Hydraulic losses in sewer pipes are caused by wall roughness, blockages and in-pipe sedimentation. Hydraulic resistance is a key parameter that is used to account for the hydraulic energy losses and predict the sewer system propensity to flood. Unfortunately, there are no objective methods to measure the hydraulic resistance in live sewers. A common method to estimate the hydraulic resistance of a sewer is to analyse collected CCTV images and then to compare them against a number of suggested hydraulic roughness values published in the Sewer Rehabilitation Manual. This thesis reports on the development of a novel, non-invasive acoustic method and instrumentation to measure the hydraulic roughness in partially filled pipes under various structural and operational conditions objectively. This research presents systematic laboratory and field studies of the hydraulic and surface water wave characteristics, of shallow water flows in a sewer pipes with the presence of local and distributed roughness, in order to relate them to some fundamental properties of the acoustic field measured in the vicinity of the flow surface. The results of this thesis indicate that for the local roughness the energy content of the reflected acoustic signal is an indicator of the pipe head loss and hydraulic roughness. In the case of the distributed roughness, the variation in the temporal and frequency characteristics of the propagated sound wave can be related empirically to the mean flow depth, mean velocity, wave standard deviation and hydraulic roughness.

The polymer laminated sheet metal (PLSM) is a layered material which involves a sheet metal substrate, a thin polymer film and an adhesive layer between the film and the substrate. The adhesion properties between the bonded materials are among the most important issues in PLSM forming operations. In this thesis, the main focus has been devoted to characterizing and improving the adhesion properties of the PLSM system for forming applications. Metallic surface roughness evolution and residual stress development in polymer adherends are two consequences of the plastic deformation of the PLSMs. In chapter 2, the effect of these factors on interfacial adhesion strength between metallic substrate and polymer adherend (polymer film with a thin uniform pressure-sensitive adhesive layer on one side) is investigated by devising a new experimental methodology. This methodology is based on two different protocols for preparation of peel sample, one involving pre-straining in uniaxial tension of the metallic substrate prior to lamination and the other involving post-lamination pre-straining of the PLSM. In chapter 3, the peel test results of two different types of PLSMs at different peel speeds are analyzed with two different approaches common in cohesive zone modeling in the literature, namely linear elastic stiffness approach and critical maximum stress approach. The modeling results revealed the significance of the peel speed in determining the interface strength between the adhesive and metallic substrate. In chapter 4, two mechanical treatment techniques of grinding and knurling are implemented to alter the metallic substrate surface roughness before lamination. Peel strength of these samples are investigated at different peel speeds and at different peel loading directions with respect to the grinding and knurling directions. / Thesis / Doctor of Philosophy (PhD) / The polymer laminated sheet metal (PLSM) is a layered material which involves a sheet metal substrate, a thin polymer film and an adhesive layer between the film and the substrate. In this thesis, the main focus has been devoted to characterizing and improving the adhesion properties of the PLSM system for forming applications. A new experimental methodology has been devised for analyzing the effects of deformation-induced surface roughness of metallic substrate and deformation-induced residual stress in polymer adherends on interfacial peel properties of PLSMs. A novel interpretation of the results obtained from rate-independent cohesive zone modeling of peel test has revealed the significance of peel speed in determining the interface strength between the adhesive and the metallic substrate. In another part of this thesis, the effects of two substrate surface alteration techniques, grinding and knurling, on peel properties of PLSMs have been studied.

<p dir="ltr">The Boeing/AFOSR Mach-6 Quiet Tunnel (BAM6QT) was used for a set of experiments studying the effect of isolated roughness elements on boundary-layer transition on a 7° half-angle cone. In quiet flow, the cone was tested at Reynolds numbers of 7.4 × 10e6 /m, 10.2 × 10e6 /m, and 13.0 × 10e6 /m. Tests were also completed at Re = 11.0 × 10e6 /m in noisy flow to examine the effects of freestream noise. The cone was set at both 0° and 6° angle of attack and an isolated, square trip oriented like a diamond with respect to the flow direction was attached before each set of runs. </p><p dir="ltr">Using infrared thermography and pressure transducers, the location of transition onset was estimated for each test. The results followed all expected trends: transition moved upstream as trip height increased, transition occurred earlier at higher freestream Reynolds numbers, and transition was significantly delayed in quiet flow compared to noisy flow. Mean flow solutions were generated to calculate correlation values commonly used to predict transition. Theexperimentaldatawasthenusedinconjunctionwiththesecorrelationvalues to identify a range of critical values that could be used to predict transition behavior. </p><p dir="ltr">Additionally, a z-type schlieren setup was developed for the BAM6QT. Various components were upgraded and standard procedures for aligning the system were developed. A new pulsed laser and high-speed camera were integrated into the system to enable schlieren imaging at up to 1.75M fps. The final configuration allows the schlieren system to be used for various applications with minimal adjustments, and has been utilized in many research projects in the BAM6QT.</p>

