High-Frequency Mechanical Impacts (HFMI) is a surface treatment technique utilized to introduce residual stresses and extend the service life of structures. This project primarily focuses on studying the life extension effects of HFMI on welded structures that have undergone fatigue and have existing cracks. This is of significant importance for the maintenance of structures jointed with welds, such as bridge structures. Therefore, this project selected welded components with lower fatigue strength in bridge structures as research specimens for analysis and testing.To simulate the conditions that bridges experienced over many years of usage, initial notches were prepared near the weld toes. A data acquisition and control system was developed to analyze crack propagation behavior, using NI devices to assess the pre-fatigue condition and control the fatigue testing machine. To understand the test results, fracture mechanics calculations and finite element simulations were applied for comparison.In conclusion, based on the experimental results, HFMI improves the life of welded structures with cracks. This demonstrates the feasibility of using HFMI for the maintenance of bridge welding structures and extending their service life. / HFMI (High-Frequency Mechanical Impacts) är en ytbehandlingsteknik som används för att införa restspänningar och förlänga livslängden hos strukturer. Detta projekt fokuserar främst på att studera effekterna av HFMI på svetsade strukturer som har genomgått utmattning och har befintliga sprickor. Detta är av stor betydelse för underhållet av strukturer som sammanfogas med svetsar, t.ex. brokonstruktioner. I detta projekt valdes därför svetsade komponenter med lägre utmattningshållfasthet i brokonstruktioner som forskningsexemplar för analys och provning.För att simulera de förhållanden som broar utsätts för under många års användning förbereddes initiala sprickor vid svetsfogarna. Ett datainsamlings och styrsystem utvecklades för att analysera sprickornas utbredning, med hjälp av NI-enheter för att bedöma tillståndet före utmattning och styra utmattningsprovningsmaskinen. För att göra de experimentella resultaten mer rimliga användes brottmekaniska beräkningar och finita elementsimuleringar för jämförelse.Slutsatsen är att HFMI, baserat på de experimentella resultaten, förbättrar livslängden avsevärt för svetsade strukturer med sprickor av djup mindre än 0.5 mm. Detta visar att det är möjligt att använda HFMI för underhåll av svetsade brokonstruktioner och förlänga deras livslängd.

Prostate cancer is one of the most common types of cancer worldwide and claims hundreds of thousands of lives annually. Currently the most common treatment for prostate cancer is external beam radiotherapy, however, this treatment comes with serious side effects since it lacks selectivity for the cancer cells. Therefore, less harmful treatments are needed and sought for, such as targeted treatments that are intended to only affect cancer cells and thereby reduce the side effects. Targeted treatments require a target that differentiates the cancer cells from healthy cells. A promising target candidate that has gained attention in recent years is gastrin releasing peptide receptor (GRPR), a protein commonly overexpressed in prostate cancer cells. Furthermore, a targeting molecule intended to bind to the target is also required. For this purpose, the bombesin analogue RM26, a high affinity GRPR binder, shows promise. Previous studies have led to the development of RM26-conjugates for the purpose of targeted prostate cancer radiotherapy. In these conjugates RM26 has been linked to a DOTA-chelator for radiolabeling, and an albumin binding domain (ABD) to prolong the conjugate’s half-life in vivo by binding to human serum albumin (HSA). The idea is that the RM26-conjugate will bind to both HSA in the blood and to GRPR on the prostate