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FEM shakedown analysis of structures under random strength with chance constrained programming
(2022)
Direct methods, comprising limit and shakedown analysis, are a branch of computational mechanics. They play a significant role in mechanical and civil engineering design. The concept of direct methods aims to determine the ultimate load carrying capacity of structures beyond the elastic range. In practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and constraints. If strength and loading are random quantities, the shakedown analysis can be formulated as stochastic programming problem. In this paper, a method called chance constrained programming is presented, which is an effective method of stochastic programming to solve shakedown analysis problems under random conditions of strength. In this study, the loading is deterministic, and the strength is a normally or lognormally distributed variable.
Direct methods comprising limit and shakedown analysis is a branch of computational mechanics. It plays a significant role in mechanical and civil engineering design. The concept of direct method aims to determinate the ultimate load bearing capacity of structures beyond the elastic range. For practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and onstraints. If strength and loading are random quantities, the problem of shakedown analysis is considered as stochastic programming. This paper presents a method so called chance constrained programming, an effective method of stochastic programming, to solve shakedown analysis problem under random condition of strength. In this our investigation, the loading is deterministic, the strength is distributed as normal or lognormal variables.
A new formulation to calculate the shakedown limit load of Kirchhoff plates under stochastic conditions of strength is developed. Direct structural reliability design by chance con-strained programming is based on the prescribed failure probabilities, which is an effective approach of stochastic programming if it can be formulated as an equivalent deterministic optimization problem. We restrict uncertainty to strength, the loading is still deterministic. A new formulation is derived in case of random strength with lognormal distribution. Upper bound and lower bound shakedown load factors are calculated simultaneously by a dual algorithm.
We propose the so-called chance constrained programming model of stochastic programming theory to analyze limit and shakedown loads of structures under random strength with a lognormal distribution. A dual chance constrained programming algorithm is developed to calculate simultaneously both the upper and lower bounds of the plastic collapse limit and the shakedown limit. The edge-based smoothed finite element method (ES-FEM) is used with three-node linear triangular elements.
We propose a stochastic programming method to analyse limit and shakedown of structures under random strength with lognormal distribution. In this investigation a dual chance constrained programming algorithm is developed to calculate simultaneously both the upper and lower bounds of the plastic collapse limit or the shakedown limit. The edge-based smoothed finite element method (ES-FEM) using three-node linear triangular elements is used.
In this paper we propose a stochastic programming method to analyse limit and shakedown of structures under uncertainty condition of strength. Based on the duality theory, the shakedown load multiplier formulated by the kinematic theorem is proved actually to be the dual form of the shakedown load multiplier formulated by static theorem. In this investigation a dual chance constrained programming algorithm is developed to calculate simultaneously both the upper and lower bounds of the plastic collapse limit and the shakedown limit. The edge-based smoothed finite element method (ES-FEM) with three-node linear triangular elements is used for structural analysis.
This paper investigates the extent to which corporate governance affects the cost of debt and equity capital of German exchange-listed companies. I examine corporate governance along three dimensions: financial information quality, ownership structure and board structure. The results suggest that firms with high levels of financial transparency and bonus compensations face lower cost of equity. In addition, block ownership is negatively related to firms' cost of equity when the blockholders are other firms, managers or founding-family members. Consistent with the conjecture that agency costs increase with firm size, I find significant cost of debt effects only in the largest German companies. Here, the creditors demand lower cost of debt from firms with block ownerships held by corporations or banks. My findings demonstrate that a uniform set of governance attributes is unlikely to satisfy suppliers of debt and equity capital equally.
A generalized shear-lag theory for fibres with variable radius is developed to analyse elastic fibre/matrix stress transfer. The theory accounts for the reinforcement of biological composites, such as soft tissue and bone tissue, as well as for the reinforcement of technical composite materials, such as fibre-reinforced polymers (FRP). The original shear-lag theory proposed by Cox in 1952 is generalized for fibres with variable radius and with symmetric and asymmetric ends. Analytical solutions are derived for the distribution of axial and interfacial shear stress in cylindrical and elliptical fibres, as well as conical and paraboloidal fibres with asymmetric ends. Additionally, the distribution of axial and interfacial shear stress for conical and paraboloidal fibres with symmetric ends are numerically predicted. The results are compared with solutions from axisymmetric finite element models. A parameter study is performed, to investigate the suitability of alternative fibre geometries for use in FRP.