In the field of vehicle durability, many individuals are focusing on methods for better replicating the durability a user will experience throughout the typical design lifespan of a vehicle (e.g., 100,000 miles). To estimate user durability a means of understand the types of damaging events and driving styles of uses must be understood. The difficulty with accurately estimating customer usage is, firstly, there is a large pool of possible roads for a user to drive along, for example, there are over 4 million miles of public roads in the United States, alone [1]. In addition, while measurements of these surfaces could be collected it would be impractical for two reasons, the first is the financial and extreme time burden this would take. Second, when collecting measurements of a road surface only the current state of a road surface can be measured, thus as a road deteriorates or is repaved the measurements collected would no longer be an accurate representation of the road. It should be mentioned that even, if all of the road surfaces were measured performing simulation and analysis of all of these road surfaces would be computationally intensive. Instead, it would be beneficial if select events that account for a significant portion of the damage a vehicle experiences can be identified. These damaging events could then be used in more complex vehicle simulation models and as input and validation of proving ground and laboratory durability testing. The objective of this research is to provide a means for improved estimation of vehicle durability, specifically a means for identifying, characterizing, and grouping unique separable damaging events from a road profile measurement. In order to achieve this objective a measure that can be used to identify separate damaging events from a road profile is developed. This measure is defined as Localized Pseudo Damage (LPD), which identifies the amount of damage each individual road excitation makes to the total accumulated damage for a single load path in a vehicle system. LPD is defined as a damage density to minimize the effect of measurement spacing on the resulting metric. The developed LPD measure is causal in that the value of LPD at a location is not affected by any future locations. In addition, for a singular event (e.g., impulse or step) in the absences of other excitations, the LPD value at the singular event location is equivalent to the total pseudo damage divided by the step size at the location. Once a measure of pseudo damage density is known at multiple locations along a road profile for multiple load paths of interest, then separable damaging events can be identified. To identify separable damaging events the activity of the vehicle system must be considered because separate damaging events can only occur when a region of inactivity is present across all load paths. Subsequently, an optimization problem is formed to determine the optimal active regions to maintain. The cost function associated with the optimization problem is defined to minimize the cost (number of locations maintained in damaging events) and maximize the benefit (the amount of pseudo damage maintained). Lastly, a statistical test is developed to assess if separate damaging events can be considered to be from the same general class of events based on their damage characteristics. The developed assessment methods establish the similarity between two more separable damaging events based on application specific user defined inputs. In the development, two example similarity metrics are defined. The first similarity metric is in terms of distance and the second is in terms of likelihood (probability). The developed statistical analysis uses the current state-of-the-art in clustering algorithms to allow for multiple damaging events to be identified and grouped together. / Doctor of Philosophy / In the automotive field determining the level of damage a typical production vehicle experiences over its lifetime has always been a desirable criterion to identify. This criterion is commonly referred to as customer usage. By understanding the typical customer usage of a vehicle over the lifetime of a vehicle, automotive engineers are able to improve the design of vehicle components. The issue with defining customer usage is that there are millions of miles of roads that a customer can travel on and millions of customers that all have unique driving characteristics. While it is possible to collect measurements of these road surfaces to use in further vehicle simulations, it is not feasible both from a financial and time perspective. In addition, the simulation and analysis of all road surfaces would be computationally intensive. However, if select damaging events (regions of the road surface that excessively contribute to accumulated damage) are identified, then they can be used in more complex vehicle durability analyses with lower computational efforts. In conventional damage analysis a total amount of accumulated damage is established for a known road surface. The issue with defining damage this way is that unique events which likely contributed a large amount of the accumulated damage cannot be identified. The first objective of this research is to define damage as a function of the vehicle's location along a road surface. Then, unique and separable damaging events can be identified and separated from sections of the road that do not significantly contribute to the accumulated damage. After defining this measure, an optimization problem is developed to identify damaging events based on maximizing the benefit (amount of damage accounted for in damaging events) and minimizing the cost (amount of road surface retained). Unique and separable damaging events are identified by solving this optimization problem. While the optimization problem identifies unique, separable damaging events, it is likely that some damaging events contain similar characteristics to each other. When performing additional durability analysis, it would be beneficial to form connections between similar damaging events to allow for analysis to be performed based on groups of events. To identify damaging events with similar characteristics, a statistical analysis is developed as the last contribution of this work. By combining this analysis with current state-of-the-art clustering algorithms and user provided definitions based on applications, similar damaging events are able to be grouped together.

