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Solar sails provide ignificant advantages over other low-thrust propulsion systems because they produce thrust by the momentum exchange from solar radiation pressure (SRP) and thus do not consume any propellant.The force exerted on a very thin sail foil basically depends on the light incidence angle. Several analytical SRP force models that describe the SRP force acting on the sail have been established since the 1970s. All the widely used models use constant optical force coefficients of the reflecting sail material. In 2006,MENGALI et al. proposed a refined SRP force model that takes into account the dependancy of the force coefficients on the light incident angle,the sail’s distance from the sun (and thus the sail emperature) and the surface roughness of the sail material [1]. In this paper, the refined SRP force model is compared to the previous ones in order to identify the potential impact of the new model on the predicted capabilities of solar sails in performing low-cost interplanetary space missions. All force models have been implemented within InTrance, a global low-thrust trajectory optimization software utilizing evolutionary neurocontrol [2]. Two interplanetary rendezvous missions, to Mercury and the near-Earth asteroid 1996FG3, are investigated. Two solar sail performances in terms of characteristic acceleration are examined for both scenarios, 0.2 mm/s2 and 0.5 mm/s2, termed “low” and “medium” sail performance. In case of the refined SRP model, three different values of surface roughness are chosen, h = 0 nm, 10 nm and 25 nm. The results show that the refined SRP force model yields shorter transfer times than the standard model.
Clearance of blood components and fluid drainage play a crucial role in subarachnoid hemorrhage (SAH) and post hemorrhagic hydrocephalus (PHH). With the involvement of interstitial fluid (ISF) and cerebrospinal fluid (CSF), two pathways for the clearance of fluid and solutes in the brain are proposed. Starting at the level of capillaries, flow of ISF follows along the basement membranes in the walls of cerebral arteries out of the parenchyma to drain into the lymphatics and CSF [1]–[3]. Conversely, it is shown that CSF enters the parenchyma between glial and pial basement membranes of penetrating arteries [4]–[6]. Nevertheless, the involved structures and the contribution of either flow pathway to fluid balance between the subarachnoid space and interstitial space remains controversial. Low frequency oscillations in vascular tone are referred to as vasomotion and corresponding vasomotion waves are modeled as the driving force for flow of ISF out of the parenchyma [7]. Retinal vessel analysis (RVA) allows non-invasive measurement of retinal vessel vasomotion with respect to diameter changes [8]. Thus, the aim of the study is to investigate vasomotion in RVA signals of SAH and PHH patients.
Using optimization to design a renewable energy system has become a computationally demanding task as the high temporal fluctuations of demand and supply arise within the considered time series. The aggregation of typical operation periods has become a popular method to reduce effort. These operation periods are modelled independently and cannot interact in most cases. Consequently, seasonal storage is not reproducible. This inability can lead to a significant error, especially for energy systems with a high share of fluctuating renewable energy. The previous paper, “Time series aggregation for energy system design: Modeling seasonal storage”, has developed a seasonal storage model to address this issue. Simultaneously, the paper “Optimal design of multi-energy systems with seasonal storage” has developed a different approach. This paper aims to review these models and extend the first model. The extension is a mathematical reformulation to decrease the number of variables and constraints. Furthermore, it aims to reduce the calculation time while achieving the same results.
Reliable methods for automatic readability assessment have the potential to impact a variety of fields, ranging from machine translation to self-informed learning. Recently, large language models for the German language (such as GBERT and GPT-2-Wechsel) have become available, allowing to develop Deep Learning based approaches that promise to further improve automatic readability assessment. In this contribution, we studied the ability of ensembles of fine-tuned GBERT and GPT-2-Wechsel models to reliably predict the readability of German sentences. We combined these models with linguistic features and investigated the dependence of prediction performance on ensemble size and composition. Mixed ensembles of GBERT and GPT-2-Wechsel performed better than ensembles of the same size consisting of only GBERT or GPT-2-Wechsel models. Our models were evaluated in the GermEval 2022 Shared Task on Text Complexity Assessment on data of German sentences. On out-of-sample data, our best ensemble achieved a root mean squared error of 0:435.
