The project was developed within the engineering degree in engineering technology, and is focused in welding together of two different materials. Welds will be done on a high strength steel Domex 420 MC and deep drawing steel DC01 using laser welding, and will be compared with the method of electron beam welding. Part of this project is a scientific research describing the basic physical principles of both methods, different types of lasers, welding material properties and inspection of welds. In the experimental part was carried tensile test, macroscopic and microscopic examination. Finally, work is to evaluate the individual tests.

This thesis introduces issues of passenger car side-door hinges. Practical part of this thesis deals with modifying the current low-cost side-door hinge for Edscha Automotive Kamenice s.r.o. First, material was chosen to decrease weight while maintaining the required mechanical properties. Then follows the detail design of the hinge model, which was created in the software program Catia. Heat and surface treatments are described. Both treatments ensures the hinge's final features. To verify the strength of the hinge, tensile and sag test was simulated in Ansys. Subsequently, record from the consultation of the hinge's manufacturability in series and the hinge’s cutting plans are provided. At the end of the thesis, the assembling procedure is suggested. Final part of the thesis compares the developed low-cost hinge against two similar side door hinges.

Práce byla zaměřena na ověření platnosti koncepce master křivky pro hodnocení heterogenních svarových spojů, resp. teplotně stárnutých svarů. Současně bylo cílem disertace vyvinout kvantitativní model pro predikci referenční teploty lokalizující tranzitní oblast na teplotní ose za použití dat získaných z tahové zkoušky, a to za použití metody umělých neuronových sítí. Studie je současně zaměřena na heterogenní svarový spoj připravený tavným svařováním. Je zacílena na hodnocení lomového chování v tranzitní oblasti nejméně odolné části svaru, tj. tepelně ovlivněné zóny ferritické oceli v blízkosti zóny natavení s vysokolegovaným materiálem. Pro predikci referenční teploty master křivky je použita zmíněná metoda neuronových sítí, a to za použití dat z tahových zkoušek a měření tvrdosti. Predikovaná referenční teplota byla ověřována na základě výsledku experimentálních měření. Vytvoření modelu za použití neuronových sítí vyžaduje dostatečné množství dat a není vždy snadno tuto podmínku splnit. V případě sledovaného problému to znamenalo použití dat z dostatečně věrohodných zdrojů (skupiny Křehký lom ÚFM AVČR) a se známou metalurgickou historií. Smysl práce je tak možno spatřovat ve vývoji modelu neuronové sítě, která bude dostatečně přesně predikovat referenční teplotu. Celkově byla pro tyto účely použita data z 29 nízkolegovaných ocelí. Pro účely vývoje byly použity kromě hladkých zkušebních tyčí, rovněž tahové zkoušky s obvodovým vrubem testované při kritické teplotě křehkosti (mez makroplastických deformací) a při teplotě pokojové. Při tvorbě modelu byla postupně v různých kombinacích využita všechna data z uvedených zkoušek. Studie ukázala, že referenční teplota charakterizující tranzitní chování lomové houževnatosti oceli s převažující feritickou strukturou je jedinečným parametrem predikovatelným na základě vybraných charakteristik tahových zkoušek.

Corrosion of steel reinforcement has been identified as one of the major problems facing many existing reinforced concrete structures including bridges. The exposure to aggressive environmental conditions such as those with high concentrations of chloride ions due to the use of de-icing salt in cold regions or high concentrations of carbon dioxide due to increased greenhouse gas emissions, accelerate the initiation process of corrosion. As corrosion initiates, the structural performance in terms of load-carrying capacity, ductility, and service life deteriorate over time. Coupling the effect of reinforcement corrosion with service loads may further weaken the structural performance of reinforced concrete bridges due to the presence of transverse load-induced cracks. Accordingly, a research program was conducted to evaluate the structural performance of reinforced concrete beams subjected to coupled effects of service loads and reinforcement corrosion. The research project consisted of combined experimental and numerical investigations. The experimental phase consisted of tests of nine small-scale beams and six large-scale beams. The beams were designed, constructed, instrumented, and loaded under a four-point load test. The primary test variables were the applied corrosion current density, level of corrosion, and level of sustained loading as percentage of beam ultimate capacity (0% Pu, 40% Pu, and 60% Pu). The corrosion level of steel reinforcement was quantitatively assessed using gravimetric weight measurements and three-dimensional laser scanner technique. Test results indicated that failure of corroded RC beams was brittle due to premature rupture of corroded steel bars, which was attributed to the development of localized corrosion at the sections with flexural cracks in beams. Furthermore, it was found that beams subjected to higher levels of service loads, experienced further reductions in ultimate load capacity and ductility. In addition, tensile tests were used to evaluate the effect of corrosion on the mechanical performance of steel bars retrieved from the corroded beams. It was found that the tensile strength of corroded steel bars, based on nominal sectional area, was reduced with the increase of corrosion levels. In contrast, the tensile strength, based on minimum sectional area, was not influenced by the non-uniform distribution and localization of corrosion. In fact, there was a slight increase in strength with the increase of corrosion levels. The numerical phase consisted of finite element analyses of beams using DIANA FE analysis software. A simplified approach was implemented to introduce the damage induced by corrosion into two-dimensional nonlinear FE models, based on the experimental testing of corroded beams and corroded steel bars. The analyses were reasonably accurate in predicting cracking patterns, residual load capacity, residual ductility, and failure modes of corroded beams. Subsequently, the validated model was used to conduct a parametric study on the level of service loads, level of corrosion, strength of concrete, and tensile reinforcement ratio. It was found that the FE model of corroded beams was strongly influenced by the level of service loads, level of corrosion, and tensile reinforcement ratio.

