Uncontrolled open dumping and burning of municipal solid waste (MSW) has resulted in soil, water, and air pollution in many urban cities in India. Landfills are the most common cost-effective solution for MSW management in many developing countries like India. However, the identification of suitable landfill sites always remains a challenging task as it involves the selection of several environmental criteria set by the local authorities. The objective of this study is to identify the most potential landfill sites proposed by the Government in Bengaluru Metropolitan Region, Karnataka state, India using Geographic Information System enabled Analytical Hierarchy Process based multi-criteria evaluation technique. Several criteria and constraints as recommended by the local authorities along with the proximity to the solid waste processing plants are used to identify the potential landfill sites in the study region. The study identified three highly suitable sites (Neraluru, Gudhatti, Madivala) for landfills which are not only environmentally sustainable but also economically attractive as they are closer to the solid waste processing plants minimizing the transportation cost involved in the disposal of solid waste from the source to the final disposal sites in the study region.

The photovoltaic (PV) panel can produce electrical energy that is very environmentally friendly and easy to use. The use of PV panels is suitable for supplying peak loads or at night using batteries as energy storage. However, the battery needs to manage for control, and the battery can last long. The solution to battery management problems is through research about the battery charging system. The DC-DC converter used is the Single Ended Primary Inductance Converter (SEPIC) type. Voltage Control of the battery charging using Adaptive Neuro-Fuzzy Inference System (ANFIS). In the simulation of bright conditions, ANFIS controls can track the charging point set point and obtain a voltage response with a rise time of 0.0028 s, a maximum overshoot of 0.027 %, a peak time of 0.008 s, and a settling time of 0.0193 s. When charging a solar tracker, PV battery gets a 0.25 % increase compared to a fixed PV panel. PV solar tracker can follow the direction of the sun's position. The irradiation value and maximum temperature affect the input voltage and input current that enters the converter. © The Authors, published by EDP Sciences, 2020.

World energy consumption increases with time, so that occur an energy imbalance. Many breakthroughs have developed to utilize renewable energy. The photovoltaic system is one of the easy-to-use renewable energies. The power conversion from PV fixed is still low, so the PV system is designed using the active dual-axis solar tracker. The PV tracker position can be adjusted to change the sun position to get maximum efficiency. The active dual-axis solar tracker system is integrated with the maximum power point tracking (MPPT) algorithm to keep PV operating at a maximum power point even though input variations change. The active dual-axis solar tracker system integrated with the maximum power point tracking (MPPT) algorithm to keep PV operating at a maximum power point even though input variations change. Tracking test simulation had done by comparing the output power of a fixed PV system with the active dual-axis solar tracker. Type-2 fuzzy logic based MPPT successfully increased the average output power by 10.48 % with the highest increase of 17.48 % obtained at 15:00 West Indonesia Time (GMT+7). The difference in power from a fixed PV system with the active dual-axis solar tracker of 36.08 W is from the output power worth 206.3 to 242.4 W. © The Authors, published by EDP Sciences, 2020.

The Unified Modeling Language (UML) is widely used as a high level object oriented specification language. In this paper we present a novel approach in which reverse engineering is performed using UML as the modelling language used to achieve a representation of the implemented system. The target is the core logic of a complex critical railway control system, which was written in an application specific legacy language. UML perfectly suited to represent the nature of the core logic, made up by concurrent and interacting processes, using a bottom-up approach and proper modeling rules. Each process, in fact, was strictly related to the management of a physically (resp. logically) well distinguished railway device (resp. functionality). The obtained model deeply facilitated the static analysis of the logic code, allowing for at a glance verification of correctness and compliance with higher-level specifications, and opened the way to refactoring and other formal analyses. © 2006 IEEE.

Within any ecosystem, information sharing is essential. In this paper, the Swedish gravel road ecosystem is studied, where information plays a crucial role for the effective management of operations and maintenance. However, efficient information sharing is not enabled due to the lack of appropriate information systems. For addressing this issue, this paper intends to elicit information needs of gravel road stakeholders to support the design of a cloud-based information system. The main purpose is to explore the information needs of stakeholders within the Swedish gravel road ecosystem. Data were collected through in-depth semi-structured interviews with 11 participants representing key stakeholders in the ecosystem. Template analysis was used for analyzing the interview results. The major findings were a set of information needs covering road identification and condition, weather conditions, accessibility and traffic, maintenance policy, and sensor data. The results form a comprehensive information model for the further development of a cloud-based gravel road management system that would contribute to increased traffic safety and comfort, lower maintenance and management costs, and better decision-making abilities.

Facial recognition technology has become a ubiquitous tool in security and personal identification. However, the rise of this technology has been accompanied by concerns over inherent biases, particularly regarding ethnic and gender. This thesis examines the extent of these biases by focusing on the influence of dataset imbalances in facial recognition algorithms. We employ a structured methodological approach that integrates AI-generated images to enhance dataset diversity, with the intent to balance representation across ethnics and genders. Using the ResNet and Vgg model, we conducted a series of controlled experiments that compare the performance impacts of balanced versus imbalanced datasets. Our analysis includes the use of confusion matrices and accuracy, precision, recall and F1-score metrics to critically assess the model’s performance. The results demonstrate how tailored augmentation of training datasets can mitigate bias, leading to more equitable outcomes in facial recognition technology. We present our findings with the aim of contributing to the ongoing dialogue regarding AI fairness and propose a framework for future research in the field.

Asynchronous machines are considered nowadays the most commonly used electrical machines, which are mainly used as electrical induction motors. Starting the induction motor is the most important and dangerous step. The theory behind this project is based on representing the real motor by a set of equations and values in Matlab using the subsystem feature, forming a corresponding idealistic motor in a way where all the physical effects are similar. The motor is started under different loads in two methods: Direct and Soft starting. Each method is studied and discussed using supporting simulation of currents, torque, speed, efficiency and power factor curves.