Assessment of RF Safety of Transmit Coils at 7 Tesla by Experimental and Numerical Procedures (490.)
(2012)
The vaginal prolapse after hysterectomy (removal of the uterus) is often associated with the prolapse of the vaginal vault, rectum, bladder, urethra or small bowel. Minimally
invasive surgery such as laparoscopic sacrocolpopexy and pectopexy are widely performed for the treatment of the vaginal prolapse with weakly supported vaginal vault after hysterectomy using prosthetic mesh implants to support (or strengthen) lax apical ligaments. Implants of different shape, size and polymers are selected depending on the patient’s anatomy and the surgeon’s preference. In this computational study on pectopexy, DynaMesh®-PRP soft, GYNECARE GYNEMESH® PS Nonabsorbable PROLENE® soft and Ultrapro® are tested in a 3D finite element model of the female pelvic floor. The mesh model is implanted into the extraperitoneal space and sutured to the vaginal stump with a bilateral fixation to the iliopectineal ligament at both sides. Numerical simulations are conducted at rest, after surgery and during Valsalva maneuver with weakened tissues modeled by reduced tissue stiffness. Tissues and prosthetic meshes are modeled as incompressible, isotropic hyperelastic materials. The positions of the organs are calculated with respect to the pubococcygeal line (PCL) for female pelvic floor at rest, after repair and during Valsalva maneuver using the three meshes.
The structure of the female pelvic floor (PF) is an inter-related system of bony pelvis,muscles, pelvic organs, fascias, ligaments, and nerves with multiple functions. Mechanically, thepelvic organ support system are of two types: (I) supporting system of the levator ani (LA) muscle,and (II) the suspension system of the endopelvic fascia condensation [1], [2]. Significantdenervation injury to the pelvic musculature, depolimerization of the collagen fibrils of the softvaginal hammock, cervical ring and ligaments during pregnancy and vaginal delivery weakens thenormal functions of the pelvic floor. Pelvic organ prolapse, incontinence, sexual dysfunction aresome of the dysfunctions which increases progressively with age and menopause due toweakened support system according to the Integral theory [3]. An improved 3D finite elementmodel of the female pelvic floor as shown in Fig. 1 is constructed that: (I) considers the realisticsupport of the organs to the pelvic side walls, (II) employs the improvement of our previous FEmodel [4], [5] along with the patient based geometries, (III) incorporates the realistic anatomy andboundary conditions of the endopelvic (pubocervical and rectovaginal) fascia, and (IV) considersvarying stiffness of the endopelvic fascia in the craniocaudal direction [3]. Several computationsare carried out on the presented computational model with healthy and damaged supportingtissues, and comparisons are made to understand the physiopathology of the female PF disorders.
The utilization of phase change material (PCM) for latent heat storage and thermal control of spacecraft has been demonstrated in the past in few missions only. One limiting factor was the fact that all concepts developed so far envisioned the PCM to be applied as an additional capacitor, encapsulated in its own housing, leading to mass, efficiency and accommodation challenges. Recently, the application of PCM within the scan cavity of a GEOS type satellite has been suggested, in order to tackle thermal issues due to direct sun intrusion (Choi, M., 2014). However, the application of PCM in such complex mechanical structures is extremely challenging. A new concept to tackle this issue is currently under development at the FH Aachen University of Applied Sciences. The concept "Infused Thermal Solutions (ITS)" is based on the idea to 3D print metallic structures in their regular functional shape, but double walled with internal lattice support structures, allowing the infusion of a PCM layer directly into the voids and eliminating the need for additional parts and interfaces. Together with OHB System, FH Aachen theoretically studied the application of this technology to the Meteosat Third Generation (MTG) Infra-Red Sounder (IRS) instrument. The study focuses on the scan cavity and entrance baffling assembly (EBA) of the IRS. It consists of thermal analyses, 3D-redesign and bread boarding of a scaled and PCM infused EBA version. In the thermal design of the alternative EBA, PCM was applied directly into the EBA, simulating the worst hot case sun intrusion of the mission. By applying 4kg of PCM (to a 60kg baffle) the EBA temperature excursions during sun intrusion were limited from 140K to 30K, leading to a significant thermo-opto-elastic performance gain. This paper introduces the ITS concept development status.