In many historical centres in Europe, stone masonry buildings are part of building aggregates, which developed when the layout of the city or village was densified. In these aggregates, adjacent buildings share structural walls to support floors and roofs. Meanwhile, the masonry walls of the façades of adjacent buildings are often connected by dry joints since adjacent buildings were constructed at different times. Observations after for example the recent Central Italy earthquakes showed that the dry joints between the building units were often the first elements to be damaged. As a result, the joints opened up leading to pounding between the building units and a complicated interaction at floor and roof beam supports. The analysis of such building aggregates is very challenging and modelling guidelines do not exist. Advances in the development of analysis methods have been impeded by the lack of experimental data on the seismic response of such aggregates. The objective of the project AIMS (Seismic Testing of Adjacent Interacting Masonry Structures), included in the H2020 project SERA, is to provide such experimental data by testing an aggregate of two buildings under two horizontal components of dynamic
excitation. The test unit is built at half-scale, with a two-storey building and a one-storey building. The buildings share one common wall while the façade walls are connected by dry joints. The floors are at different heights leading to a complex dynamic response of this smallest possible building aggregate. The shake table test is conducted at the LNEC seismic testing facility. The testing sequence comprises four levels of shaking: 25%, 50%, 75% and 100% of nominal shaking table capacity. Extensive instrumentation, including accelerometers, displacement transducers and optical measurement systems, provides detailed information on the building aggregate response. Special attention is paid to the interface opening, the globa
In many historical centers in Europe, stone masonry is part of building aggregates, which developed when the layout of the city or village was densified. The analysis of such building aggregates is very challenging and modelling guidelines missing. Advances in the development of analysis methods have been impeded by the lack of experimental data on the seismic response of such aggregates. The SERA project AIMS (Seismic Testing of Adjacent Interacting Masonry Structures) provides such experimental data by testing an aggregate of two buildings under two horizontal components of dynamic excitation. With the aim to advance the modelling of unreinforced masonry aggregates, a blind prediction competition is organized before the experimental campaign. Each group has been provided a complete set of construction drawings, material properties, testing sequence and the list of measurements to be reported. The applied modelling approaches span from equivalent frame models to Finite Element models using shell elements and discrete element models with solid elements. This paper compares the first entries, regarding the modelling approaches, results in terms of base shear, roof displacements, interface openings, and the failure modes.
The assessment of the right ventricle (RV) is a challenge in today's cardiology, but of growing clinical impact regarding patient prognosis in different cardiac diseases. The detection and differentiation of small wall motion abnormalities may help to enhance the differentiation of cardiomyopathies including Arrhythmogenic Rightventricular Cardiomyopathy. Cardiovascular magnetic resonance (CMR) at 1.5T is the accepted gold standard for RV quantification. The higher spatial resolution achievable at ultrahigh field strength (UHF) offers the potential to gain new insights into the structure and function of the RV. To approach this goal accurate RV chamber quantification at 7T has to be proven. Consequently this study examines the feasibility of assessment of RV dimensions and function at 7T using improved spatial resolution enabled by the intrinsic sensitivity gain of UHF CMR. For this purpose, a dedicated 16 channel TX/RX RF coil array is used together with 2D CINE fast gradient echo (FGRE) imaging. For comparison RV chamber quantification is conducted at 1.5T using a SSFP based state of the art clinical protocol.
Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis.
A major part of edible oil is subjected to bleaching procedures, primarily with minerals applied as adsorbers. Their recycling is currently done either by regaining the oil via organic solvent extraction or by using the spent bleaching earth (SBE) as additive for animal feed, etc. As a new method, the reutilization of the by-product SBE for the microbiologic formation of acetone, butanol, and ethanol (ABE) is presented as proof-of-concept. The SBE was taken from a palm oil cleaning process. The recycling concept is based on the application of lipolytic clostridia strains. Due to considerably long fermentation times, co-fermentation with Candida rugosa and enzymatic hydrolyses of the bound oil with a subsequent clostridia fermentation are shown as alternative routes. Anaerobic fermentations under comparison of different clostridia strains were performed with glycerol media, enzymatically hydrolyzed palm oil and SBE. Solutes, side product compositions and productivities were quantified via HPLC. A successful production of ABE solutes from SBE has been done with a yield of 0.15 g butanol per gram of bound glycerol. Thus, the biotechnological recycling of the waste stream is possible in principle. Inhibition of the substrate suspension has been observed. A chromatographic ion-exchange of substrates increased the biomass concentration.
