Rapid Prototyping for Sheet Metal Products

The aim of this chapter is to evaluate and predict forming limit and then to improve and develop the incremental sheet metal forming (ISMF) processes for complex surface products of sheet metal. The theoretical study was first overviewed and synthesized in order to recognize the effect of geometry, technology parameters, and processing conditions on ISMF process. Finite element method (FEM) simulation study was then used to compare the accuracy of constitutive material models and fracture criteria and propose new equations in order to improve the prediction of FEM simulation for incremental sheet metal forming process. To develop a new technique for improving the formability of sheet metal using ISMF, FEM was also adopted to reduce the cost and time of research. The basic experimental studies were performed to determine the input data for FEM simulation such as tensile data, fracture parameters, and so on. To investigate and compare the simulation results, the incremental sheet metal forming processes for complex shapes were also conducted

River modeling for control tasks in water systems

Die Saint Venant Gleichungen (Englisch: Saint Venant Equations; SVEs) werden sehr häutig eingesetzt, um das Fließverhalten im offenen Kanal / Fluss zu beschreiben. Einerseits benötigen Modelle, die auf den SVEs basieren, sehr viele Daten für die Parametrierung und auch große Rechenzeiten, um das Fließverhalten zu simulieren. Andererseits sind vereinfachte Modelle eine oft angewandte Technik, um komplexe hydrodynamische Modelle für die modellbasierte Steuerung einzusetzen ohne die wichtigsten dynamischen Attribute zu vernachlässigen. Das adaptive Zeitverzögerungsmodell (Englisch: Adaptive Time Delay; ATD) erweitert den Anwendungsbereich des bisher eingesetzten Zeitverzögerungsmodells durch Simulation des Durchflusses mit einer prismatischen Trapezgeometrie. In dieser Arbeit wird die mathematische Herleitung des ATD-Modells aus dem linearisierten Saint Venant-Modell (SVEs) dargestellt. Die Übertragungsfunktionen des ATD-Modells und des komplexen hydraulischen Modells (SVEs) werden mittels Laplace-Transformation abgeleitet. Es wird die Taylor-Reihen-Entwicklung verwendet, um die Kumulanten der beiden Übertragungsfunktionen zu finden, und um daraus die Zeitkonstante und Totzeit des ATD-Modells als Funktionen der komplexen hydraulischen Modellparameter abzuleiten. Eine weitere Neuerung ist die Kopplung des ATD-Modells mit dem Reservoir-Modell, um den Effekt des Rückstaus zu simulieren. Das Gerinne ist dabei grundsätzlich in zwei Teile unterteilt: der stromaufwärtige gleichförmige Durchflussbereich und der stromabwärtige Rückstaubereich. Die Länge ist abhängig von der Fließgeschwindigkeit und dem stromabwärtigen Zustand. Die Modellparameter sind damit Funktionen sowohl der Fließgeschwindigkeit als auch der Länge der genannten Bereiche. Der dritte Beitrag in dieser Dissertation ist ein Verfahren, um Parameter des ATD-Modells anhand eines komplexen hydraulischen Modells zu identifizieren. Zunächst wird die typische Hydrographie eines extremen Hochwasserereignisses durch das Verfahren der medianen Hydrographanalyse erzeugt. Zweitens wird der typische Abfluss durch das komplexe Hydraulikmodell simuliert, um das Abflussverhalten zu bestimmen. Dann werden diese Daten verwendet, um Parameter des ATD-Modells durch ein Optimierungsverfahren zu ermitteln. Die Anwendung der neu entwickelten Verfahren wird am Beispiel der optimalen Steuerung einer Staustufenkaskade gezeigt. Der Vorteil ist, dass das ATD-Modell die Systemdynamik sehr gut beschreiben kann. Alle Modellerweiterungen, die in dieser Arbeit vorgestellt werden, wurden in die WaterLib Toolbox von der MATLAB SIMULINK zur Simulation von Wassersystemen integriert.The Saint Venant Equations (SVEs) are frequently used to describe flow in open channel/river. On the one hand, models based on SVEs require huge data for parameterization as well as large computation time in order to simulate flow behavior. On the other hand, simplified models are an often-chosen technique for model based control without eliminating the key dynamic attributes. The Adaptive Time Delay model (ATD) expands the application scope of the previous time delay models by simulating the flow using a prismatic trapezoidal geometry. In this approach, the mathematical derivation of the ATD model and the linearized Saint Venant model (SVEs) are defined. The transfer functions of the ATD model and the complex hydraulic model (SVEs) are derived by Laplace transformation. The Taylor expansion technique is used to find cumulants of the two transfer functions and the time constant and time delay of the ATD model as functions of the complex hydraulic model parameters. Another innovation is the coupling of the ATD model with the reservoir model in order to simulate the backwater effect. The reach is fundamentally separated into two parts: upstream uniform flow area and downstream backwater area. The length of both areas is relied on flow rate and downstream condition. The model parameters are thus the functions of both flow rate and the length of the areas. The third contribution of the dissertation is a method to identify parameters of ATD model from a complex hydraulic model. Initially, the typical hydrograph of an extreme flood event is generated by the method of characteristic hydrograph analysis. Secondly, the typical outflow is simulated by the complex hydraulic model to determine the flow behavior. Then those data are used to estimate parameters of ATD model by an optimization technique. The application of the new method is presented by the case study of optimal control of a hydropower plant cascade. The advantage of this is that the ATD model is able to describe the system dynamics. All of extensions are then integrated in the 'WaterLib' tool box by MATLAB SIMULINK for water system simulation

