Field Programmable Gate Arrays (FPGAs) are programmable logic devices used for the implementation of a wide range of digital systems. In recent years, there has been an increasing interest in design methodologies that allow high-level design descriptions to be automatically implemented in FPGAs. This thesis describes the design and implementation of a novel compilation flow that implements circuits in FPGAs from a streaming programming language. The streaming language supported is called FPGA Brook, and is based on the existing Brook and GPU Brook languages, which target streaming multiprocessors and graphics processing units (GPUs), respectively. A streaming language is suitable for targeting FPGAs because it allows system designers to express applications in a way that exposes parallelism, which can then be exploited through parallel hardware implementation. FPGA Brook supports replication, which allows the system designer to trade-off area for performance, by specifying the parts of an application that should be implemented as multiple hardware units operating in parallel, to achieve desired application throughput. Hardware units are interconnected through FIFO buffers, which effectively utilize the small memory modules available in FPGAs. The FPGA Brook design flow uses a source-to-source compiler, and combines it with a commercial behavioural synthesis tool to generate hardware. The source-to-source compiler was developed as a part of this thesis and includes novel algorithms for implementation of complex reductions in FPGAs. The design flow is fully automated and presents a user-interface similar to traditional software compilers. A suite of benchmark applications was developed in FPGA Brook and implemented using our design flow. Experimental results show that applications implemented using our flow achieve much higher throughput than the Nios II soft processor implemented in the same FPGA device. Comparison to the commercial C2H compiler from Altera shows that while simple applications can be effectively implemented using the C2H compiler, complex applications achieve significantly better throughput when implemented by our system. Performance of many applications implemented using our design flow would scale further if a larger FPGA device were used. The thesis demonstrates that using an automated design flow to implement streaming applications in FPGAs is a promising methodology.

Denna studie undersöker möjligheten att påverka fientliga konstruktioner genom användandet av en effektiv metod, som kan medge en liten risk att upptäckas. Den tänkta påverkan uppnås genom fenomenet Liquid Metal Embrittlement (LME), med vilken höghållfasta metaller kan påverkas så mycket att de kollapsar av sin egenvikt. Uppsatsen studerar LME på ett ofta använt konstruktionsmaterial både civilt som militärt. Ett experiment genomfördes i syfte att undersöka effekterna av LME på en aluminiumlegering, där en aluminiumdetalj exponerades för metallen gallium. Förförsök genomfördes i syfte att undersöka inom vilka tidsförhållanden LME uppstod och experimentets exponeringstider planerades därefter. Efter varje exponeringstid genomfördes ett dragprov för att påvisa en minskad hållfasthet och seghet hos aluminiumet. Resultatet blev en stor minskning av hållfasthet och seghet, där hållfastheten sänktes till 20% av referensvärdet och segheten till 1% av referensvärdet, även om resultatet var spritt. / The possibility to damage enemy constructions using an efficient method, which might permit a low risk of detection, is studied in this thesis. This damage is based on the phenomena Liquid Metal Embrittlement (LME) with which high strength metals can be affected so much that they collapse under their own weight. This thesis studies this effect in a material often used for various constructions, both civilian and military. An experiment was conducted in order to evaluate the effects of LME on an aluminium alloy by exposing the aluminium to the metal known as gallium. A pre-experiment was made in order to determine how the time of exposure affected the LME-process and time-periods were decided accordingly. At each of the timeperiods a yield test was conducted in order to measure losses in strength and elasticity of the aluminium. It was shown that a great reduction in strength and elasticity occurred, where the strength was reduced to 20% of the reference sample and elasticity to 1% of the reference sample.