Magnetisierbare Partikel als Träger von Katalysatoren können durch Anlegen eines magnetisches Feldes einfach und schnell abgetrennt werden. Die Wiedergewinnung von wertvollen Enzymen unter geringem Energie- und Materialeinsatz der magnetischen Abtrennung eröffnet einen Wettbewerbsvorteil für Produktionsprozesse. Die Abtrennung von magnetisierbaren Partikeln vom Überstand wird üblicherweise entweder durch Anlegen eines äußeren Magnetfelds und der resultierenden Ablagerung der Partikel an den Reaktorwänden oder durch Hochgradientenmagnetseparation (HGMS)durchgeführt. Beide Verfahren resultieren meist in der Bildung eines Filterkuchens aus Magnetpartikeln und den Feststoffen des Reaktionsmediums. Das magnetische horizontale Wirbelbett ermöglicht simultan eine kontinuierliche Reaktionsführung und die Rückhaltung der Partikel im Durchfluss. Die Partikelsuspension fließt durch einen Rohrreaktor, der in einem Magnetfeld mit wechselnden Feldgradienten eingebracht ist. Die Änderung des Magnetfeldgradienten erfolgt entgegen der Strömungsrichtung der Reaktionslösung. Durch alternierende Feldmaxima an den beiden Seiten des Reaktors werden die magnetisierbaren Partikel zu dessen Wänden gezogen. Bei Umkehrung des Feldes wandern die Partikel an die gegenüberliegende Reaktorwand. Durch Wahl einer geeigneten Wechselfrequenz kann eine kontinuierliche Durchmischung und Rückhaltung der Mikropartikel im durchströmten Rohr erreicht werden. Somit können Immobilisierungsreaktionen und Biotransformationen mit den Partikelsystemen im Durchfluss durchgeführt werden.
An immunochromatographic lateral flow dipstick assay for the fast detection of microcystin-LR was developed. Colloid gold particles with diameters of 40 nm were used as red-colored antibody labels for the visual detection of the antigen. The new dipstick sensor is capable of detecting down to 5 µg·l−1 (ppb; total inversion of the color signal) or 1 ppb (observation of color grading) of microcystin-LR. The course of the labeling reaction was observed via spectrometric wave shifts caused by the change of particle size during the binding of antibodies. Different stabilizing reagents showed that especially bovine serum albumin (BSA) and casein increase the assays sensitivity and the conjugate stability. Performance of the dipsticks was quantified by pattern processing of capture zone CCD images. Storage stability of dipsticks and conjugate suspensions over 115 days under different conditions were monitored. The ready-to-use dipsticks were successfully tested with microcystin-LR-spiked samples of outdoor drinking- and salt water and applied to the tissue of microcystin-fed mussels.
Paracoccus denitrificans for the effluent recycling during continuous denitrification of liquid food
(2010)
Nitrate is an undesirable component of several foods. A typical case of contamination with high nitrate contents is whey concentrate, containing nitrate in concentrations up to 25 l. The microbiological removal of nitrate by Paracoccus denitrificans under formation of harmless nitrogen in combination with a cell retention reactor is described here. Focus lies on the resource-conserving design of a microbal denitrification process. Two methods are compared. The application of polyvinyl alcohol-immobilized cells, which can be applied several times in whey feed, is compared with the implementation of a two step denitrification system. First, the whey concentrate's nitrate is removed by ion exchange and subsequently the eluent regenerated by microorganisms under their retention by crossflow filtration. Nitrite and nitrate concentrations were determined by reflectometric color measurement with a commercially available Reflectoquant® device. Correction factors for these media had to be determined. During the pilot development, bioreactors from 4 to 250 mg·L-1 and crossflow units with membrane areas from 0.02 to 0.80 m2 were examined. Based on the results of the pilot plants, a scaling for the exemplary process of denitrifying 1,000 tons per day is discussed.
In comparison to crude oil, biorefinery raw materials are challenging in concerns of transport and storage. The plant raw materials are more voluminous, so that shredding and compacting usually are necessary before transport. These mechanical processes can have a negative influence on the subsequent biotechnological processing and shelf life of the raw materials. Various approaches and their effects on renewable raw materials are shown. In addition, aspects of decentralized pretreatment steps are discussed. Another important aspect of pretreatment is the varying composition of the raw materials depending on the growth conditions. This problem can be solved with advanced on-site spectrometric analysis of the material.