This study presentes a new nonparametric structural damage detection algorithm that integrates self-organizing maps with a pattern-recognition neural network to quantify and locate structural damage. In this algorithm, self-organizing maps are used to extract a number of damage indices from the ambient vibration response of the monitored structure. The presented study is unique because it demonstrates the development of a nonparametric vibration-based damage detection algorithm that utilizes self-organizing maps to extract meaningful damage indices from ambient vibration signals in the time domain. The ability of the algorithm to identify damage was demonstrated analytically using a finite-element model of a hot-rolled steel grid structure. The algorithm successfully located the structural damage under several damage cases, including damage resulting from local stiffness loss in members and damage resulting from changes in boundary conditions. A sensitivity study was also conducted to evaluate the effects of noise on the computed damage indices. The algorithm was proved to be successful even when the signals are noise-contaminated.

One of the main tasks in structural health monitoring process is to create reliable algorithms that are capable of translating the measured response into meaningful information reflecting the actual condition of the monitored structure. The authors have recently introduced a novel unsupervised vibration-based damage detection algorithm that utilizes self-organizing maps to quantify structural damage and assess the overall condition of structures. Previously, this algorithm had been tested using the experimental data of Phase II Experimental Benchmark Problem of Structural Health Monitoring, introduced by the IASC (International Association for Structural Control) and ASCE (American Society of Civil Engineers). In this paper, the ability of this algorithm to quantify structural damage is tested analytically using an experimentally validated finite element model of a laboratory structure constructed at Qatar University.

The study presented in this paper introduces a new intelligent methodology to mitigate the vibration response of flexible cantilever plates. The use of the piezoelectric sensor/actuator pairs for active control of plates is discussed. An intelligent neural network based controller is designed to control the optimal voltage applied on the piezoelectric patches. The control technique utilizes a neurocontroller along with a Kalman Filter to compute the appropriate actuator command. The neurocontroller is trained based on an algorithm that incorporates a set of emulator neural networks which are also trained to predict the future response of the cantilever plate. Then, the neurocontroller is evaluated by comparing the uncontrolled and controlled responses under several types of dynamic excitations. It is observed that the neurocontroller reduced the vibration response of the flexible cantilever plate significantly; the results demonstrated the success and robustness of the neurocontroller independent of the type and distribution of the excitation force.

Metamaterial inspired structures, or metastructures, are structural members that incorporate periodic or non-periodic inserts. Recently, a new class of metastructures has been introduced which feature chiral lattice inserts. It was found that this type of inserts has frequency bandgaps which can be tuned by altering the geometry of the chiral lattice. Previous studies have shown that inserting non-periodic chiral lattices inside a beam-like structure results in efficient vibration attenuation at low frequencies. In the study presented in this paper, a genetic algorithm based optimization technique is developed to automatically generate chiral lattices which are tuned to suppress vibration in a flexible beam-like structure. Several parameters are incorporated in the optimization process such as the radius of circular nodes and characteristic angle as well as the spacing and distribution of circular inserts. The efficiency of the …

One of the major challenges in civil, mechanical, and aerospace engineering is to develop vibration suppression systems with high efficiency and low cost. Recent studies have shown that high damping performance at broadband frequencies can be achieved by incorporating periodic inserts with tunable dynamic properties as internal resonators in structural systems. Structures featuring these kinds of inserts are referred to as metamaterials inspired structures or metastructures. Chiral lattice inserts exhibit unique characteristics such as frequency bandgaps which can be tuned by varying the parameters that define the lattice topology. Recent analytical and experimental investigations have shown that broadband vibration attenuation can be achieved by including chiral lattices as internal resonators in beam-like structures. However, these studies have suggested that the performance of chiral lattice inserts can be maximized by utilizing an efficient optimization technique to obtain the optimal topology of the inserted lattice. In this study, an automated optimization procedure based on a genetic algorithm is applied to obtain the optimal set of parameters that will result in chiral lattice inserts tuned properly to reduce the global vibration levels of a finite-sized beam. Genetic algorithms are considered in this study due to their capability of dealing with complex and insufficiently understood optimization problems. In the optimization process, the basic parameters that govern the geometry of periodic chiral lattices including the number of circular nodes, the thickness of the ligaments, and the characteristic angle are considered. Additionally, a new set of parameters is introduced to enable the optimization process to explore non-periodic chiral designs. Numerical simulations are carried out to demonstrate the efficiency of the optimization process.

Structural damage detection has been an interdisciplinary area of interest for various engineering fields. While the available damage detection methods have been in the process of adapting machine learning concepts, most machine learning based methods extract “hand-crafted” features which are fixed and manually selected in advance. Their performance varies significantly among various patterns of data depending on the particular structure under analysis. Convolutional neural networks (CNNs), on the other hand, can fuse and simultaneously optimize two major sets of an assessment task (feature extraction and classification) into a single learning block during the training phase. This ability not only provides an improved classification performance but also yields a superior computational efficiency. 1D CNNs have recently achieved state-of-the-art performance in vibration-based structural damage detection; however, it has been reported that the training of the CNNs requires significant amount of measurements especially in large structures. In order to overcome this limitation, this paper presents an enhanced CNN-based approach that requires only two measurement sets regardless of the size of the structure. This approach is verified using the experimental data of the Phase II benchmark problem of structural health monitoring which had been introduced by IASC-ASCE Structural Health Monitoring Task Group. As a result, it is shown that the enhanced CNN-based approach successfully estimated the actual amount of damage for the nine damage scenarios of the benchmark study.