A Distance-Based Method for Attribute Reduction in Incomplete Decision Systems

There are limitations in recent research undertaken on attribute reduction in incomplete decision systems. In this paper, we propose a distance-based method for attribute reduction in an incomplete decision system. In addition, we prove theoretically that our method is more effective than some other methods

Partial Underpinning a Five-Storey Building

Partial underpinning is often not accepted because of dangerous damage that may be caused by the redistribution of stresses in the superstructure. A five-storey building was partially underpinned successfully. To give stability to the building only a small number of piles, about 70% fewer than with the conventional method, were used. The results observed have proved the success of the partial underpinning

Power beacon-assisted energy harvesting in a half-duplex communication network under co-channel interference over a Rayleigh fading environment: Energy efficiency and outage probability analysis

In this time, energy efficiency (EE), measured in bits per Watt, has been considered as an important emerging metric in energy-constrained wireless communication networks because of their energy shortage. In this paper, we investigate power beacon assisted (PB) energy harvesting (EH) in half-duplex (HD) communication network under co-channel Interferer over Rayleigh fading environment. In this work, we investigate the model system with the time switching (TS) protocol. Firstly, the exact and asymptotic form expressions of the outage probability (OP) are analyzed and derived. Then the system EE is investigated and the influence of the primary system parameters on the system performance. Finally, we verify the correctness of the analytical expressions using Monte Carlo simulation. Finally, we can state that the simulation and analytical results are the same.Web of Science1213art. no. 257

Optimal solutions for fixed head short-term hydrothermal system scheduling problem

In this paper, optimal short-term hydrothermal operation (STHTO) problem is determined by a proposed high-performance particle swarm optimization (HPPSO). Control variables of the problem are regarded as an optimal solution including reservoir volumes of hydropower plants (HdPs) and power generation of thermal power plants (ThPs) with respect to scheduled time periods. This problem focuses on reduction of electric power generation cost (EPGC) of ThPs and exact satisfactory of all constraints of HdPs, ThPs and power system. The proposed method is compared to earlier methods and other implemented methods such as particle swarm optimization (PSO), constriction factor (CF) and inertia weight factor (IWF)-based PSO (FCIW-PSO), two time-varying acceleration coefficient (TTVACs)-based PSO (TVAC-PSO), salp swarm algorithm (SSA), and Harris hawk algorithm (HHA). By comparing EPGC from 100 trial runs, speed of search and simulation time, the suggested HPPSO method sees it is more robust than other ones. Thus, HPPSO is recommended for applying to the considered and other problems in power systems

First Principles Prediction Unveils High-Tc_c Superconductivity in YSc2_2H24_{24} Cage Structures

The quest for room-temperature superconductivity has been a long-standing aspiration in the field of materials science, driving extensive research efforts. In this work, we present a novel hydride, YSc$_2$H$_{24}$, which is stable at high pressure using a crystal structure prediction approach with a fixed composition based on known structures. The discovered material is crystalline in a hexagonal unit cell with space group P6/mmm and has a fastinating structure consisting of two distinct cages: Sc@H$_{24}$ and Y@H$_{30}$. By conducting an extensive numerical investigation of lattice dynamics, electron-phonon coupling, and solving the isotropic Eliashberg equation, we have revealed a significant value of $\lambda$ = 2.96 as the underlying factor responsible for the remarkably high critical temperature (T$_c$) of 306-332 K in YSc$_2$H$_{24}$. As pressure increases, the T$_c$ remains above the ambient temperature. Our work has the potential to enhance the existing understanding of high-temperature superconductors, with implications for practical applications. The unique network of these cage-like structures holds great promise for advancing our understanding of high-temperature superconductors, potentially leading to innovative applications