The continuing growth of scientific publications raises the question how research processes can be digitalized and thus realized more productively. Especially in information technology fields, research practice is characterized by a rapidly growing volume of publications. For the search process various information systems exist. However, the analysis of the published content is still a highly manual task. Therefore, we propose a text analytics system that allows a fully digitalized analysis of literature sources. We have realized a prototype by using EBSCO Discovery Service in combination with IBM Watson Explorer and demonstrated the results in real-life research projects. Potential addressees are research institutions, consulting firms, and decision-makers in politics and business practice.
After a brief introduction of conventional laboratory structures, this work focuses on an innovative and universal approach for a setup of a training laboratory for electric machines and drive systems. The novel approach employs a central 48 V DC bus, which forms the backbone of the structure. Several sets of DC machine, asynchronous machine and synchronous machine are connected to this bus. The advantages of the novel system structure are manifold, both from a didactic and a technical point of view: Student groups can work on their own performance level in a highly parallelized and at the same time individualized way. Additional training setups (similar or different) can easily be added. Only the total power dissipation has to be provided, i.e. the DC bus balances the power flow between the student groups. Comparative results of course evaluations of several cohorts of students are shown.
Hypertension describes the pathological increase of blood pressure, which is most commonly associated with the increase of vascular wall stiffness [1]. Referring to the “Deutsche Bluthochdruck Liga” this pathology shows a growing trend in our aging society. In order to find novel pharmacological and probably personalized treatments, we want to present a functional approach to study biomechanical properties of a human aortic vascular model.
In this method review we will give an overview of recent studies which were carried out with the CellDrum technology [2] and underline the added value to already existing standard procedures known from the field of physiology.
Herein described CellDrum technology is a system to measure functional mechanical properties of cell monolayers and thin tissue constructs in-vitro. Additionally, the CellDrum enables to elucidate the mechanical response of cells to pharmacological drugs, toxins and vasoactive agents. Due to its highly flexible polymer support, cells can also be mechanically stimulated by steady and cyclic biaxial stretching.
This paper describes the concept of an innovative, interdisciplinary, user-oriented earthquake warning and rapid response system coupled with a structural health monitoring system (SHM), capable to detect structural damages in real time. The novel system is based on interconnected decentralized seismic and structural health monitoring sensors. It is developed and will be exemplarily applied on critical infrastructures in Lower Rhine Region, in particular on a road bridge and within a chemical industrial facility. A communication network is responsible to exchange information between sensors and forward warnings and status reports about infrastructures’health condition to the concerned recipients (e.g., facility operators, local authorities). Safety measures such as emergency shutdowns are activated to mitigate structural damages and damage propagation. Local monitoring systems of the infrastructures are integrated in BIM models. The visualization of sensor data and the graphic representation of the detected damages provide spatial content to sensors data and serve as a useful and effective tool for the decision-making processes after an earthquake in the region under consideration.
Combined with the use of renewable energy sources for
its production, Hydrogen represents a possible alternative gas
turbine fuel for future low emission power generation. Due to
its different physical properties compared to other fuels such
as natural gas, well established gas turbine combustion
systems cannot be directly applied for Dry Low NOx (DLN)
Hydrogen combustion. This makes the development of new
combustion technologies an essential and challenging task
for the future of hydrogen fueled gas turbines.
The newly developed and successfully tested “DLN
Micromix” combustion technology offers a great potential to
burn hydrogen in gas turbines at very low NOx emissions.
Aiming to further develop an existing burner design in terms
of increased energy density, a redesign is required in order to
stabilise the flames at higher mass flows and to maintain low
emission levels.
For this purpose, a systematic design exploration has
been carried out with the support of CFD and optimisation
tools to identify the interactions of geometrical and design
parameters on the combustor performance. Aerodynamic
effects as well as flame and emission formation are observed
and understood time- and cost-efficiently. Correlations
between single geometric values, the pressure drop of the
burner and NOx production have been identified as a result.
This numeric methodology helps to reduce the effort of
manufacturing and testing to few designs for single
validation campaigns, in order to confirm the flame stability
and NOx emissions in a wider operating condition field.