Structural health monitoring (SHM) and vibration-based structural damage detection have been a continuous interest for civil, mechanical and aerospace engineers over the decades. Early and meticulous damage detection has always been one of the principal objectives of SHM applications. The performance of a classical damage detection system predominantly depends on the choice of the features and the classifier. While the fixed and hand-crafted features may either be a sub-optimal choice for a particular structure or fail to achieve the same level of performance on another structure, they usually require a large computation power which may hinder their usage for real-time structural damage detection. This paper presents a novel, fast and accurate structural damage detection system using 1D Convolutional Neural Networks (CNNs) that has an inherent adaptive design to fuse both feature extraction and classification blocks into a single and compact learning body. The proposed method performs vibration-based damage detection and localization of the damage in real-time. The advantage of this approach is its ability to extract optimal damage-sensitive features automatically from the raw acceleration signals. Large-scale experiments conducted on a grandstand simulator revealed an outstanding performance and verified the computational efficiency of the proposed real-time damage detection method.

Vibration suppression remains a crucial issue in the design of structures and machines. Recent studies have shown that with the use of metamaterial inspired structures (or metastructures), considerable vibration attenuation can be achieved. Optimization of the internal geometry of metastructures maximizes the suppression performance. Zigzag inserts have been reported to be efficient for vibration attenuation. It has also been reported that the geometric parameters of the inserts affect the vibration suppression performance in a complex manner. In an attempt to find out the most efficient parameters, an optimization study has been conducted on the linear zigzag inserts and is presented here. The research reported in this paper aims at developing an automated method for determining the geometry of zigzag inserts through optimization. This genetic algorithm based optimization process searches for optimal zigzag designs which are properly tuned to suppress vibrations when inserted in a specific host structure (cantilever beam). The inserts adopted in this study consist of a cantilever zigzag structure with a mass attached to its unsupported tip. Numerical simulations are carried out to demonstrate the efficiency of the proposed zigzag optimization approach.

Operational modal analysis, OMA, results in unscaled mode shapes, since no forces are measured. Yet, obtaining a scaled modal model, i.e. knowing the modal mass of each mode (assuming proportional damping), is essential in many cases for structural health monitoring and load estimation. Several methods have therefore recently been developed for this purpose. The so-called OMAH method is a recently developed method for scaling OMA models, based on harmonic excitation of the structure. A number of frequencies are excited, one by one, and for each frequency, one or more frequency response values are calculated, that are then used for estimation of the modal masses of each mode, and residual effects of modes outside the frequency of interest. In the present paper, measurements were made on a four-story office building which was excited with a small, 200 N sine peak electrodynamic shaker. It is demonstrated that this small shaker was sufficient to excite the building with a force level of approx.. 1.8 N RMS close to the first eigenfrequency of the building, which was sufficient to produce harmonic response across the building. Reliable modal masses were possible to obtain within an accuracy of 6%. This demonstrates the feasibility of the OMAH method.

Walking-induced loads on office floors can generate unwanted vibrations. The current multi-person loading models are limited since they do not take into account nondeterministic factors such as pacing rates, walking paths, obstacles in walking paths, busyness of floors, stride lengths, and interactions among the occupants. This study proposes a novel video-vibration monitoring system to investigate the complex human walking patterns on floors. The system is capable of capturing occupant movements on the floor with cameras, and extracting walking trajectories using image processing techniques. To demonstrate its capabilities, the system was installed on a real office floor and resulting trajectories were statistically analyzed to identify the actual walking patterns, paths, pacing rates, and busyness of the floor with respect to time. The correlation between the vibration levels measured by the wireless sensors and the trajectories extracted from the video recordings were also investigated. The results showed that the proposed video-vibration monitoring system has strong potential to be used in training data-driven crowd models, which can be used in future studies to generate realistic multi-person loading scenarios.

This paper presents a fast, accurate, and simple systematic approach for online condition monitoring and severity identification of ball bearings. This approach utilizes compact one-dimensional (1-D) convolutional neural networks (CNNs) to identify, quantify, and localize bearing damage. The proposed approach is verified experimentally under several single and multiple damage scenarios. The experimental results demonstrated that the proposed approach can achieve a high level of accuracy for damage detection, localization, and quantification. Besides its real-time processing ability and superior robustness against the high-level noise presence, the compact and minimally trained 1-D CNNs in the core of the proposed approach can handle new damage scenarios with utmost accuracy.

Internationally, an annual number of more than a million fatalities are caused by road traffic crashes, with particularly signalized intersections being crash prone locations within the highway system. An accumulation of conflicts between drivers is caused by the  different  movements  (through  and  turning)  from  different  directions  at  the  intersection;  hence,  studying  the  trajectories  of  turning vehicles is an important step towards improving traffic safety performance of these facilities. In view of that, the current paper aims at providing further insight into the behaviour of left-turning vehicles (right-hand traffic rule) at signalized intersections in the State of Qatar. At first, a total of 44 trajectories of free-flowing vehicles were manually extracted from a recorded video for a  single  approach  of  Lekhwair  signalized  intersection  in  Doha  City,  State  of  Qatar.  After  that,  the  extracted  trajectories  were statistically analysed in an attempt to explore the factors affecting the path of left-turning vehicles at signalized intersections. The results suggest that the characteristics of the extracted paths are significantly related to the vehicle’s entry speed, minimum speed throughout its turning manoeuvre, and the lateral distance between the exit point and the curb (i.e., targeted exit lane). Provided that the speed parameters can be fairly an indication to the driving behaviour, it can be concluded that the driver’s attitude plays an important role in drawing the manoeuvre of a turning vehicle as does the pre-selection of the exit lane. Finally, the effort presented in this paper can be regarded as a way forward towards understanding the behaviour of turning vehicles at signalised intersection in the State of Qatar.