In geotechnical engineering, the uncertainties such as the variability and uncertainty inherent in the geotechnical properties have caught more and more attentions from researchers and engineers. They have found that a single “Factor of Safety” calculated by traditional deterministic analyses methods can not represent the slope stability exactly. Recently in order to provide a more rational mathematical framework to incorporate different types of uncertainties in the slope stability estimation, reliability analyses and non-deterministic methods, which include probabilistic and non probabilistic (imprecise methods) methods, have been applied widely. In short, the slope non-deterministic analysis is to combine the probabilistic analysis or non probabilistic analysis with the deterministic slope stability analysis. It cannot be regarded as a completely new slope stability analysis method, but just an extension of the slope deterministic analysis. The slope failure probability calculated by slope non-deterministic analysis is a kind of complement of safety factor. Therefore, the accuracy of non deterministic analysis is not only depended on a suitable probabilistic or non probabilistic analysis method selected, but also on a more rigorous deterministic analysis method or geological model adopted. In this thesis, reliability concepts have been reviewed first, and some typical non-deterministic methods, including Monte Carlo Simulation (MCS), First Order Reliability Method (FORM), Point Estimate Method (PEM) and Random Set Theory (RSM), have been described and successfully applied to the slope stability analysis based on a numerical simulation method-Strength Reduction Method (SRM). All of the processes have been performed in a commercial finite difference code FLAC and a distinct element code UDEC. First of all, as the fundamental of slope reliability analysis, the deterministic numerical simulation method has been improved. This method has a higher accuracy than the conventional limit equilibrium methods, because of the reason that the constitutive relationship of soil is considered, and fewer assumptions on boundary conditions of slope model are necessary. However, the construction of slope numerical models, particularly for the large and complicated models has always been very difficult and it has become an obstacle for application of numerical simulation method. In this study, the excellent spatial analysis function of Geographic Information System (GIS) technique has been introduced to help numerical modeling of the slope. In the process of modeling, the topographic map of slope has been gridded using GIS software, and then the GIS data was transformed into FLAC smoothly through the program built-in language FISH. At last, the feasibility and high efficiency of this technique has been illustrated through a case study-Xuecheng slope, and both 2D and 3D models have been investigated. Subsequently, three most widely used probabilistic analyses methods, Monte Carlo Simulation, First Order Reliability Method and Point Estimate Method applied with Strength Reduction Method have been studied. Monte Carlo Simulation which needs to repeat thousands of deterministic analysis is the most accurate probabilistic method. However it is too time consuming for practical applications, especially when it is combined with numerical simulation method. For reducing the computation effort, a simplified Monte Carlo Simulation-Strength Reduction Method (MCS-SRM) has been developed in this study. This method has estimated the probable failure of slope and calculated the mean value of safety factor by means of soil parameters first, and then calculated the variance of safety factor and reliability of slope according to the assumed probability density function of safety factor. Case studies have confirmed that this method can reduce about 4/5 of time compared with traditional MCS-SRM, and maintain almost the same accuracy. First Order Reliability Method is an approximate method which is based on the Taylor\'s series expansion of performance function. The closed form solution of the partial derivatives of the performance function is necessary to calculate the mean and standard deviation of safety factor. However, there is no explicit performance function in numerical simulation method, so the derivative expressions have been replaced with equivalent difference quotients to solve the differential quotients approximately in this study. Point Estimate Method is also an approximate method involved even fewer calculations than FORM. In the present study, it has been integrated with Strength Reduction Method directly. Another important observation referred to the correlation between the soil parameters cohesion and friction angle. Some authors have found a negative correlation between cohesion and friction angle of soil on the basis of experimental data. However, few slope probabilistic studies are found to consider this negative correlation between soil parameters in literatures. In this thesis, the influence of this correlation on slope probability of failure has been investigated based on numerical simulation method. It was found that a negative correlation considered in the cohesion and friction angle of soil can reduce the variability of safety factor and failure probability of slope, thus increasing the reliability of results. Besides inter-correlation of soil parameters, these are always auto-correlated in space, which is described as spatial variability. For the reason that knowledge on this character is rather limited in literature, it is ignored in geotechnical engineering by most researchers and engineers. In this thesis, the random field method has been introduced in slope numerical simulation to simulate the spatial variability structure, and a numerical procedure for a probabilistic slope stability analysis based on Monte Carlo simulation was presented. The soil properties such as cohesion and friction angle were discretized to continuous random fields based on local averaging method. In the case study, both stationary and non-stationary random fields have been investigated, and the influence of spatial variability and averaging domain on the convergence of numerical simulation and probability of failure was studied. In rock medium, the structure faces have very important influence on the slope stability, and the rock material can be modeled as the combination of rigid or deformable blocks with joints in distinct element method. Therefore, much more input parameters like strength of joints are required to input the rock slope model, which increase the uncertainty of the results of numerical model. Furthermore, because of the limitations of the current laboratory and in-site testes, there is always lack of exact values of geotechnical parameters from rock material, even the probability distribution of these variables. Most of time, engineers can only estimate the interval of these variables from the limit testes or the expertise’s experience. In this study, to assess the reliability of the rock slope, a Random Set Distinct Element Method (RS-DEM) has been developed through coupling of Random Set Theory and Distinct Element Method, and applied in a rock slope in Sichuan province China.

