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Gearboxes are mechanical transmission systems that provide speed and torque conversions from a rotating power source. Being a central element of the drive train, they are relevant for the efficiency and durability of motor vehicles. In this work, we present a new approach for gearbox design: Modeling the design problem as a mixed-integer nonlinear program (MINLP) allows us to create gearbox designs from scratch for arbitrary requirements and—given enough time—to compute provably globally optimal designs for a given objective. We show how different degrees of freedom influence the runtime and present an exemplary solution.
The term ocular rigidity is widely used in clinical ophthalmology. Generally it is assumed as a resistance of the whole eyeball to mechanical deformation and relates to biomechanical properties of the eye and its tissues. Basic principles and formulas for clinical tonometry, tonography and pulsatile ocular blood flow measurements are based on the concept of ocular rigidity. There is evidence for altered ocular rigidity in aging, in several eye diseases and after eye surgery. Unfortunately, there is no consensual view on ocular rigidity: it used to make a quite different sense for different people but still the same name. Foremost there is no clear consent between biomechanical engineers and ophthalmologists on the concept. Moreover ocular rigidity is occasionally characterized using various parameters with their different physical dimensions. In contrast to engineering approach, clinical approach to ocular rigidity claims to characterize the total mechanical response of the eyeball to its deformation without any detailed considerations on eye morphology or material properties of its tissues. Further to the previous chapter this section aims to describe clinical approach to ocular rigidity from the perspective of an engineer in an attempt to straighten out this concept, to show its advantages, disadvantages and various applications.
Pure analytical or experimental methods can only find a control strategy for technical systems with a fixed setup. In former contributions we presented an approach that simultaneously finds the optimal topology and the optimal open-loop control of a system via Mixed Integer Linear Programming (MILP). In order to extend this approach by a closed-loop control we present a Mixed Integer Program for a time discretized tank level control. This model is the basis for an extension by combinatorial decisions and thus for the variation of the network topology. Furthermore, one is able to appraise feasible solutions using the global optimality gap.
The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design.
Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.
Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.
In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.
This chapter describes three general strategies to master uncertainty in technical systems: robustness, flexibility and resilience. It builds on the previous chapters about methods to analyse and identify uncertainty and may rely on the availability of technologies for particular systems, such as active components. Robustness aims for the design of technical systems that are insensitive to anticipated uncertainties. Flexibility increases the ability of a system to work under different situations. Resilience extends this characteristic by requiring a given minimal functional performance, even after disturbances or failure of system components, and it may incorporate recovery. The three strategies are described and discussed in turn. Moreover, they are demonstrated on specific technical systems.
Concentrating Solar Power
(2021)
The focus of this chapter is the production of power and the use of the heat produced from concentrated solar thermal power (CSP) systems.
The chapter starts with the general theoretical principles of concentrating systems including the description of the concentration ratio, the energy and mass balance. The power conversion systems is the main part where solar-only operation and the increase in operational hours.
Solar-only operation include the use of steam turbines, gas turbines, organic Rankine cycles and solar dishes. The operational hours can be increased with hybridization and with storage.
Another important topic is the cogeneration where solar cooling, desalination and of heat usage is described.
Many examples of commercial CSP power plants as well as research facilities from the past as well as current installed and in operation are described in detail.
The chapter closes with economic and environmental aspects and with the future potential of the development of CSP around the world.
Magnetic nanoparticle relaxation in biomedical application: focus on simulating nanoparticle heating
(2021)
The recent advances in microbiology have shed light on understanding the role of vitamins beyond the nutritional range. Vitamins are critical in contributing to healthy biodiversity and maintaining the proper function of gut microbiota. The sharing of vitamins among bacterial populations promotes stability in community composition and diversity; however, this balance becomes disturbed in various pathologies. Here, we overview and analyze the ability of different vitamins to selectively and specifically induce changes in the intestinal microbial community. Some schemes and regularities become visible, which may provide new insights and avenues for therapeutic management and functional optimization of the gut microbiota.
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.