This paper aims at developing a convolutional neural network (CNN)-based tool that can automatically detect the left-turning vehicles (right-hand traffic rule) at signalized intersections and extract their trajectories from a recorded video. The proposed tool uses a region-based CNN trained over a limited number of video frames to detect moving vehicles. Kalman filters are then used to track the detected vehicles and extract their trajectories. The proposed tool achieved an acceptable accuracy level when verified against the manually extracted trajectories, with an average error of 16.5 cm. Furthermore, the trajectories extracted using the proposed vehicle tracking method were used to demonstrate the applicability of the minimum-jerk principle to reproduce variations in the vehicles’ paths. The effort presented in this paper can be regarded as a way forward toward maximizing the potential use of deep learning in traffic safety applications.

Studies with large physical models are a vital link between the theoretical work and field applications provided that these models are designed to represent real structures where various types and levels of uncertainties can be incorporated. While comprehensive analytical and laboratory joint studies are ongoing at Qatar University, University of Central Florida and University of Alberta, this paper presents the initial findings of dynamic testing at Qatar University. A laboratory stadium structure (grandstand simulator) has been constructed at Qatar University. Capable of housing thirty spectators, Qatar University grandstand simulator is arguably the largest laboratory stadium in the world. The structure is designed in a way that several different structural configurations can be tested in laboratory conditions to enable researchers to test newly developed damage detection algorithms. The study presented in this paper covers the finite element modeling and modal testing of the test structure.

Many industrial companies place high demands on product development, from a simple idea to a finished product and then bring it to market. Therefore, there has been a rapid development of methods, models and working methodes in product development. This development is mostley about the product having a balance between price, quality, customer adaptation, safety, production and less environmental impact. 

Många webbgränssnitt idag misslyckas med att möta användarnas behov och blir därför bristfälliga gällande användarvänligheten. Detta leder till att användarna begår stora misstag och anstränger sig vid användningen av webbaserade system. Visuell design och struktur i ett gränssnitt spelar en stor roll i hur användarna förstår sig på och tolkar ett gränssnitt då de avser hur olika beteenden och information kommuniceras till användarna. I denna studie undersöks hur visuell design, struktur och användbarhet i ett gränssnitt underlättar användarnas kognitiva bearbetning av information vid utförande av komplexa uppgifter. Studien har utförts genom ett uppdrag för Ahltorpmedia AB, som skapar lösningar för bl.a. webbplatser, webbaserade system och e-handel. Uppdraget har varit att förbättra en av deras egen utvecklade tjänst Nuhet som är bristfällig gällande områdena ovan.

Först har en heuristisk utvärdering av Nuhets befintliga gränssnitt samt sju intervjuer med tjänstens befintliga- och potentiella användare inom huvudområdena visuell design, struktur och kognitiv bearbetning av information gjorts. Resultaten från intervjuerna och utvärderingen har använts för att bilda en persona varefter fokusområden för prototyparbetet har skapats. Sedan har en prototyp på Nuhets nya utseende och en ny funktionalitet skapats. Designprinciper för användbarhet samt gestaltlagar har nyttjats i skapandet av Nuhets nya gränssnitt.

Utifrån de metoder som har genomförts i detta examensarbete har det framkommit att det beror på flera faktorer gällande hur användarnas kognitiva bearbetning av information underlättas med hjälp av visuell design, struktur och användarvänlighet. Dessa är då en bra struktur, gruppering och organisering av innehåll i ett gränssnitt. Dessutom är det tydliga kontraster, bra färgval och standardisering som underlättar den. 

Den 2 juli 2014 blev det enligt lag tillåtet för en- och tvåbostadshusägare att uppföra en bygglovsbefriad komplementbyggnad på max 25 kvadratmeter på den egna fastigheten. Rapporten undersöker vilket genomslag lagändringen har haft i Stor-Stockholm, Stor-Göteborg och Stor-Malmö. Undersökningen visar att lagändringen ännu inte har haft något stort genomslag. I rapporten undersöks även en utvald del av marknadsaktörers utbud av attefallshus avsett som komplementbostadshus. 

Ett attefallshus utformas med miljövänligt hållbara material och inspireras av Vitruvius tre principer för god arkitektur. Huset konstrueras med avsikt att uppfylla kraven som ställs i PBL, PBF, BBR och EKS. Målet med de framtagna bygghandlingarna är att få startbesked från byggnadsnämnden i Växjö. 

In the construction sector today, there is a lot of discussion about material reuse tominimize the negative environmental impact. By reuse of precast concreteelements, significant amounts of CO2 emissions can be prevented. In order toreuse a concrete element for structural purposes in a building, the element need tobe assessed to ensure it can withstand the required loads.

This report is based on a comparison of different building codes, it describes andcompares three selected building codes and their associated concrete standardsfrom different eras. The purpose of the report is to compare the results obtainedwhen designing predetermined concrete elements and components. The findingswill indicate whether it is possible to reuse concrete elements that were designedaccording to previous standards. The calculations will demonstrate bothsimilarities and, more importantly, differences in the design approaches of thebuilding codes and how they have evolved.

An investigation concludes that by employing a chain of checks, it is possible todetermine if an existing component is reusable considering its load capacity.

The differences in reinforcement content vary within approximately 0-25% infavor of the previous code, i.e. the older code requires more reinforcement.

