The performance of hot mix asphalt, Portland cement concrete, unbound base, and subbase layers in a pavement are significantly affected by aggregate shape characteristics. Classification of coarse and fine aggregate shape properties such as shape (form), angularity, and texture, are important in predicting the performance of pavements. Consequently, there is a need to implement a system that can characterize aggregates without the limitations of the current aggregate classification standards. The Aggregate Image Measurement System (AIMS) was developed as a comprehensive and capable means of measuring aggregate shape properties. A new design of AIMS will be introduced with several modifications to improve the operational and physical components. The sensitivity, repeatability, and reproducibility are analyzed to evaluate the quality of AIMS measurements. The sensitivity of AIMS is evaluated and found to be good for several operational and aggregate parameters. Important operational and environmental factors that could affect the AIMS results are identified and appropriate limits are recommended. AIMS is able to control normal variations in the system without affecting the results. A comprehensive analysis is conducted to determine the repeatability and reproducibility of AIMS for multiple users and laboratories. Single-operator and multi-laboratory precision statements are developed for the test method in order to be implemented into test standards.

A new route to highly active hopcalite catalysts via flame spray pyrolysis of an inverse microemulsion precursor is reported. The nitrate derived nanoparticles are around 15 nm in diameter and show excellent conversion of CO under ambient conditions, outperforming commercial reference hopcalite materials produced by co-precipitation.

A new route to highly active hopcalite catalysts via flame spray pyrolysis of an inverse microemulsion precursor is reported. The nitrate derived nanoparticles are around 15 nm in diameter and show excellent conversion of CO under ambient conditions, outperforming commercial reference hopcalite materials produced by co-precipitation.

Dryout and Departure from Nucleate boiling (DNB) are utmost thermal-hydraulic concerns for the safety of LWRs. The behavior of two-phase flows at these conditions is still not fully understood. There is at least a need for a good local velocity and void fraction database at these conditions. This database can be exploited by CFD codes, thereby leading to understanding and predicting DNB and boiling crisis. Since these conditions occur in LWR at pressures greater than 70 bar and temperatures above 285 $^oC$, most instrumentations fail at these conditions. So there is a need for developing or optimizing new instruments for this specific objective. This study will look into the application of Hot Wire Anemometry (HWA) for this application. Previous experiments at near saturation conditions were studied, the hurdles of application of HWA in the HWAT loop at KTH were also investigated. Finally, the deposition of thin film on the HWA sensors for protection was studied. / Dryout och avvikelse från kärnkokning (DNB) är extrema termiska hydrauliska problem för säkerheten för LWR. Tvåfasflödets beteende under dessa förhållanden är fortfarande inte helt förstådd. Det finns ett behov av en god lokal hastighets- och tomrumsfraktionsdatabas under dessa förhållanden. Denna databas kan användas av CFD-koder, vilket leder till att förstå och förutsäga DNB och den kokande krisen. Eftersom dessa förhållanden förekommer i LWR vid tryck större än 70 bar och temperaturer över 285 oC, misslyckas de flesta instrument vid dessa förhållanden. Så det finns ett behov av att utveckla eller optimera nya instrument för detta specifika mål. Denna studie kommer att undersöka tillämpningen av Hot Wire Anemometry (HWA) för denna applikation. Tidigare experiment vid nästan mättnadsförhållanden dissekerades, hinder för tillämpningen av HWA i HWAT-slingan vid KTH undersöktes också. Slutligen undersöks avsättningen av tunn film på HWA-sensorerna för skydd.