This chapter shows that nanomaterials obtained by high-temperature carbonization of inexpensive plant raw material such as rice husk, grape seeds, and walnut shells can serve as a basis for the production of highly efficient microbial drugs, biodestructors, biosorbents, and biocatalysts, which are promising for the remediation of the ecosystem contaminated with heavy and radioactive metals, oil and oil products. A strong interest in engineering zymology is dictated by the necessity to address the issues of monitoring enzymatic processes, treatment, and diagnosis of a number of common human diseases, environmental pollution, quality control of pharmaceuticals and food. Nanomaterials obtained by high-temperature carbonization of cheap plant raw material such as-rice husks, grape seeds and walnut shells, can serve as a basis for creating of highly effective microbial preparations-biodestructors, biosorbents and biocatalysts, which are promising for the use of contaminated ecosystems, and for restoration of human intestine microecology.
Activated carbons are known as excellent adsorbents. Their applications include the adsorptive removal of color, odor, taste, undesirable organic and inorganic pollutants from drinking and waste water; air purification in inhabited spaces; purification of many chemicals, pharmaceutical products and many others. This chapter elucidates the role of normal microflora in the maintenance of human health and presents materials on possible clinical displays of microecological infringements and ways of their correction. It presents new developments concerning new probiotics with immobilized Lactobacillus and Bacillus. The chapter considers the mechanisms of the intestine disbacteriosis correction by sorbed probiotics. It demonstrates the advantages and creation prospects of immobilized probiotics developed on the basis of carbonized rice husk. There are great prospects for the development of medical biotechnology due to use of carbon sorbents with a nanostructured surface. Microbial communities form a biocenosis of the biotope and together with the host organism create permanent or temporary ecosystems.
The treatment of septic wounds with curative dressings based on biocomposites containing sage and marigold phytoextracts was effective in in vitro and in vivo experiments. These dressings caused the purification of the wound surface from purulent-necrotic masses three days earlier than in the other experimental groups. The consequence of an increase in incidents of severe course of the wound and the observed tendency to increase the number of adverse effects is the development of long-term recurrent wound processes. To treat purulent wounds, the following tactics were used: The purulent wounds of animals were covered with the examined wound dressing, and then the next day samples were taken, the procedure was performed once in 2 days. To obtain the active nanostructured sorbents such as carbonized rice husks, they are functionalized with biologically active components possessing antimicrobial, anti-inflammatory, antitoxic, immunomodulating, antiallergic and other types of properties.
Biocomposite Materials Based on Carbonized Rice Husk in Biomedicine and Environmental Applications
(2020)
This chapter describes the prospects for biomedical and environmental engineering applications of heterogeneous materials based on nanostructured carbonized rice husk. Efforts in engineering enzymology are focused on the following directions: development and optimization of immobilization methods leading to novel biotechnological and biomedical applications; construction of biocomposite materials based on individual enzymes, multi-enzyme complexes and whole cells, targeted on realization of specific industrial processes. Molecular biological and biochemical studies on cell adhesion focus predominantly on identification, isolation and structural analysis of attachment-responsible biological molecules and their genetic determinants. The chapter provides a short overview of applications of the biocomposite materials based of nanostructured carbonized adsorbents. It emphasizes that further studies and better understanding of the interactions between CNS and microbial cells are necessary. The future use of living cells as biocatalysts, especially in the environmental field, needs more systematic investigations of the microbial adsorption phenomenon.
Additive manufacturing (AM) works by creating objects layer by layer in a manner similar to a 2D printer with the “printed” layers stacked on top of each other. The layer-wise manufacturing nature of AM enables fabrication of freeform geometries which cannot be fabricated using conventional manufacturing methods as a one part. Depending on how each layer is created and bonded to the adjacent layers, different AM methods have been developed. In this chapter, the basic terms, common materials, and different methods of AM are described, and their potential applications are discussed.
Rapid Tooling
(2019)
The adoption of the Digital Health Transformation is a tremendous paradigm change in health organizations, which is not a trivial process in reality. For that reason, in this chapter, it is proposed a methodology with the objective to generate a changing culture in healthcare organisations. Such a change culture is essential for the successful implementation of any supporting methods like Interactive Process Mining. It needs to incorporate (mostly) new ways of team-based and evidence-based approaches for solving structural problems in a digital healthcare environment.