Underhåll har utvecklats under århundraden och har spelat en betydande roll för organisationers tillväxt.Underhållshistoriken särskiljs av tre generationer, utvecklingen av underhåll anses från att vara "nödvändigtont" till "vinstbidragsgivare". Mycket litteratur har diskuterat underhåll för optimering och ökad lönsamhet,men lite om de faktorer som påverkar underhållets framtid. Underhåll bör ses som en "konkurrensfaktor" iframtiden. Många trender har utvecklats inom produktionen och varje trend har haft ett stort bidrag tillproduktionsutvecklingen. Att framgångsrikt implementera trenderna anses vara en stor utmaning. Litelitteratur har pratat om de framväxande trenderna och utmaningarna inom produktionen.Avhandlingen går igenom den historiska utvecklingen av underhåll över generationer och presenterarnyckelfaktorer som spelar en stor roll under den fjärde generationen, och identifierar också de framväxandetrenderna och utmaningarna som produktionen står inför. Litteraturgenomgången, intervjuerna ochundersökningarna har använts i denna avhandling.Akademiska forskare och industriexperter från både underhålls- och produktionsavdelningen besvaradeintervju- och enkätfrågorna för denna forskning. Nyckelfaktorerna för förslaget om fjärde generationensunderhåll och de framväxande trenderna och utmaningarna som produktionen står inför presenteras.Resultaten från forskningsfrågorna och de empiriska resultaten sammanfattas i ett ramverk som gör detmöjligt för läsarna att känna till den historiska utvecklingen av underhåll, nyckelfaktorerna som ska beaktasför den fjärde generationens underhåll och de framväxande trenderna och utmaningarna som produktionenstår inför i framtiden. Dessutom diskuterar avhandlingen också informationsteknologins inverkan påunderhållets framtid och hållbarhetseffekten i produktionens framtid

På begäran av Marinfloc AB har en studie gjorts där ett antal faktorer undersökts som påverkar behandlingen av avloppsvattnet på olika reningsverk. Mätningarna har utförts på respektive anläggnings biologiska steg där de organiska material och ämnen bryts ner. De faktorer som har granskats är vilka metoder som används för att syresätta avloppsvattnet, vilken syrehalt som uppnås och hur mycket energi syresättningen förbrukar. Ett test gjordes också på Marinflocs egna anläggning där vi undersökte om det är någon skillnad i tid att syresätta rent vatten kontra obehandlat avloppsvatten. Undersökningarna visade att de 4 landbaserade reningsverken som besöktes syresätter avloppsvattnet efter samma princip, genom bottenluftning, och att de samtliga ligger på en syrehalt mellan 1,8 – 5,9 mg syre per liter vatten. Marinflocs nuvarande anläggning använder sig av en annan metod än de övriga och ligger på en syrehalt om cirka 12 mg/l. De visade sig att det tar längre tid att syresätta obehandlat avloppsvatten än rent vatten på deras anläggning. 

A direct method for recovering three-dimensional (3D) head motion parameters from a sequence of range images acquired by Kinect sensors is presented. Based on the range images, a new version of the optical flow constraint equation is derived, which can be used to directly estimate 3D motion parameters without any need of imposing other constraints. Since all calculations with the new constraint equation are based on the range images, Z(x, y, t), the existing techniques and experiences developed and accumulated on the topic of motion from optical flow can be directly applied simply by treating the range images as normal intensity images I(x, y, t). In this reported work, it is demonstrated how to employ the new optical flow constraint equation to recover the 3D motion of a moving head from the sequences of range images, and furthermore, how to use an old trick to handle the case when the optical flow is large. It is shown, in the end, that the performance of the proposed approach is comparable with that of some of the state-of-the-art approaches that use range data to recover 3D motion parameters.

The present paper concerns the mechanical response of semi-crystalline polymers during cyclic loading, and it includes both modelling and experimental testing. The model is Eulerian in the sense that it is independent of measures of total deformation and plastic/inelastic deformations. It is able to account for such essential phenomena as strain-rate dependence, work hardening, and damage. The model was applied to uniaxial tension tests performed on high-density polyethylene (HDPE), which is a semi-crystalline polymer widely used in the industry. Two types of tests were conducted: monotonic tests, and loading-unloading tests. The model was able to reproduce the experimental results very well. The proposed model was also implemented as a UMAT in Abaqus, including an analytic tangent. The UMAT was used for simulating two 3D geometries. The implementation seems to be robust, and no convergence problems were observed.

Recognition of maintenance management as a significant factor holds the key to competitiveness in the global market irrespective of the size of the business. Maintenance management practices are primarily found in larger and multinational companies but the purpose of this paper is to investigate the maintenance practices that are used in SMEs of Sweden (Kronoberg County). The study is expected to expose the level of maintenance perception in the Swedish industry via a postal (and web based) questionnaire. The survey covered 74 company chosen from different sectors and produced a response rate of 20.3 percent. The main results achieved from the study show us difference between the maintenance perception and awareness of the maintenance. The respondents are aware of the importance of maintenance, but maintenance is still perceived as a necessary expense. Because according to the results of the survey the percentage of maintenance budget in comparison to the companies’ turnover is on average about 0.97% and it is very low. Again, when we look at the maintenance cost distribution of companies, spare parts and labour costs consist of 73 % of total maintenance cost, despite that they spend very little money for technology and training costs, their percentages in total cost are just 3% and 2%, also they still ignore statistical modelling (historical data) and condition monitoring. Moreover, just 27% of the participants use the maintenance key performance indicators (KPIs), and just 14% of them used basic KPIs which are used for measuring maintenance performance. There is a need to spend and invest more in maintenance especially they should invest more in technology and training to perform them. On the other hand, there is a need for choosing right maintenance strategy and service type, because these points are very important for an effective and economic maintenance management.