In geotechnical engineering, the uncertainties such as the variability and uncertainty inherent in the geotechnical properties have caught more and more attentions from researchers and engineers. They have found that a single “Factor of Safety” calculated by traditional deterministic analyses methods can not represent the slope stability exactly. Recently in order to provide a more rational mathematical framework to incorporate different types of uncertainties in the slope stability estimation, reliability analyses and non-deterministic methods, which include probabilistic and non probabilistic (imprecise methods) methods, have been applied widely. In short, the slope non-deterministic analysis is to combine the probabilistic analysis or non probabilistic analysis with the deterministic slope stability analysis. It cannot be regarded as a completely new slope stability analysis method, but just an extension of the slope deterministic analysis. The slope failure probability calculated by slope non-deterministic analysis is a kind of complement of safety factor. Therefore, the accuracy of non deterministic analysis is not only depended on a suitable probabilistic or non probabilistic analysis method selected, but also on a more rigorous deterministic analysis method or geological model adopted. In this thesis, reliability concepts have been reviewed first, and some typical non-deterministic methods, including Monte Carlo Simulation (MCS), First Order Reliability Method (FORM), Point Estimate Method (PEM) and Random Set Theory (RSM), have been described and successfully applied to the slope stability analysis based on a numerical simulation method-Strength Reduction Method (SRM). All of the processes have been performed in a commercial finite difference code FLAC and a distinct element code UDEC. First of all, as the fundamental of slope reliability analysis, the deterministic numerical simulation method has been improved. This method has a higher accuracy than the conventional limit equilibrium methods, because of the reason that the constitutive relationship of soil is considered, and fewer assumptions on boundary conditions of slope model are necessary. However, the construction of slope numerical models, particularly for the large and complicated models has always been very difficult and it has become an obstacle for application of numerical simulation method. In this study, the excellent spatial analysis function of Geographic Information System (GIS) technique has been introduced to help numerical modeling of the slope. In the process of modeling, the topographic map of slope has been gridded using GIS software, and then the GIS data was transformed into FLAC smoothly through the program built-in language FISH. At last, the feasibility and high efficiency of this technique has been illustrated through a case study-Xuecheng slope, and both 2D and 3D models have been investigated. Subsequently, three most widely used probabilistic analyses methods, Monte Carlo Simulation, First Order Reliability Method and Point Estimate Method applied with Strength Reduction Method have been studied. Monte Carlo Simulation which needs to repeat thousands of deterministic analysis is the most accurate probabilistic method. However it is too time consuming for practical applications, especially when it is combined with numerical simulation method. For reducing the computation effort, a simplified Monte Carlo Simulation-Strength Reduction Method (MCS-SRM) has been developed in this study. This method has estimated the probable failure of slope and calculated the mean value of safety factor by means of soil parameters first, and then calculated the variance of safety factor and reliability of slope according to the assumed probability density function of safety factor. Case studies have confirmed that this method can reduce about 4/5 of time compared with traditional MCS-SRM, and maintain almost the same accuracy. First Order Reliability Method is an approximate method which is based on the Taylor\'s series expansion of performance function. The closed form solution of the partial derivatives of the performance function is necessary to calculate the mean and standard deviation of safety factor. However, there is no explicit performance function in numerical simulation method, so the derivative expressions have been replaced with equivalent difference quotients to solve the differential quotients approximately in this study. Point Estimate Method is also an approximate method involved even fewer calculations than FORM. In the present study, it has been integrated with Strength Reduction Method directly. Another important observation