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through the presentation layer of existing application systems. For this simple emulation of user input and output by software robots, no changes of the systems and architecture is required. However, considering strategic aspects of aligning business and technology on an enterprise level as well as the growing capabilities of RPA driven by artificial intelligence, interrelations between RPA and Enterprise Architecture (EA) become visible and pose new questions. In this paper we discuss the relationship between RPA and EA in terms of perspectives and implications. As workin- progress we focus on identifying new questions and research opportunities related to RPA and EA.
This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.
The Effect of Openings on Out-of-Plane Capacity of Masonry Infilled Reinforced Concrete Frames
(2018)
Digital twins enable the modeling and simulation of real-world entities (objects, processes or systems), resulting in improvements in the associated value chains. The emerging field of quantum computing holds tremendous promise forevolving this virtualization towards Quantum (Digital) Twins (QDT) and ultimately Quantum Twins (QT). The quantum (digital) twin concept is not a contradiction in terms - but instead describes a hybrid approach that can be implemented using the technologies available today by combining classicalcomputing and digital twin concepts with quantum processing. This paperpresents the status quo of research and practice on quantum (digital) twins. It alsodiscuses their potential to create competitive advantage through real-timesimulation of highly complex, interconnected entities that helps companies better
address changes in their environment and differentiate their products andservices.
Energy-efficient components do not automatically lead to energy-efficient systems. Technical Operations Research (TOR) shifts the focus from the single component to the system as a whole and finds its optimal topology and operating strategy simultaneously. In previous works, we provided a preselected construction kit of suitable components for the algorithm. This approach may give rise to a combinatorial explosion if the preselection cannot be cut down to a reasonable number by human intuition. To reduce the number of discrete decisions, we integrate laws derived from similarity theory into the optimization model. Since the physical characteristics of a production series are similar, it can be described by affinity and scaling laws. Making use of these laws, our construction kit can be modeled more efficiently: Instead of a preselection of components, it now encompasses whole model ranges. This allows us to significantly increase the number of possible set-ups in our model. In this paper, we present how to embed this new formulation into a mixed-integer program and assess the run time via benchmarks. We present our approach on the example of a ventilation system design problem.
In times of planned obsolescence the demand for sustainability keeps growing. Ideally, a technical system is highly reliable, without failures and down times due to fast wear of single components. At the same time, maintenance should preferably be limited to pre-defined time intervals. Dispersion of load between multiple components can increase a system’s reliability and thus its availability inbetween maintenance points. However, this also results in higher investment costs and additional efforts due to higher complexity. Given a specific load profile and resulting wear of components, it is often unclear which system structure is the optimal one. Technical Operations Research (TOR) finds an optimal structure balancing availability and effort. We present our approach by designing a hydrostatic transmission system.
Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems
In this paper research activities developed within the FutureCom project are presented. The project, funded by the European Metrology Programme for Innovation and Research (EMPIR), aims at evaluating and characterizing: (i) active devices, (ii) signal- and power integrity of field programmable gate array (FPGA) circuits, (iii) operational performance of electronic circuits in real-world and harsh environments (e.g. below and above ambient temperatures and at different levels of humidity), (iv) passive inter-modulation (PIM) in communication systems considering different values of temperature and humidity corresponding to the typical operating conditions that we can experience in real-world scenarios. An overview of the FutureCom project is provided here, then the research activities are described.
Clinical assessment of newly developed sensors is important for ensuring their validity. Comparing recordings of emerging electrocardiography (ECG) systems to a reference ECG system requires accurate synchronization of data from both devices. Current methods can be inefficient and prone to errors. To address this issue, three algorithms are presented to synchronize two ECG time series from different recording systems: Binned R-peak Correlation, R-R Interval Correlation, and Average R-peak Distance. These algorithms reduce ECG data to their cyclic features, mitigating inefficiencies and minimizing discrepancies between different recording systems. We evaluate the performance of these algorithms using high-quality data and then assess their robustness after manipulating the R-peaks. Our results show that R-R Interval Correlation was the most efficient, whereas the Average R-peak Distance and Binned R-peak Correlation were more robust against noisy data.