Cardiovascular disease is the leading cause of death globally and is responsible for taking 17.9 million lives per year. Despite the use of clinical treatments and detection methods, there remains a large population of individuals that suffer from CVD whose symptoms are left undetected and untreated prior to a life-threatening cardiac event. This highlights a need for an early detection method that can prevent the manifestation and worsening of the disease as well as address limitations of current early detection methods. An area of interest for early detection of CVD is subclinical atherosclerosis, which is the long, early, asymptomatic stage of plaque formation. Subclinical atherosclerosis has been namely associated with endothelial dysfunction and is the result of the pathological state of the endothelium due to its impact on vascular homeostasis, thrombosis, and vascular tone. Endothelial dysfunction is a result of several factors contributing to and promoting inflammation and results in changes in biological pathways that can alter the surface of the endothelium. This surface modification or added roughness changes the flow profile from laminar to turbulent flow due to the decreased shear stress on the vascular wall. Current detection methods such as carotid intima media thickness (CIMT) and flow-mediated dilation (FMD) targeted at identifying the early stages of atherosclerosis present limitations such as identifying late-stage effects of plaque formation and subjective readings highlight the need for a different approach to early detection. This experimental study aims to present a possible method of detecting the morphological changes of the endothelium due to inflammation through acoustic analysis of flow. Three silicone artery phantom groups were created with different degrees of inner diameter surface roughness to explore the relationship between relative roughness and sound associated with fluid flow. The results of this study are power spectral density graphs (PSD) which show frequency peaks associated with each of the phantoms at a theoretical laminar and turbulent Reynolds number. The PSD graphs show that there is a difference in frequency response between a smooth and rough artery phantom at the same flow rate providing preliminary support that sound analysis of fluid flow could provide information regarding early-stage cardiovascular disease.

Time of Flight - Elastic recoil detection analysis (ToF-ERDA) is a method used to analyse the composition of wall samples from fusion devices. All current analysing software for ToF-ERDA assumes that the target is perfectly flat which could create inaccuracies when rough surfaces are analysed. The aim of this project was to get a better understanding of how the roughness of samples from fusion devices affect the results from ToF-ERDA. To investigate this, three existing simulation softwares SIMNRA, TRIM and Potku were used. Programs were developed in order to use these to simulate three different targets with varying roughness, which were modelled as a combination of surfaces of different thicknesses. The results from which were put back into Potku where the differences between the targets could be noted. The study shows that it was possible to apply roughness to the already existing programs and showed similarities between the resulting depth profiles. When applying roughness, the concentration of surface elements decreased at the top of the layer but also went further into the sample. / Time of Flight - Elastic recoil detection analysis (ToF-ERDA) är en metod som används för att analysera kompositionen av prover av väggmaterial från fusionsreaktorer. Alla mjukvaror som används för att analysera datan från ToF-ERDA idag antar att provets yta är helt platt vilket skulle kunna innebära att felaktiga resultat erhålls när så ej är fallet. Målet med där här projektet var att undersöka och skapa en bättre förståelse för hur skrovligheten hos material från fusionsanordningar påverkar resultaten från ToF-ERDA. För att undersöka detta användes tre simulationsmjukvaror, SIMNRA, TRIM och Potku. Program skrevs för att använda dessa för att simulera tre olika material med olika stor skrovlighet, vilka modellerades som en kombination av material med olika tjockt ytskikt. Resultaten från dessa analyserades därefter i Potku där skillnaderna mellan materialen kunde noteras. Studien visar att det är möjligt att implementera ojämnhet i den simulationsprogram som finns idag och flera likheter mellan de resulterande djupprofilerna från de olika simulationsmetoderna uppmärksammades. När högre skrovlighet användes minskade koncentrationerna av ytelementen vid materialets topp men djupet som de når i materialet ökade. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