cancer cells and eliminate the cancer cells with the radiation from the radionuclide attached to the DOTA-chelator. Although these earlier studied conjugates have been very promising some improvements of certain aspects need to be achieved, mainly to improve the biodistribution with retained GRPR binding affinity. Therefor the purpose of this project was to produce three new versions of previous RM26- conjugates and evaluate if they are suitable for further prostate cancer therapy studies. The three RM26-conjugates were developed with primarily recombinant expression in E. coli cells and solid phase peptide synthesis (SPPS). The characterization phase in this project was carried out with mainly five different methods: matrix-assisted laser desorption ionization time- of-flight mass spectrometry (MALDI-TOF-MS), electrospray ionization- mass spectrometry (ESI-MS), circular dichroism (CD), surface plasmon resonance (SPR) and flow cytometry. The results showed that all three new RM26-conjugates were possible to produce and yielded final products corresponding to the expected molecular weights. Furthermore, the results indicate that all three RM26-conjuagtes are stable and maintain their structural properties under in vivo- temperatures and that they have high binding affinity for HSA. Further studies need to be conducted before drawing any certain conclusions regarding GRPR binding affinity. / Prostatacancer är en av de mest vanligt förekommande cancertyperna världen över och skördar hundratusentals liv årligen. I nuläget är extern strålbehandling det vanligaste terapialternativet mot prostatacancer, men denna behandling kommer med allvarliga biverkningar på grund av att den saknar selektivitet för cancerceller. Därför finns ett stort behov av mindre skadliga behandlingsformer, såsom riktade behandlingar som endast är avsedda att påverka cancerceller och därigenom minska biverkningarna. Riktade behandlingar kräver ett mål som skiljer cancercellerna från friska celler. En lovande målkandidat som har uppmärksammats de senaste åren är gastrinfrisättande peptidreceptor (GRPR), ett protein som vanligtvis överuttrycks i prostatacancerceller. I tillägg så krävs också en målsökande molekyl avsedd att binda till målet. För detta ändamål visar bombesinanalogen RM26, en GRPR-bindare med hög affinitet, sig vara lovande. Tidigare studier har utvecklat RM26-konjugat för målinriktad strålbehandling av prostatacancer. Dessa konjugat består av en RM26-peptid bunden till en DOTA-kelator för radioinmärkning och en albuminbindande domän (ABD) för att förlänga konjugatens halveringstid in vivo genom att binda till humant serumalbumin (HSA). Syftet med RM26- konjugaten är att de ska binda till både HSA i blodet och GRPR på prostatacancercellerna, och därmed eliminera cancercellerna med strålning från den radioinmärkta DOTA-kelatorn. Även om de tidigare RM26-konjugaten har varit mycket lovande krävs det att vissa förbättringar av några aspekter uppnås, främst affiniteten för GRPR. Syftet med detta projekt var därför att producera tre nya versioner av tidigare RM26-konjugat och utvärdera ifall de uppvisar tillfredsställande egenskaper. De tre RM26-konjugaten utvecklades primärt rekombinant i E. coli-celler och fastfas- peptidsyntes (SPPS). Karaktäriseringsfasen i detta projekt genomfördes med huvudsakligen fem olika metoder: MALDI-TOF-MS, elektrosprejjonisering-masspektrometri (ESI-MS), cirkulär dikroism (CD), ytplasmonresonans (SPR) och flödescytometri. Resultaten visade att alla tre nya RM26-konjugat var möjliga att producera och gav slutprodukter motsvarande de förväntade molekylvikterna. Vidare indikerar resultaten att alla tre RM26-konjugat är stabila och bibehåller sina strukturella egenskaper under in vivo-temperaturer och att de har hög affinitet för HSA. Ytterligare studier bör utföras innan säkrare slutsatser kan dras angående GRPR-bindningsaffinitet.