Humans are increasingly influencing the climate and the temperature of the Earth by burning fossilfuels, destroying forests, and raising livestock. This adds massive amounts of greenhouse gases(GHG) to those already present in the atmosphere, amplifying the greenhouse effect andcontributing to global warming. The building sector accounts for a significant amount ofgreenhouse gas emissions. Decarbonizing the building industry can result in significant emissionreductions in the future years. Sweden's energy and climate goals have been updated, and some ofthem include reducing GHG emissions in the building sector, increasing energy efficiency, andmaking electricity production 100 percent renewable. In Sweden, energy renovations in singlefamily houses (SFHs) have the potential to reduce GHG emissions and improve energy efficiency,but the rate of energy renovations remains low because of financial, social, and behavioral barriers.This thesis aims to use LCA and LCC methodologies to assess energy renovations on SFH inVäxjö by combining various combinations of energy efficiency measures (EEMs) to reduce energyuse. The energy performance and eight different renovation scenarios using different EEMs havebeen evaluated for the selected single-family building. To evaluate building renovation measures,we developed a method based on life cycle assessment (LCA) and life cycle cost (LCC) thatincorporates building information modeling (BIM). Five different renovation measures werecombined in eight scenarios in this research, including different thicknesses of thermal insulationfor walls and roofs, triple-glazed windows, and doors with different U-values, air-source heatpumps, mechanical ventilation with heat recovery, and solar photovoltaic. The present cost valuesof renovation measures over 50 years for LCC calculation were calculated. The global warmingpotential (GWP) of each renovation measure was estimated over 50 years using One-click LCA.According to the findings of this thesis project, scenarios 1 and 8 had the lowest and highestreductions in primary energy number, respectively. Scenarios 5, 6, 7, and 8 are the most costeffective in comparison to other scenarios. All scenarios resulted in a reduction in GWP impactfrom an LCA perspective in which scenario 7 resulted in the highest reduction in GWP impact. 

Due to the waste crisis in Lebanon and its impact on the social, environmental, and economic sectors, many municipalities like Zahle District and its Unions of Municipalities planned to apply the circular economy to tackle the mismanagement of solid waste. Theoretically, many studies have been conducted at Zahle landfill to integrate was-to-energy technologies and get benefit of the gas generated by anaerobic digestion of biodegradable waste such as food. However, several basic variables related to anaerobic digestion AD had not been taken into consideration such as variation in the organic composition, waste generation related to the population, and power generation efficiency. Therefore, based on the plans set by Law 80 on Integrated Solid Waste Management ISWM to achieve 35% recycling rates 2025-2035, and Intended Nationally Determined Contribution (INDC) with conditional target 30% of recycling by 2030, the aim of this thesis is to estimate the biomethane production and power generation achieved at different rates of food waste digestion between 2025 and 2035, to achieve 30 and 35% recycling of FW beside the composting.Thus, scenario A where 10 to 20% of FW is digested, by increasing 1% every year from 2025 t0 2035, and 15% for composting as constant, results show a biomethane yield of 604000 to 1725000m3 annually, with a power generation 2400 to 6800 MWh/years for 2025 and 2035 respectively by usage of 1MW CHP 41.25% electrical efficiency. The achievement of scenario A requires 5 to 9 150m3digesters.Scenario B where digestion rates are 25% by 2025 and 35% by 2035 requires 10 to 19 150m3digesters, where biomethane and power production have ranges of 1466500 to 3019000 m3 annually, and 5800 to 11900MWh/year, respectively.

While the HPC community is working towards the development of the first Exaflop computer (expected around 2020), after reaching the Petaflop milestone in 2008 still only few HPC applications are able to fully exploit the capabilities of Petaflop systems. In this paper we argue that efforts for preparing HPC applications for Exascale should start before such systems become available. We identify challenges that need to be addressed and recommend solutions in key areas of interest, including formal modeling, static analysis and optimization, runtime analysis and optimization, and autonomic computing. Furthermore, we outline a conceptual framework for porting HPC applications to future Exascale computing systems and propose steps for its implementation.

Wind-induced dynamic excitation is becoming a governing design action determin-ing size and shape of modern Tall Timber Buildings (TTBs). The wind actions generate dynamic loading, causing discomfort or annoyance for occupants due to the perceived horizontal sway – i.e. vibration serviceability failure. Although some TTBs have been instrumented and meas-ured to estimate their key dynamic properties (natural frequencies and damping), no systematic evaluation of dynamic performance pertinent to wind loading has been performed for the new and evolving construction technology used in TTBs. The DynaTTB project, funded by the Forest Value research program, mixes on site measurements on existing buildings excited by heavy shakers, for identification of the structural system, with laboratory identification of building elements mechanical features coupled with numerical modelling of timber structures. The goal is to identify and quantify the causes of vibration energy dissipation in modern TTBs and pro-vide key elements to FE modelers.

The first building, from a list of 8, was modelled and tested at full scale in December 2019. Some results are presented in this paper. Four other buildings will be modelled and tested in spring 2020.

Wind-induced dynamic excitation is a governing design action determining size and shape of modern Tall Timber Buildings (TTBs). The wind actions generate dynamic loading, causing discomfort or annoyance for occupants due to the perceived horizontal sway, i.e. vibration serviceability problem. Although some TTBs have been instrumented and measured to estimate their key dynamic properties (eigenfrequencies, mode shapes and damping), no systematic evaluation of dynamic performance pertinent to wind loading had been performed for the new and evolving construction technologies used in TTBs. The DynaTTB project, funded by the ForestValue research program, mixed on site measurements on existing buildings excited by mass inertia shakers (forced vibration) and/or the wind loads (ambient vibration), for identification of the structural system, with laboratory identification of building elements mechanical features, coupled with numerical modelling of timber structures. The goal is to identify and quantify the causes of vibration energy dissipation in modern TTBs and provide key elements to finite element models. This paper presents an overview of the results of the project and the proposed Guidelines for design of TTBs in relation to their dynamic properties.

Cross Laminated Timber (CLT) has in recent years become a more important building material. This means that the demand for accurate calculation methods in building standards such as Eurocode 5 has increased. There is limited knowledge about the connections in CLT buildings which is an important part of a CLT structure. This thesis was therefore focused on investigating a wall-floor-wall type connection commonly found in platform type buildings. 