The chapter initially provides a summary of the contents of Eurocode 8, its aim being to offer both to the students and to practising engineers an easy introduction into the calculation and dimensioning procedures of this earthquake code. Specifically, the general rules for earthquake-resistant structures, the definition of design response spectra taking behaviour and importance factors into account, the application of linear and non-linear calculation methods and the structural safety verifications at the serviceability and ultimate limit state are presented. The application of linear and non-linear calculation methods and corresponding seismic design rules is demonstrated on practical examples for reinforced concrete, steel and masonry buildings. Furthermore, the seismic assessment of existing buildings is discussed and illustrated on the example of a typical historical masonry building in Italy. The examples are worked out in detail and each step of the design process, from the preliminary analysis to the final design, is explained in detail.
Industrial units consist of the primary load-carrying structure and various process engineering components, the latter being by far the most important in financial terms. In addition, supply structures such as free-standing tanks and silos are usually required for each plant to ensure the supply of material and product storage. Thus, for the earthquake-proof design of industrial plants, design and construction rules are required for the primary structures, the secondary structures and the supply structures. Within the framework of these rules, possible interactions of primary and secondary structures must also be taken into account. Importance factors are used in seismic design in order to take into account the usually higher risk potential of an industrial unit compared to conventional building structures. Industrial facilities must be able to withstand seismic actions because of possibly wide-ranging damage consequences in addition to losses due to production standstill and the destruction of valuable equipment. The chapter presents an integrated concept for the seismic design of industrial units based on current seismic standards and the latest research results. Special attention is devoted to the seismic design of steel thin-walled silos and tank structures.
The problem of creation and use of sorption materials is of current interest for the practice of the modern medicine and agriculture. Practical importance is production of a biostimulant using a carbon sorbent for a significant increase in productivity, which is very relevant for the regions of Kazakhstan. It is known that a plant phytohormone—fusicoccin—in nanogram concentrations transforms cancer cells to the state of apoptosis. In this regard, there is a scientific practical interest in the development of a highly efficient method for producing fusicoccin from extract of germinated wheat seeds. According to the results of computer modeling, cleaning composite components of fusicoccin using microporous carbon adsorbents not suitable as the size of the molecule of fusicoccin more than micropores and the optimum pore size for purification of constituents of fusicoccin was determined by computer simulation.
The increasing complexity of Advanced Driver Assistance Systems (ADAS) presents a challenging task to validate safe and reliable performance of these systems under varied conditions. The test and validation of ADAS/AD with real test drives, although important, involves huge costs and time. Simulation tools provide an alternative with the added advantage of reproducibility but often use ideal sensors, which do not reflect real sensor output accurately. This paper presents a new validation methodology using fault injection, as recommended by the ISO 26262 standard, to test software and system robustness. In our work, we investigated and developed a tool capable of inserting faults at different software and system levels to verify its robustness. The scope of this paper is to cover the fault injection test for the Visteon’s DriveCore™ system, a centralized domain controller for Autonomous driving which is sensor agnostic and SoC agnostic. With this new approach, the validation of safety monitoring functionality and its behavior can be tested using real-world data instead of synthetic data from simulation tools resulting in having better confidence in system performance before proceeding with in-vehicle testing.
Searching optimal continuous-thrust trajectories is usually a difficult and time-consuming task. The solution quality of traditional optimal-control methods depends strongly on an adequate initial guess because the solution is typically close to the initial guess, which may be far from the (unknown) global optimum. Evolutionary neurocontrol attacks continuous-thrust optimization problems from the perspective of artificial intelligence and machine learning, combining artificial neural networks and evolutionary algorithms. This chapter describes the method and shows some example results for single- and multi-phase continuous-thrust trajectory optimization problems to assess its performance. Evolutionary neurocontrol can explore the trajectory search space more exhaustively than a human expert can do with traditional optimal-control methods. Especially for difficult problems, it usually finds solutions that are closer to the global optimum. Another fundamental advantage is that continuous-thrust trajectories can be optimized without an initial guess and without expert supervision.