Marknaden för proteinbaserade läkemedel, de så kallade biologiska läkemedlen, är idag en industri som omsätter miljarder. Ett vanligt sätt att utveckla dessa läkemedel på är med hjälp av monoklonala antikroppar då de kan binda till sitt mål med hög specificitet. Däremot begränsas denna teknik av en lång och dyr produktion som dessutom kräver däggdjursbaserade uttrycksystem. En alternativ teknik till de monoklonala antikropparna är att använda små proteiner som enkelt kan produceras i bakterier till en låg kostnad. Dock begränsas denna metod av de små proteinernas korta cirkuleringstid i blodet. I ett tidigare projekt, har ett litet protein vid namnet ABDderived affinity ProTein (ADAPT) på cirka 7 kDa, utvecklats för att kunna binda till både humant serumalbumin (HSA) för att förlänga cirkulationstiden i blodet och Interleukin 17c (IL17c) som är ett pro-inflammatorisk cytokin. Studien visade dock att ADAPT proteinet inte samtidigt kunde binda till de båda molekylerna tillräckligt effektivt. Syftet med denna uppsats är därför att undersöka om det nämnda proteinet kan optimeras genom så kallad multimering och/eller manipulering av bindningssätet för HSA i syfte att åstadkomma en effektiv och mer långvarig cirkulationstid i blodet samtidigt som det binder sig till sitt mål, IL17c. Tio nya versioner av ADAPT proteinet har utvecklats genom att klona och transformera proteiner till en högt producerande Escherichia coli (E. coli) stam. Proteinerna har sedan producerats och renats fram. Det kunde observeras att proteinerna hade den önskade renheten för att kunna karaktäriseras. Vidare var det möjligt att se att proteinerna hade sin önskade molekylvikt och erhöll sin förväntade struktur som en alfahelix. Proteinernas smältpunkter hade förbättrats eller var liknande jämfört med det ursprungliga proteinet. Dessutom kunde alla proteiner återgå till sin ursprungliga struktur efter upphettning. Utvärderingen av proteinernas bindningskapacitet, med original proteinet som referens, visade på en ökad affinitet till sitt mål, IL17c, för två dimerer och trimeren samt en jämförbar affinitet för två av monomererna med ett manipulerat bindingssäte till HSA. Interaktion till HSA var jämförbar med den ursprungliga ADAPT molekylen för alla nya varianter förutom monomererna med ett manipulerat bindingssäte och dimeren med två manipulerat bindingssäten till HSA. Evaluering av de nya proteinernas kapacitet att binda samtidigt till HSA och IL17c visade att det var gynnsamt med en dimereiserad molekyl då det skapade en distans mellan molekylerna och dess bindningssäten. Vidare kunde det också visas att ordningen som molekylerna interagerade med varandra påverkade proteinernas simultana bindning. / The market for protein-based drugs, or the so-called biopharmaceuticals, is a multibillion-dollar industry today. In the development of protein-based drugs it is common to use monoclonal antibodies (mAbs) due to their ability to bind to its target with high specificity. However, therapeutical development of mAbs is limited by its long and expensive production in mammalian expression system. An alternative to mAbs are the so-called alternative scaffolds which are small proteins that can be produced in bacteria at lower costs. Although a drawback with the latter proteins is their short serum half-life. A small scaffold protein, ABD-Derived Affinity ProTein (ADAPT) of approximate 7 kDa was earlier engineered to obtain bispecific affinity, to Human Serum Albumin (HSA), to extend its half-life, as well as to the pro-inflammatory cytokine, Interleukin 17c (IL17c). Unfortunately, it was shown that the simultaneous binding was not efficient enough for its desired purpose. The aim with this project was therefore to investigate if the previous mentioned binder could be optimized by multimerization and/or manipulation of the HSA binding site for an efficient half-life extension. By generating ten new designs of the ADAPT variants, it was observed that the new variants had stable alpha helical structures and an improved or similar melting temperature as the original variant. The evaluation of the target binding displayed an improved affinity to the target, IL17c, for two of the dimeric versions as well as for the trimer and a comparable affinity for two of the monomers with a manipulated HAS binding site. The interaction to HSA was comparable to the original ADAPT for all binders except from the monomers with impaired HSA binding and the dimer with two impaired HSA binding sites. The evaluation of the simultaneous binding showed that it was favored by dimerization when a distance between the two molecule and their binding surfaces was added. Moreover, it could also be seen that the order of binding events had an impact on the simultaneous binding.