An experimental and numerical study on typical wall-floor-wall connections was carried out in this thesis. In the experimental part 60 tests with 8 different configurations were conducted to investigate the influence of different parameters on the connection, moment capacity and rotational stiffness. During the tests the deformation of the specimens under four load levels were investigated. Compression tests were also performed on the specimens to determine the compressive strength and stiffness of the elements. In the numerical part two different models for the connection were created. One simplified model with rotational springs and one more complex model with compression springs. With these models the influence from the number of stories, span and thickness of the wall on the global behavior of a structure was investigated. 

The result from this thesis shows that there is both moment capacity and rotational stiffness in the wall-floor-wall type connection that can be utilized in the design phase of a structure. This was proven by both the experimental and the numerical study. The parameters that influence the behavior of the connection most were the load level applied on the wall and the wall thickness. The model created in the numerical study showed great potential regarding the replication of the connection behavior observed in the experimental study.  

This study is made to understand the opportunities and challenges SMEs have to adopt GHG calculation tools. Adoption of GHG calculation tools are common by large organizations and have proven as a consequence to lower their GHG emissions, motivate their employees and establish sustainability goals. Even thou a large amount of large organizations have adopted GHG calculation tools, this is very rare in SMEs. Using the theoretical framework called Rogers diffusion of innovation theory and a survey, the factors behind why or why not SMEs have adopted GHG calculation tools were studied. The results showed that only 9% of SMEs have adopted GHG calculation tools and the reason for this is lack of resources, competence and data. The analysis showed that the characteristics of an organization that affects this the most are leadership, education and regulations. In order to overcome the challenges, organizations should prioritize to have a leadership that motivates employees to engage in sustainability actions. Organizations should enable skill development in the field of sustainability to increase the competence. This would enable more organization to adopt GHG calculation tools and most likely lower their GHG emissions. 

Syftet med arbetet är att undersöka hur bullernivån kan minskas eller elimineras genom att utveckla en lösning som förhindrar bakluckan på Volvos A45 dumper från att studsa. Genom en utvecklad och noggrann produktutvecklingsprocess redovisades 14 olika koncept. Tillsammans med Volvo CE valdes ett koncept som var en vidareutveckling från en tidigare lösning. Resultatet är en robust och funktionssäker lösning som minskar bullernivån samtidigt som det inte påverkar hållfastheten på dumpern negativt.

Landsbygderna är en stor del av vårt samhälle och en resurs som kan bidra till en långsiktigt hållbar samhällsutveckling. Dock finns det rådande problem på landsbygderna som bland annat nedläggning av skolor och minskad kollektivtrafik. På senare tid har det börjat komma positiva initiativ på landsbygderna. 

Arbetet syftar till att inspirera om landsbygd och samhälle genom att peka på positiva initiativ men också belysa de problem och hinder som finns på landsbygden. Arbetet genomförs i form av intervjuer och en fallstudie med tre stycken landsbygdsprojekt. I fallstudien undersöktes olika projekt och processer som ligger i tiden och hur de kan skapa en mer levande landsbygd.

Resultatet visar att positiva initiativ tillsammans med processerna som ligger i tiden kan bidra till mer levande landsbygder. Landsbygdsprojekten i fallstuiden tillsammans med intervjuerna visar att det finns potential för hållbar samhällsutveckling på landsbygden. Resultatet visar också att de tre hållbarhetsdimensionerna berörs i de olika landsbygdsprojekten. 

Slutsatserna som dragits baseras på det framkomna resultatet av både fallstudien och intervjuerna. Utifrån arbetet går det se att det finns flera faktorer såsom synergier, entreprenörskap och gräsrotsinnovationer som påverkar landsbygden positivt men också vad som kan bidra till en mer levande landsbygd. 

Nowadays, companies started to realize the impact of a good maintenance strategy on the production process. Quality, performance as well as availability are affected by maintenance; existing maintenance strategies help to optimize the production process to achieve high quality products with a low production cost. A new strategy of maintenance has immerged recently, e-maintenance provides an easy solution to follow up with maintenance, it provides condition monitoring, documentation, and it also gives you the best maintenance solution that fits your goals and vision. Articles related to e-maintenance was studied and analyzed to know the steps to implement a cost-effective e-maintenance. The authors came up with a model that describes the implementation process in three main steps.

The use of plastic materials in the design of vehicle components is primarily driven by the need for vehicle weight and cost reduction. Additionally, these materials give design engineers freedom in creating appealing exterior designs. However, creating self-carrying exterior structures with polymers must fulfill long-term strength, creep and fatigue life requirements. Thus, the polymer polyDicyclopentadiene (pDCPD) has been chosen for this purpose. Its aging mechanics need to be understood by the design engineers to make the right decisions. This thesis has carried out mechanical tests such as uniaxial tensile testing, fatigue, and creep testing. Digital image correlation (DIC) system has been used to capture strain data from tensile tests. In the final analysis, DIC measurements proved more accurate than extensometer data retrieved from the testing machine. The rise in temperature has been captured using thermal imaging. Several degradation processes have been explored including physical aging, thermo-oxidation, photo-oxidation, chemical- and bio- degradations. Test results showed significant changes in mechanical properties after 17 years of aging. Additionally, severe thermal degradation has been observed in one of the tested panels of pDCPD. Temperature can rise to significant levels during cyclic loading at high stresses, which could have an impact on physical aging effects. Viscoelastic behavior has been explored and changes in dynamic and creep properties have been observed. The investigation also reviled that different defects caused by flawed manufacturing also can affect the material severely as one case has proved in this research.

As the demand of high data rate is increasing, a lot of research is being conducted in the field of wireless communication. A well-known channel coding technique called Space-Time Coding has been implemented in the wireless Communication systems using multiple antennas to ensure the high speed communication as well as reliability by exploiting limited spectrum and maintaining the power. In this thesis, Space-Time Coding is discussed along with other related topics with special focus on Alamouti Space-Time Block Code. The Alamouti Codes show good performance in terms of bit error rate over Rayleigh fading channel. The performance of Altamonte’s code and MIMO capacity is evaluated by using MATLAB simulation.