No description available.

The current and forecasted global consumption of plastic packaging and products through the 21st century combined with the already reported and growing negative impact of plastics on the environment due to plastics being synthesized from nonrenewable resources that do not biodegrade is of serious concern. However, recent advances in starch technology including the development of thermoplastic starch (TPS) materials —polymers that are both renewable and biodegradable—have brought hope to reducing this impact. The mechanical properties of thermoplastic starch have often been improved by blending with synthetic polymers. One issue that arises with blending is volatilization of the melt from moisture in the TPS materials. Ecostarch™ a proprietary, pelletized thermoplastic starch resin formulated from potato starch, was processed and tested to observe injection molding processability at various moisture levels, in pure TPS as well as various blend ratios with high-density polyethylene (HDPE) and polypropylene (PP). This study evaluated and analyzed the effects of the TPS pellet moisture content on void formation in the plastic pre-injection melt and subsequent molded part mechanical properties. Statistical analysis of the test results showed that moisture had a significant effect on void formation in the plastic melt. In TPS/HDPE blends, voids percent (as measured by cross section area) increased by 300-350% from 0.6% to 1.4% moisture levels. In unblended TPS, void percent increased by 150% from 0.4% to 1.4% moisture levels. In the unblended TPS parts, impact strength (energy in ft-lb) was decreased by 1% from 0.6% to 1.4% moisture level. In the TPS/HDPE and TPS/PP blends, there was no significant effect on impact strength due to the moisture percent levels of the TPS. Modulus decreased by 25% from 0.4% to 1.4% moisture level in unblended TPS parts. From 0.6% to 1.4% change in TPS moisture content, the modulus of the TPS/HDPE blend decreased by 9% at a 30% TPS/70% HDPE blend and decreased by 14% at a 70% TPS/30% HDPE blend. Though the moisture of TPS did not have a significant impact on the tensile strength of TPS/HDPE blends, the tensile strength of TPS/PP blend samples were significantly affected: a change from 0.6% to 1.4% moisture increased tensile strength 34% at a 70% TPS/30% PP blend and increased tensile strength by 22% at a 30% TPS/70% PP blend. Thus the results of this study highlight the relationships between moisture, voids, and mechanical performance of TPS and TPS/Polymer blends.

Year 2019, football, rugby, netball and skiing had most occurring ACL injuries, listed by United Kingdom National Ligament Report (NLR). The standard procedure treatment of complete laceration of the ACL, is performed by tissue autograft implantation designed from a patellar tendon, for replacement of damaged tissue using orthopaedic surgery. The aim of this thesis is to design and fabricate an ACL graft, attempting to mimic the natural ACL, for the purpose of tissue reconstruction. The desired graft analogues exhibited properties imitating native connective tissue, reducing pain through drug delivery with great biocompatibility and enhance suture mechanical strength. Various biomaterials were implemented into this study, utilising strategies; polymer solution fabrication, electrospinning, hydrogel synthesis, mechanical braiding and graft assembly to fabricate an ACL graft. The polymeric material poly (E- caprolactone) (PCL) was researched, utilising its ability to fabricate scaffolds. Results showed, three analogue ACL grafts (Braided PCL-BP, Braided PCL + Hydrogel-BPH & Braided PCL + Sutures-BPS) created utilising the properties of braiding, hydrogels and sutures, ultimately improving the versatility of electrospinning for tissue engineering and reconstruction. Graft analogues were tested and compared against patellar tendons producing similar tensile properties. Poly vinyl alcohol (PVA) hydrogels successfully held ibuprofen, revealing drug delivery characteristics, polyester threads improved mechanical properties of electrospun grafts and dry degradation showed that PCL did not lose significant mass over two months. Conclusion, tensile strength of patella tendon was 395x, 790x & 56x of analogue grafts (BP, BPH & BPS) respectively, having potential for improvement of tensile parameters for ligament reconstruction.

No description available.