As a consequence of the recent deregulation in the electrical power production industry, there has been a shift in the traditional ownership of power plants and the way they are operated. To hedge their business risks, the many new private entrepreneurs enter into long-term service agreement (LTSA) with third parties for their operation and maintenance activities. As the major LTSA providers, original equipment manufacturers have invested huge amounts of money to develop preventive maintenance strategies to minimize the occurrence of costly unplanned outages resulting from failures of the equipments covered under LTSA contracts. As a matter of fact, a recent study by the Electric Power Research Institute estimates the cost benefit of preventing a failure of a General Electric 7FA or 9FA technology compressor at $10 to $20 million. Therefore, in this dissertation, a two-phase data analytics approach is proposed to use the existing monitoring gas path and vibration sensors data to first develop a proactive strategy that systematically detects and validates catastrophic failure precursors so as to avoid the failure; and secondly to estimate the residual time to failure of the unhealthy items. For the first part of this work, the time-frequency technique of the wavelet packet transforms is used to de-noise the noisy sensor data. Next, the time-series signal of each sensor is decomposed to perform a multi-resolution analysis to extract its features. After that, the probabilistic principal component analysis is applied as a data fusion technique to reduce the number of the potentially correlated multi-sensors measurement into a few uncorrelated principal components. The last step of the failure precursor detection methodology, the anomaly detection decision, is in itself a multi-stage process. The obtained principal components from the data fusion step are first combined into a one-dimensional reconstructed signal representing the overall health assessment of the monitored systems. Then, two damage indicators of the reconstructed signal are defined and monitored for defect using a statistical process control approach. Finally, the Bayesian evaluation method for hypothesis testing is applied to a computed threshold to test for deviations from the healthy band. To model the residual time to failure, the anomaly severity index and the anomaly duration index are defined as defects characteristics. Two modeling techniques are investigated for the prognostication of the survival time after an anomaly is detected: the deterministic regression approach, and parametric approximation of the non-parametric Kaplan-Meier plot estimator. It is established that the deterministic regression provides poor prediction estimation. The non parametric survival data analysis technique of the Kaplan-Meier estimator provides the empirical survivor function of the data set comprised of both non-censored and right censored data. Though powerful because no a-priori predefined lifetime distribution is made, the Kaplan-Meier result lacks the flexibility to be transplanted to other units of a given fleet. The parametric analysis of survival data is performed with two popular failure analysis distributions: the exponential distribution and the Weibull distribution. The conclusion from the parametric analysis of the Kaplan-Meier plot is that the larger the data set, the more accurate is the prognostication ability of the residual time to failure model.

<p>  </p> <p>There has been a growing interest within the aerospace industry for shifting towards a digital twin approach, for reliable assessment of individual components during the product lifecycle - across design, manufacturing, and in-service maintenance, repair & overhaul (MRO) stages. The transition towards digital twins relies on continuous updating of the product lifecycle datasets and interoperable exchange of data applicable to components, thereby permitting engineers to utilize current state information to make more-informed downstream decisions. In this thesis, we primarily develop a framework to store, track, update, and retrieve product lifecycle data applicable to a serialized component, its features, and individual locations. </p> <p>From a structural integrity standpoint, the fatigue performance of a component is inherently tied to the component geometry, its material state, and applied loading conditions. The manufacturing process controls the underlying material microstructure, which in turn governs the mechanical properties and ultimately the performance. The processing also controls the residual stress distributions within the component volume, which influences the durability and damage tolerance of the component. Hence, we have demonstrated multiple use cases for fatigue life assessment of critical aerospace components, by using the developed framework for efficiently tracking and retrieving (i) the current geometric state, (ii) the material microstructure state, and (iii) residual stress distributions.