Recent improvements in deep learning architectures, combined with the strength of modern computing hardware such as graphics processing units, has lead to significant results in the field of image analysis. In this thesis work, locally connected architectures are employed to reduce noise in flash X-ray diffraction images. The layers in these architectures use convolutional kernels, but without shared weights. This combines the benefits of lower model memory footprint in convolutional networks with the higher model capacity of fully connected networks. Since the camera used to capture the diffraction images has pixelwise unique characteristics, and thus lacks equivariance, this compromise can be beneficial. The background images of this thesis work were generated with an active laser but without injected samples. Artificial diffraction patterns were then added to these background images allowing for training U-Net architectures to separate them. Architecture A achieved a performance of 0.187 on the test set, roughly translating to 35 fewer photon errors than a model similar to state of the art. After smoothing the photon errors this performance increased to 0.285, since the U-Net architectures managed to remove flares where state of the art could not. This could be taken as a proof of concept that locally connected networks are able to separate diffraction from background in flash X-Ray imaging.

Coherent diffractive imaging (CDI) has become a very popular technique over the past two decades. CDI is a "lensless" imaging method which replaces the objective lens of a conventional microscope by a computational image reconstruction procedure. Its increase in popularity came together with the development of X-ray free-electron lasers (XFELs) which produce extremely bright and coherent X-rays. By facilitating these unique properties, CDI enables structure determination of non-crystalline samples at nanometre resolution and has many applications in structural biology, material science and X-ray optics among others. This work focuses on two specific CDI techniques, flash X-ray diffractive imaging (FXI) on biological samples and X-ray ptychography. While the first FXI demonstrations using soft X-rays have been quite promising, they also revealed remaining technical challenges. FXI becomes even more demanding when approaching shorter wavelengths to allow subnanometre resolution imaging. We described one of the first FXI experiments using hard X-rays and characterized the most critical components of such an experiment, namely the properties of X-ray focus, sample delivery and detectors. Based on our findings, we discussed experimental and computational strategies for FXI to overcome its current difficulties and reach its full potential. We deposited the data in the Coherent X-ray Database (CXIDB) and made our data analysis code available in a public repository. We developed algorithms targeted towards the needs of FXI experiments and implemented a software package which enables the analysis of diffraction data in real time. X-ray ptychography has developed into a very useful tool for quantitative imaging of complex materials and has found applications in many areas. However, it involves a computational reconstruction step which can be slow. Therefore, we developed a fast GPU-based ptychographic solver and combined it with a framework for real-time data processing which already starts the ptychographic reconstruction process while data is still being collected. This provides immediate feedback to the user and allows high-throughput ptychographic imaging. Finally, we have used ptychographic imaging as a method to study the wavefront of a focused XFEL beam under typical FXI conditions.  We are convinced that this work on developing strategies and algorithms for FXI and ptychography is a valuable contribution to the development of coherent diffractive imaging.

Inom materialforskning och en stor del av den mekaniska och mekatroniska industrin finns ett intresse av att utnyttja blixtröntgen för att studera dynamiska händelseförlopp i inneslutna system, ej synbara med konventionella kameror. I och med att många rörelser inom de benämna områdena även sker i hyperhastighet så tillåter blixtröntgen statisk bildtagning  av rörelser i flera km/s, med minimal rörelseoskärpa. Detta examensarbete har grundats i att utveckla och utvärdera koncept för en komplett systemuppställning inklusive höghastighetskamera för denna tillämpning.  Syftet med arbetet har således varit att både identifiera och definiera produktens ingående produktkrav, för att spegla den funktion och syftet som önskas uppfyllas, och utifrån detta generera koncept för uppställningen på systemnivå, samt för separata  komponenter. Slutligen har de utvalda koncepten utvärderats genom praktiska prestandatester för att kontrollera dess uppfyllelse av produktkraven. Datainsamlingen för arbetet skedde i form av flertalet praktiska experiment för insamling av kvantitativ data, samt återkommande uppföljningsmöten med involverade medarbetare för insamling av kvalitativ data.  Undersökningen resulterade i ett koncept för en slutprodukt, benämnt funktionsprototyp som motsvarade och uppfyllde de definierade produktkraven vad gäller funktionalitet och prestanda. En diskussion fördes även för den kommande vidareutvecklingen av slutprodukten, inklusive färdigställandet av samtliga koncept och den följande designfasen. / In materials research and a large part of the mechanical and mechatronic industry, there is an interest in using flash X-rays to study dynamic events in enclosed systems, not visible with conventional cameras. Since many movements within the named areas also take place at hyper-speed, flash X-rays allow to capture static images of movements in several km / s, with minimal distortion. This thesis has been based on developing and evaluating concepts for a complete system setup including a high speed camera for this application. The purpose of the work has thus been to both identify and define the product's included product requirements, to reflect the function and purpose that is desired to be fulfilled, and based on this generate concepts for the set-up at system level, as well as for separate components. Finally, the selected concepts have been evaluated through practical performance tests to check its compliance with the product requirements. The data collection for the work took place in the form of two practical experiments for the collection of quantitative data, as well as recurring follow-up meetings with involved employees for the collection of qualitative data. The study resulted in a concept for an end product, called an end concept that corresponded to, and met the defined product requirements in terms of functionality and performance. A discussion was also held for the further development of the end product, including the completion of all concepts and the subsequent design phase.

A key challenge facing the nuclear fusion community is how to design a reactor that will operate in environmental conditions not easily reproducible in the laboratory for materials testing. Finite element analysis (FEA), commonly used to predict components’ performance, typically uses idealised geometries. An emerging technique shown to have improved accuracy is image based finite element modelling (IBFEM). This involves converting a three dimensional image (such as from X ray tomography) into an FEA mesh. A main advantage of IBFEM is that models include micro structural and non idealised manufacturing features. The aim of this work was to investigate the thermal performance of a CFC Cu divertor monoblock, a carbon fibre composite (CFC) tile joined through its centre to a CuCrZr pipe with a Cu interlayer. As a plasma facing component located where thermal flux in the reactor is at its highest, one of its primary functions is to extract heat by active cooling. Therefore, characterisation of its thermal performance is vital. Investigation of the thermal performance of CFC Cu joining methods by laser flash analysis and X ray tomography showed a strong correlation between micro structures at the material interface and a reduction in thermal conductivity. Therefore, this problem leant itself well to be investigated further by IBFEM. However, because these high resolution models require such large numbers of elements, commercial FEA software could not be used. This served as motivation to develop parallel software capable of performing the necessary transient thermal simulations. The resultant code was shown to scale well with increasing problem sizes and a simulation with 137 million elements was successfully completed using 4096 cores. In comparison with a low resolution IBFEM and traditional FEA simulations it was demonstrated to provide additional accuracy. IBFEM was used to simulate a divertor monoblock mock up, where it was found that a region of delamination existed on the CFC Cu interface. Predictions showed that if this was aligned unfavourably it would increase thermal gradients across the component thus reducing lifespan. As this was a feature introduced in manufacturing it would not have been accounted for without IBFEM.The technique developed in this work has broad engineering applications. It could be used similarly to accurately model components in conditions unfeasible to produce in the laboratory, to assist in research and development of component manufacturing or to verify commercial components against manufacturers’ claims.