[pt] O ensaio de tração é o ensaio mecânico mais aplicado para a obtenção das propriedades mecânicas de polímeros. Por meio de um ensaio de tração é obtida a curva tensão-deformação, e é a partir desta curva que são obtidas propriedades mecânicas tais como o módulo de elasticidade, a tenacidade e a resiliência do material, as quais podem ser utilizadas na identificação de comportamentos mecânicos equivalentes em materiais poliméricos, seja para a diferenciação de resíduos plásticos para a reciclagem ou para a classificação de um material plástico reciclado quanto ao teor de um determinado polímero em sua composição. Porém, a obtenção das propriedades mecânicas a partir da curva tensão-deformação envolve cálculos e ajustes nos intervalos da curva em que essas propriedades são determinadas, tornando a obtenção das propriedades mecânicas um processo complexo sem a utilização de programas computacionais especializados. A partir da compreensão do padrão de comportamento da curva tensão-deformação de um material, algoritmos de aprendizagem de máquina (AM) podem ser ferramentas eficientes para automatizar a classificação de diferentes tipos de materiais poliméricos. Com o objetivo de verificar a acurácia de um algoritmo de AM na classificação de três tipos de polímeros, foram realizados ensaios de tração em corpos de prova de polietileno de alta densidade (PEAD), polipropileno (PP) e policloreto de vinila (PVC). O conjunto de dados obtido a partir das curvas tensão-deformação foi utilizado no treinamento de uma rede neural artificial perceptron de múltiplas camadas (PMC). Com uma acurácia de 0,9261 para o conjunto de teste, o modelo obtido a partir da rede PMC foi capaz de classificar os polímeros com base nos dados da curva tensão-deformação, indicando a possibilidade do uso de modelos de AM para automatizar a classificação de materiais poliméricos a partir de dados de ensaios de tração. / [en] The tensile test is the most applied mechanical test to obtain the mechanical properties of polymers, which can be used in polymeric materials classification. Through a tensile test is obtained the stress-strain curve, is from which mechanical properties such as the modulus of elasticity, tenacity, and resilience of the material are obtained, which can be used to identify equivalent mechanical behaviors in polymeric materials, whether for the distinguishing plastic waste for recycling or for classifying recycled plastic material according to the content of a polymer type in its composition. However, obtaining mechanical properties from the stress-strain curve involves calculations and adjustments in the intervals of the curve in which these properties are determined, turning it into a complex process without the use of specialized software. By understanding the behavior pattern of a material’s stress-strain curve, machine learning (ML) algorithms can be efficient tools to automate the classification of different types of polymeric materials. To verify the accuracy of an ML algorithm in classifying three types of polymers, tensile tests were performed on specimens made of high-density polyethylene (HDPE), polypropylene (PP), and polyvinyl chloride (PVC). The dataset obtained from the stress-strain curves was used in the training of a multilayer perceptron (MLP) neural network. With an accuracy of 0.9261 for the test set, the model obtained from the MLP neural network was able to classify the polymers based on the stress-strain curve data, thus indicating the possibility of using an ML algorithm to automate the classification of polymeric materials based on tensile test data.

This thesis investigates the challenges and opportunities of recycling PA6-GF30, a glass-filled polyamide, to address the pressing environmental concerns surrounding polymer waste. Through a collaboration between Thule Group and Jönköping University, it aims to understand how the properties of recycled materials evolve over time and reprocessing cycles, proposing practical methods for their utilization in sustainable manufacturing practices. Thule Group's commitment to reducing emissions entails transitioning to sustainable materials, particularly through increased use of recycled engineering materials like PA6-GF30, to lower the carbon footprint of products, emphasizing the importance of maintaining product quality and safety while exploring the effects of recycled materials on mechanical properties. Through producing and testing post-industrial and post-consumer samples added to virgin PA6-GF30 with varying ratios, comparison with the commercially available polymers was conducted. In total, 15 different mixtures of pellets of different quantity and quality of recycled composites were investigated with tensile test and impact test, moreover the fibers of some batches were filtrated from the matrix and the fiber aspect ratio was examined with the help of an optical microscope. Results illustrated that recycled polymers generally showed more mechanical property degradation as the ratio of recycled polymers were increased. Furthermore, adding the same amount of post-consumer regrinds as opposed to post-industrial was more detrimental to the overall mechanical performance. Post-industrial composite regrinds performed 11,3% worse in UTS, meanwhile post-consumer regrinds dropped by 25,5% in the same characteristic when the samples made of 100% recycled materials were compared to the virgin composite.  The reason behind this phenomenon was investigated and supported by microscopy. One of them is the natural aging of the material that operates through chain scission, that slowly makes that polymer stiffer and weaker. The other and more dominant reason is the damage taken by the fibers, that create numerous stress concentration sites at fiber ends, within the structure, ultimately damaging the fiber-matrix interface.