To bridge the technology gap between IC-level and board-level fabrications, a fully additive selective metallization has already been demonstrated in the literature. In this article, the surface characterization of each step involved in the fabrication process is outlined with bulk metallization of the surface. This production technique has used polyurethane as epoxy resin and proprietary grafting chemistry to functionalize the surface with covalent bonds on an FR-4 base substrate. The surface was then metalized using an electroless copper (Cu) bath. This sequential growth of layers on top of each other using an actinic laser beam and palladium (Pd) ions to deposit Cu is analyzed. State-of-the-art material characterization techniques were employed to investigate process mechanism at the interfaces. Density functional theory calculations were performed to validate the experimental evidence of covalent bonding of the layers. This manufacturing approach is capable of adding metallic layers in a selective manner to the printed circuit boards at considerably lower temperatures. A complete analysis of the process using bulk deposition of the materials is illustrated in this work.

Scientific and technological innovations have become increasingly important as we face the benefits and challenges of both globalization and a knowledge-based economy. Still, enrolment rates in STEM degrees are low in many European countries and consequently there is a lack of adequately educated workforce in industries. We believe that this can be mainly attributed to pedagogical issues, such as the lack of engaging hands-on activities utilized for science and math education in middle and high schools. In this paper, we report our work in the SciChallenge European project, which aims at increasing the interest of pre-university students in STEM disciplines, through its distinguishing feature, the systematic use of social media for providing and evaluation of the student-generated content. A social media-aware contest and platform were thus developed and tested in a pan-European contest that attracted >700 participants. The statistical analysis and results revealed that the platform and contest positively influenced participants STEM learning and motivation, while only the gender factor for the younger study group appeared to affect the outcomes (confidence level – p<.05).

Abstract

Today Sweden has 341 ice hockey arenas, around 140 outdoor ice hockey rinks, 60 ice fields for bandy and about 35 curling arenas. In addition, the numbers of indoor bandy arenas are increasing. The cooling systems installed today should be able to lower its energy consumption with 10-30%.In this thesis, Ronneby ice-arena has been researched. This artificial cooling facility was inaugurated 2011 and is one of the newest in Sweden. This is an outdoor ice field for bandy and therefor has no roof or walls to cover the field. Ronneby ice-arena has problems with uneven cooling distribution of the ice field. This results in cracks and uneven ice quality. These problems also result in higher energy consumption than necessary.To find a solution for the uneven cooling of the ice field flow measurements were carried out in the brine circuit. To get a better understanding of the cooling distribution, temperature measurements were carried out on the brine feeding lines. A calculation has been performed on what energy savings a speed control of the brine circulation pumps depending on the outdoor temperature could generate. Another calculation was made to see the possible savings with a windshield around the field. In this thesis the benefits of a heat recovery system on the cooling compressors refrigerant has been investigated. The heat recovery system could heat the locker rooms, the clubhouse, the showers and the hot water for the Zambonis.In order to perform the necessary calculation for this thesis, Fredriksbergs BK and Ronneby municipality provided operating data.The actions proposed to Ronneby ice-arena to solve the uneven cooling of the ice field is to change the location of the brine feeding line connection point. At the same time this work is carried out it’s suggested that the brine feed and return lines get insulated. When the uneven cooling problems have been solved, a speed control system should be installed to control the brine circulation pumps, in order to lower the electricity consumption. Ronneby ice-arena has the possibility to install a heat recovery system. Therefore it is suggested to install a heat exchanger on each cooling compressor refrigerant. This installation is to be used to heat the clubhouse, the showers and the hot water for the Zambonis. The system to cool the condensers with seawater and currently the heat pump are not optimal designed. The installed heat pump does not work when the seawater temperature is below 5°C, therefore the system should be redesigned.

Environmental – economic pressure and associated regulations have led to a significant increase of recycled paper as the main fibrous component of corrugated board the last years. Corrugating packaging industry is facing the challenge to enhance products derived from recycled pulp and to ensure a satisfactory strength of packages. Advanced techniques are highly needed for the evaluation of packaging fiber supply sources as well as for the utilization of the available resources in an optimal manner. As industrial packaging is based on the characteristics of its constituent fibers, information on the fiber composition of the recycled raw materials is of primary importance for a continual control of fiber sources. This paper reports on the usefulness of fiber analysis techniques as diagnostic methods for assessing the potential quality distribution of fibers for sustainable packaging manufacturing.

Environmental and economic issues have led to a significant increase of recycled paper as the main fibrous component of corrugated board the last years. Qualitative data on the different fibre types are needed for the evaluation of packaging fibre supply sources, which are becoming numerous and heterogeneous. Fifteen different packaging grade papers (7 linerboards and 8 corrugating medium) were selected to represent all the variety of papers available on the Spanish market. The origin of virgin and recycled fibres was identified by their morphological characteristics employing light microscopy and standard fibre analysis techniques. The waste-based papers (Waste based-liners and Fluting), Kraft-liners and Test-liner were highly variable containing 9–18 different wood and nonwood components. Semi-chemical, with 5–13 components, was the less variable grade. Hardwoods were identified as the most important fibre component from a quantitative standpoint. All papers contained in their hardwood mix Betula, Eucalyptus and Populus in significant amounts. Fagus sylvatica and Tilia were also frequently observed and in some papers were amongst major hardwood components. Prominent softwood components were found to be Pinus sylvestris, P. pinaster, P. radiata, Picea, Larix and in some papers Pinus nigra. The lower presence of a variety of softwood, hardwood and nonwood (mainly grasses) species and genera was due to the paper recycling process.