referred to the correlation between the soil parameters cohesion and friction angle. Some authors have found a negative correlation between cohesion and friction angle of soil on the basis of experimental data. However, few slope probabilistic studies are found to consider this negative correlation between soil parameters in literatures. In this thesis, the influence of this correlation on slope probability of failure has been investigated based on numerical simulation method. It was found that a negative correlation considered in the cohesion and friction angle of soil can reduce the variability of safety factor and failure probability of slope, thus increasing the reliability of results. Besides inter-correlation of soil parameters, these are always auto-correlated in space, which is described as spatial variability. For the reason that knowledge on this character is rather limited in literature, it is ignored in geotechnical engineering by most researchers and engineers. In this thesis, the random field method has been introduced in slope numerical simulation to simulate the spatial variability structure, and a numerical procedure for a probabilistic slope stability analysis based on Monte Carlo simulation was presented. The soil properties such as cohesion and friction angle were discretized to continuous random fields based on local averaging method. In the case study, both stationary and non-stationary random fields have been investigated, and the influence of spatial variability and averaging domain on the convergence of numerical simulation and probability of failure was studied. In rock medium, the structure faces have very important influence on the slope stability, and the rock material can be modeled as the combination of rigid or deformable blocks with joints in distinct element method. Therefore, much more input parameters like strength of joints are required to input the rock slope model, which increase the uncertainty of the results of numerical model. Furthermore, because of the limitations of the current laboratory and in-site testes, there is always lack of exact values of geotechnical parameters from rock material, even the probability distribution of these variables. Most of time, engineers can only estimate the interval of these variables from the limit testes or the expertise’s experience. In this study, to assess the reliability of the rock slope, a Random Set Distinct Element Method (RS-DEM) has been developed through coupling of Random Set Theory and Distinct Element Method, and applied in a rock slope in Sichuan province China.

Im Projekt wurde das Ermüdungsverhalten eines hochgefüllten, extrudierten Holz- Polymer- Werkstoffes (Wood Polymer-Composite, kurz: WPC) und dessen technisches Halbzeug (WPC-Systemprofil) im Anwendungsfeld der Fördertechnik erforscht. Kernsegment im Projekt ist das hochgefüllte WPC-Extrusionsprofil als Trag- und Gleitelement im Hängefördersystem (HFS). Im ersten Schritt wurde das Kriechverhalten (langzeitstatisch) und Ermüdungsverhalten unter dynamisch-schwingender Belastung (langzeitdynamisch) am produktspezifischen WPC-Material und am WPC-Systembauteil untersucht. Das Prüfregime bezieht sich dabei auf das reale Belastungskollektiv in der Anwendung des Hängefördersystems, welches vorrangig einer Dreipunktbiegebelastung im WPC-Systemprofil und einer Zugbelastung in der Verbindungsstelle entspricht. Aufbauend auf die Material- und Bauteiluntersuchung wurde der Dauerlauftest am Funktionsprototyp (Hängefördersystem) durchgeführt. Dabei wurden die Kriechneigung des WPC-Systemprofils und der Vorspannkraftverlust in der Verbindungsstelle im praxisrelevanten Fall überwacht. / In the research project the fatigue behavior of a high filled extruded Wood Polymer Composite (WPC) and its technical product were investigated in the application of material handling technology. The main focus of the project is the high filled WPC extrusion profile, which is applied as a sliding rail for the use in an overhead material handling system. In the first step the creep behavior (long-term static load) and fatigue behavior under dynamic-oscillating loads were studied on the product-specific WPC material and on the WPC component. The testing procedure refers to the real stress collection in the application of the overhead material handling system, which corresponds to a three-point bending load in the profile and a tensile load in the connection point. Furthermore, an endurance test was carried out under practical conditions on the overhead matrial handling system to oversee the long-term mechanical properties of the WPC sliding rail and the loss of the preloaded force in the connection point.