The development of a cost-effective hydrolysis for crude cellulose is an essential part of biorefinery developments. To establish such high solid hydrolysis, a new solid state reactor with static mixing is used. However, concentrations >10% (w/w) cause a rate and yield reduction of enzymatic hydrolysis. By optimizing the synergetic activity of cellulolytic enzymes at solid concentrations of 9%, 17% and 23% (w/w) of crude Organosolv cellulose, glucose concentrations of 57, 113 and 152 g L⁻¹ are reached. However, the glucose yield decreases from 0.81 to 0.72gg⁻¹ at 17% (w/w). Optimal conditions for hydrolysis scale-up under minimal enzyme addition are identified. As result, at 23% (w/w) crude cellulose the glucose yield increases from 0.29 to 0.49gg⁻¹. As proof of its applicability, biobutanol, succinic and itaconic acid are produced with the crude hydrolysate. The potential of the substrate is proven e.g. by a high butanol yield of 0.33gg⁻¹.
Due to the interfering effects of acetic acid in many fermentation processes, a gas-diffusion technique was developed for the online determination of acetic acid. The measurements were accomplished with a flow diffusion analysis (FDA) unit from the TRACE Analytics GmbH, Braunschweig, Germany. The diffusion analysis is based on the UV-absorbance of acetic acid at 205 nm. The measurement was achieved by the separation of an acceptor and a carrier stream (acidified fermentation broth) using a gas permeable polytetrafluoroethylene (PTFE) membrane, whereby broth constituents that would otherwise disturb the UV-measurement of acetic acid, are held back efficiently. Merely, the fermentation by-products, e.g. formic acid, is capable of diffusing through the membrane. While formic acid can disturb the measurement, carbon dioxide does not absorb at 205 nm. The method operates with time-dependent sample enrichment. During the analysis, a small volume of the acceptor stream is stopped for a defined time interval in the acceptor chamber. During this period, the gaseous acetic acid diffuses through the membrane and is enriched in the acceptor chamber. Subsequently after the enrichment, the acceptor stream flows through a UV-detector. The intensity of the signal is proportional to the acetic acid concentration. Online measurements in bioreactors via a sterile filtration probe have been accomplished. A linear calibration in the range of 0.5–5.0 g/L acetic acid with a relative standard deviation of <5 % was obtained. A sampling rate of 8 samples per hour was possible. The system was applied for the determination of acetic acid in E. coli fermentation broth. The instrument is easy to clean, very user-friendly and does not require any toxic or expensive reagents.
Biotechnological downstream processing is usually an elaborate procedure, requiring a multitude of unit operations to isolate the target component. Besides the disadvantageous space-time yield, the risks of cross-contaminations and product loss grow fast with the complexity of the isolation procedure. A significant reduction of unit operations can be achieved by application of magnetic particles, especially if these are functionalized with affinity ligands. As magnetic susceptible materials are highly uncommon in biotechnological processes, target binding and selective separation of such particles from fermentation or reactions broths can be done in a single step. Since the magnetizable particles can be produced from iron salts and low priced polymers, a single-use implementation of these systems is highly conceivable. In this article, the principles of magnetizable particles, their synthesis and functionalization are explained. Furthermore, applications in the area of reaction engineering, microfluidics and downstream processing are discussed focusing on established single-use technologies and development potential.
Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30%. These results show promise for further enhancements and to support broader applicability.
This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance.
Digital Image Correlation (DIC) is a powerful tool used to evaluate displacements and deformations in a non-intrusive manner. By comparing two images, one of the undeformed reference state of a specimen and another of the deformed target state, the relative displacement between those two states is determined. DIC is well known and often used for post-processing analysis of in-plane displacements and deformation of specimen. Increasing the analysis speed to enable real-time DIC analysis will be beneficial and extend the field of use of this technique.
Here we tested several combinations of the most common DIC methods in combination with different parallelization approaches in MATLAB and evaluated their performance to determine whether real-time analysis is possible with these methods. To reflect improvements in computing technology different hardware settings were also analysed. We found that implementation problems can reduce the efficiency of a theoretically superior algorithm such that it becomes practically slower than a suboptimal algorithm. The Newton-Raphson algorithm in combination with a modified Particle Swarm algorithm in parallel image computation was found to be most effective. This is contrary to theory, suggesting that the inverse-compositional Gauss-Newton algorithm is superior. As expected, the Brute Force Search algorithm is the least effective method. We also found that the correct choice of parallelization tasks is crucial to achieve improvements in computing speed. A poorly chosen parallelisation approach with high parallel overhead leads to inferior performance. Finally, irrespective of the computing mode the correct choice of combinations of integerpixel and sub-pixel search algorithms is decisive for an efficient analysis. Using currently available hardware realtime analysis at high framerates remains an aspiration.