Wind loads have great impact on many engineering structures. Wind storms often cause irreparable damage to the buildings which are exposed to it. Along with the earthquakes, wind represents one of the most common environmental load on structures and is relevant for limit state design. Modern wind codes indicate calculation procedures allowing engineers to deal with structural systems, which are susceptible to conduct wind-excited oscillations. In the codes approximate formulas for wind buffeting are specified which relate the dynamic problem to rather abstract parameter functions. The complete theory behind is not visible in order to simplify the applicability of the procedures. This chapter derives the underlying basic relations of the spectral method for wind buffeting and explains the main important applications of it in order to elucidate part of the theoretical background of computations after the new codes. The stochasticity of the wind processes is addressed, and the analysis of analytical as well as measurement based power spectra is outlined. Short MATLAB codes are added to the Appendix 3 which carry out the computation of a single sided auto-spectrum from a statistically stationary, discrete stochastic process. Two examples are presented.
The use of transgenic animal models has transformed our knowledge of complex biochemical pathways in vivo. It has allowed disease processes to be modelled and used in the development of new disease prevention and treatment strategies. They can also be used to define cell- and tissue-specific pathways of gene regulation. A further major application is in the area of preclinical development where such models can be used to define pathways of chemical toxicity, and the pathways that regulate drug disposition. One major application of this approach is the humanisation of mice for the proteins that control drug metabolism and disposition. Such models can have numerous applications in the development of drugs and in their more sophisticated use in the clinic.
Genetically humanized mice for proteins involved in drug metabolism and toxicity and mice engrafted with human hepatocytes are emerging as promising in vivo models for improved prediction of the pharmacokinetic, drug–drug interaction, and safety characteristics of compounds in humans. This is an overview on the genetically humanized and chimeric liver-humanized mouse models, which are illustrated with examples of their utility in drug metabolism and toxicity studies. The models are compared to give guidance for selection of the most appropriate model by highlighting advantages and disadvantages to be carefully considered when used for studies in drug discovery and development.
In the past decade, many IS researchers focused on researching the phenomenon of Big Data. At the same time, the relevance of data protection gets more attention than ever before. In particular, since the enactment of the European General Data Protection Regulation in May 2018 Information Systems research should provide answers for protecting personal data. The article at hand presents a structuring framework for Big Data research outcome and the consideration of data protection. IS Researchers might use the framework in order to structure Big Data literature and to identify research gaps that should be addressed in the future.
In competition with other modes of transport, rail freight transport is looking for solutions to become more attractive. Short-term success can be achieved through the data-driven optimization of operations and maintenance as well as the application of novel strategies such as prescriptive maintenance. After introducing the concept of prescriptive maintenance, this paper aims to prove that vehicle-focused applications of this approach indeed have the potential to increase attractiveness. However, even greater advantages can be activated if data from the horizontal network of the vehicle is available. Drawing on the state of the art in research and technology in the field of cyber-physical systems (CPS) as well as digital twins and shadows, our work serves to design a system of systems for the horizontal interconnection of a rail vehicle and to conceptualize a draft for a digital twin of a locomotive.
Small Claims Regulation
(2017)
Names of individuals
(2017)
This chapter introduces performance and acceptance testing and describes state-of-the-art tools, methods, and instruments to assess the plant performance or realize plant acceptance testing. The status of the development of standards for performance assessment is given.
The light-addressable potentiometric sensor (LAPS) and scanning photo-induced impedance microscopy (SPIM) are two closely related methods to visualise the distributions of chemical species and impedance, respectively, at the interface between the sensing surface and the sample solution. They both have the same field-effect structure based on a semiconductor, which allows spatially resolved and label-free measurement of chemical species and impedance in the form of a photocurrent signal generated by a scanning light beam. In this article, the principles and various operation modes of LAPS and SPIM, functionalisation of the sensing surface for measuring various species, LAPS-based chemical imaging and high-resolution sensors based on silicon-on-sapphire substrates are described and discussed, focusing on their technical details and prospective applications.
Epilepsy
(2010)
The network approach towards the analysis of the dynamics of complex systems has been successfully applied in a multitude of studies in the neurosciences and has yielded fascinating insights. With this approach, a complex system is considered to be composed of different constituents which interact with each other. Interaction structures can be compactly represented in interaction networks. In this contribution, we present a brief overview about how interaction networks are derived from multivariate time series, about basic network characteristics, and about challenges associated with this analysis approach.