Industries (food, beverage, petrochemical, etc.) normally use various gravitational separation echniques in their processes. Such separation processes often suffer from the deposition of undesirable material on the active surfaces of the process equipment, e.g. a high-speed separator or decanter, causing a slew of problems with the process or product quality. To restore operational efficiencies, additional cleaning steps using both water and chemicals are required, making the process more expensive and less environmentally friendly. Other than operating time and concentration of the process fluid there are several factors such as surface nature, surface roughness, type of material, surface charge, etc which influence the fouling deposition of surfaces. Fouling on the surfaces can grow following different mechanisms. The goal of this research work is to learn more about the nature of foulant interactions with stainless steel surfaces and eventually design some antifouling methodology. It is too difficult to study foulingfor all kinds of solutions and industries, so we tried to investigate the organic deposition in dairy and brewery industries by using lab-scale synthesized milk and beer solutions, For quantitative and statistical examination of these characteristics, several experimental approaches (FTIR, percent weight change, surface roughness, surface energy) were used. It was confirmed that fouling grows on the surfaces in a non-linear fashion irrespective of the time and concentration of the solution. The fouling of surfaces can be improved by producing more hydrophilic surfaces or by reducing surface roughness. Steric hindrance, electrostatic charge, and water barrier or hydration layer theories can be used to modify the surface nature and hence the fouling deposition. For antifouling purposes, PMMA (organic) and tungsten oxide (inorganic) coatings were employed. The PMMA was deposited using a dip-coating technique using (6%,10%, and 12%) PMMA solution, and the tungsten oxide coating was carried out by using a standard two electrode electrochemical system under different voltage (3.5V and 4.5V) and time (5min, 10 min, and 20 min) conditions. The coatings were characterized by using different techniques and their antifouling effects were studied in model milk and model beer solutions / Vid industriella processer (livsmedel, petrokemisk etc.) används ofta olika tekniker för separation med hjälp av gravitation. Sådana separationsprocesser drabbas ofta av oönskade beläggningar och påväxt på processutrustningens aktiva ytor så som t.ex. i en separator eller en dekanter, vilket orsakar problem med processen eller produktkvaliteten. För att återställa driftseffektivitet krävs särskilda rengöringssteg med både vatten och kemikalier vilket gör processen dyrare och mindre miljövänlig. Förutom drifttid och processvätskans sammansättning finns det flera faktorer såsom ytbeskaffenhet, ytjämnhet, materialtyp, ytladdning m.m. som påverkar mängden oönskade beläggningar på ytor. Föroreningarna på ytor kan tillväxa med olika mekanismer. Målet med detta forskningsarbete är att studera interaktionen mellan olika former av påväxt och ytan på rostfritt stål och senare utforma metoder för att förhindra bildandet av sådana oönskade beläggningar. Det är en stor utmaning att studera olika typer av påväxt för alla typer av flöden och industrier. I studien undersöktes organisk påväxt inom mejeri- och bryggeriindustrin genom att använda syntetiserade mjölk- och ölprodukter i laboratorieskala, för kvantitativa och statistiska undersökningar av dessa egenskaper. Flera olika experimentella metoder användes (FTIR, viktförändring, ytjämnhet, ytenergi). Det bekräftades att tillväxten på ytorna var olinjärt oavsett tid och lösningens koncentration. Bildandet och tillväxt av oönskade beläggningar kan minskas med hjälp av mera hydrofila ytor eller genom att minska ytans ojämnhet. Steriska hinder, elektrostatisk laddning och vattenbarriär eller hydratiseringsskal kan användas för att modifiera ytan och därmed fördröja bildandet av oönskade beläggningar. För att förhindra påväxt belades ytan med PMMA (organisk) och volframoxid (oorganisk). PMMA deponerades genom en doppbeläggningsteknik med användning av (6%, 10% och 12%) PMMA-lösning och volframoxidbeläggningen utfördes med ett elektrokemiskt tvåelektrodssystem med olika spänningar (3,5V och 4,5V) och tider (5min, 10min och 20min). Ytbeläggningarna karakteriserades genom att använda olika tekniker och deras förmåga att förhindra snabb påväxt studerades i modellösningar av mjölk och öl.

The method for developing a soil moisture inversion algorithm using Radar data can be approached in two ways: the multiple-incident angle approach and the change detection method. This thesis discusses how these two methods can be used to predict surface soil moisture. In the multiple incident angle approach, surface roughness can be mapped, if multiple incident angle viewing is possible and if the surface roughness is assumed constant during data acquisitions. A backpropagation neural network (NN) is trained with the data set generated by the Integral Equation Method (IEM) model. The training data set includes possible combinations of backscatter obtained as a result of variation in dielectric constant within the period of data acquisitions. The inputs to the network are backscatter acquired at different incident angles. The outputs are correlation length and root mean square height (rms). Once the roughness is mapped using these outputs, dielectric constant can be determined. Three different data sets, (backscatter acquired from multiplerequencies, multiple-polarizations, and multiple-incident angles) are used to train the NN. The performance of the NN trained by the different data sets is compared. The next approach is the application of the change detection concept. In this approach, the relative change in dielectric constant over two different periods is determined from Radarsat data using a simplified algorithm. The vegetation backscatter contribution can be removed with the aid of multi-spectral data provided by Landsat. A method is proposed that minimizes the effect of incident angle on Radar backscatter by normalizing the acquired SAR images to a reference angle. A quantitative comparison of some of the existing soil moisture estimation algorithms is also made

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