes, such as natural‐gas purification or biogas upgrading, can be improved with those materials during a vapor‐pressure swing adsorption cycle (VPSA cycle) or a temperature swing adsorption cycle (TSA cycle).14 The microporous MOF series CPO‐27‐M (M=Mg, Co, Ni, Zn), for example, shows very high CO2 uptakes at low pressures (<0.1 MPa).15, 16 Concerning H2 adsorption, the microporous MOF PCN‐12 offers with 3.05 wt % the highest uptake at ambient pressure and 77 K reported to date.17
Herein, we present a novel microporous copper‐based MOF equation image[Cu(Me‐4py‐trz‐ia)] (1; Me‐4py‐trz‐ia2−=5‐(3‐methyl‐5‐(pyridin‐4‐yl)‐4H‐1,2,4‐triazol‐4‐yl)isophthalate) with extraordinarily high CO2 and H2 uptakes at ambient pressure, the H2 uptake being similar to that in PCN‐12. The ligand Me‐4py‐trz‐ia2−, which can be obtained from cheap starting materials by a three‐step synthesis in good yield, combines carboxylate, triazole, and pyridine functions and is adopted from a recently presented series of linkers,18 for which up to now only a few coordination polymers are known.