</p> <p>Model-based definitions (MBDs) present opportunities to capture both geometric and non-geometric data using 3D computer-aided design (CAD) models, with the overarching aim to disseminate product information across different stages of the lifecycle. MBDs can potentially eliminate error-prone information exchange associated with traditional paper-based drawings and improve the fidelity of component details, captured using 3D CAD models. However, current CAD capabilities limit associating the material information with the component’s shape definition. Furthermore, the material attributes of interest, viz., material microstructures and residual stress distributions, can vary across the component volume. To this end, in the first part of the thesis, we implement a CAD-based tool to store and retrieve metadata using point objects within a CAD model, thereby creating associations to spatial locations within the component. The tool is illustrated for storage and retrieval of bulk residual stresses developed during the manufacturing of a turbine disk component, acquired from process modeling and characterization. Further, variations in residual stress distribution owing to process model uncertainties have been captured as separate instances of the disk’s CAD models to represent part-to-part variability as an analogy to track individual serialized components for digital twins. The propagation of varying residual stresses from these CAD models within the damage tolerance analysis performed at critical locations in the disk has been demonstrated. The combination of geometric and non-geometric data inside the MBD, via storage of spatial and feature varying information, presents opportunities to create digital replica or digital twin(s) of actual component(s) with location-specific material state information.</p> <p>To fully realize a digital twin description of components, it is crucial to dynamically update information tied to a component as it evolves across the lifecycle, and subsequently track and retrieve current state information. Hence, in the second part of the thesis, we propose a dynamic data linking approach to include material information within the MBDs. As opposed to storing material datasets directly within the CAD model in the previous approach, we externally store and update the material datasets and create data linkages between material datasets and features within the CAD models. To this end, we develop a model-based feature information network (MFIN), a software agnostic framework for linking, updating, searching, and retrieving of relevant information across a product’s lifecycle. The use case of a damage tolerance analysis for a compressor bladed-disk (blisk) is demonstrated, wherein Ti-6Al-4V blade(s) are linear friction welded to the Ti-6Al-4V disk, comprising well-defined regions exhibiting grain refinement and high residuals stresses. By capturing the location-specific microstructural information and residual stress fields at the weld regions, this information was accessed within the MFIN and used for downstream damage tolerant analysis. The introduction of the MFIN framework facilitates access to dynamically evolving as well as location-specific data for use within physics-based models.</p> <p>In the third part of thesis, we extend the MFIN framework to enable a physics-based, microstructure sensitive and location-specific fatigue life analysis of a component. Traditionally, aerospace components are treated as monolithic structures during lifing, wherein microstructural information at individual locations are not necessarily considered. The resulting fatigue life estimates are conservative and associated with large uncertainty bounds, especially in components with gradient microstructures or distinct location-specific microstructures, thereby leading to under usage of the component’s capabilities. To improve precision in the fatigue estimates, a location-specific lifing framework is enabled via MFIN, for tracking and retrieval of microstructural information at distinct locations for subsequent use within a crystal plasticity-based fatigue life prediction model. A use case for lifing dual-microstructure heat treated LSHR turbine disk component is demonstrated at two locations, near the bore (fine grains) and near the rim (coarse grains) regions. We employ the framework to access (a) the grain size statistics and (b) the macroscopic strain fields to inform precise boundary conditions for the crystal plasticity finite-element analysis. The illustrated approach to conduct a location-specific predictive analysis of components presents opportunities for tailoring the manufacturing process and resulting microstructures to meet the component’s targeted requirements.</p> <p>For reliably conducting structural integrity analysis of a component, it is crucial to utilize their precise geometric description. The component geometries encounter variations from nominal design geometries, post manufacturing or after service. However, traditionally, stress analyses are based on nominal part geometries during assessment of these components. In the last part of the thesis, we expand the MFIN framework to dynamically capture deviations in the part geometry via physical measurements, to create a new instance of the CAD model and the associated structural analysis. This automated workflow enables engineers for improved decision-making by assessing (i) as-manufactured part geometries that fall outside of specification requirements during the materials review board or (ii) in-service damages in parts during the MRO stages of the lifecycle. We demonstrate a use case to assess the structural integrity of a turbofan blade that had experienced foreign object damage (FOD) during service. The as-designed geometry was updated based on coordinate measurements of the damaged blade surfaces, by applying a NURBS surface fit, and subsequently utilized for downstream finite-element stress analysis. The ramifications of the FOD on the local stresses within the part are illustrated, providing critical information to the engineers for their MRO decisions. The automated flow of information from geometric inspection within structural analysis, enabled by MFIN, presents opportunities for effectively assessing products by utilizing their current geometries and improving decision-making during the product lifecycle.</p>