Händelser: Studentarbete, Arkitektur, Bygg- och miljöteknik, Data- och informationsteknik, Energi och miljö, Kemi- och bioteknik, Matematiska vetenskaper, Material- och tillverkningsteknik, Mikroteknologi och nanovetenskap, Produkt- och produktionsutveckling, Rymd- och geovetenskap, Signaler och system, Sjöfart och marin teknik, Teknikens ekonomi och organisation, Fysik, Tillämpad IT, Tillämpad mekanik, Rymd-, geo- och miljövetenskap, Arkitektur och samhällsbyggnadsteknik, Bioteknik, Elektroteknik, Industri och materialvetenskap, Informations- och kommunikationsteknik, Mekanik och maritima vetenskaperhttp://www.chalmers.se/sv/om-chalmers/kalendariumAktuella händelser på Chalmers tekniska högskolaThu, 16 Sep 2021 15:33:10 +0200http://www.chalmers.se/sv/om-chalmers/kalendariumhttps://www.chalmers.se/sv/institutioner/ims/kalendarium/Sidor/Challenges-to-achieve-fossil-free-production.aspxhttps://www.chalmers.se/sv/institutioner/ims/kalendarium/Sidor/Challenges-to-achieve-fossil-free-production.aspxChallenges to achieve fossil-free production<p>Online</p><p>​Issa Hermz &amp; Julian Zora presenterar sitt examensarbete. Online presentation.</p><div>Program: BSc Mechanical Engineering</div> <div>Examinator: Dr Mélanie Despeisse (IMS, Chalmers)</div> <div>Handledare: Lena Moestam &amp; Ann Sofie Gullbring (Volvo Group Trucks Operations)</div> <div>Opponenter: Rasmus Hilmersson &amp; Rahul Kirpalani</div> <div><br /></div> <div><strong>Abstract</strong></div> <div>Volvo Trucks as a company are making their efforts to complete their part of the</div> <div>Paris agreement aiming for sustainability through making their production of trucks</div> <div>fossil-free. The problems of this are difficult in part because of the company being so</div> <div>large and in part because of the technology available, which to focus on and which</div> <div>to research. We have been assigned to create a roadmap for Volvo Trucks through</div> <div>research and interviews with different experts from different sites from Volvo Trucks</div> <div>here in Sweden to find out what in particular every site needs to achieve these</div> <div>goals. What has been concluded from all this are roadmaps for each individual site</div> <div>with specific problems and possible solutions for all of them and the company as</div> <div>a whole. The results shown are very interesting as there are specific problems in</div> <div>some sites that others might have and the possible solutions that may be used and</div> <div>researched. There is a lot of work that has been done and showcased in this report</div> <div>which people can take part of and work with for themselves regarding making a</div> <div>sustainable production work.</div>https://www.chalmers.se/sv/institutioner/e2/kalendarium/Sidor/Chattarin-Wangwittaya.aspxhttps://www.chalmers.se/sv/institutioner/e2/kalendarium/Sidor/Chattarin-Wangwittaya.aspxChattarin Wangwittaya<p>Online</p><p>​Healthcare Staff Scheduling at an Emergency Department in Thailand</p><br /><div><strong>Examinator: Kristofer Bengtsson</strong></div> <div><strong>Opponent: </strong><br /></div> <div><br /></div> <div><strong>Abstract: </strong></div> <div>Healthcare staff scheduling has been renowned for its correlation with service quality, care outcome, and staff turnover rate. Nevertheless, the complexity of the process usually impedes the hospital from achieving those goals. Particularly at the emergency department of Siriraj Hospital, the complications in scheduling are expedited by the high number of registered nurses (RNs) and the policy for ensuring adequate care service. To enhance the efficacy of human resource management, this thesis investigates the optimization model’s capability in the on-duty scheduling of RNs. </div> <div><br /></div> <div>The scheduling requirements were collected from the interviews with four stakeholders from the management team and the governed staff. The service blueprint was created to visualize the scheduling process, and the mathematical model was formulated following the collected requirements. There are two optimization models developed in this study, i.e., the mixed integer programming (MIP) model and the genetic algorithm (GA) model. Two sets of scheduling data for testing the models were obtained from the past RNs schedules in May-June and July-August 2021. </div> <div><br /></div> <div>The performance comparison between the MIP and GA model demonstrated the inefficiency of GA in optimizing the highly constrained problem, as it can provide only 3.95% of evaluation metrics with better outcomes than MIP. In comparing manual and MIP-optimized schedules, both approaches provide more than half of the evaluation metrics with unchanged outcomes, thus having comparable performance in optimizing most of the schedule’s features. </div> <div><br /></div> <div>However, MIP can significantly optimize 24% to 25% of the metrics while having only 6.58% to 9.21% of the metrics with deteriorated outcomes compared to the manual approach. As a result, the MIP optimization model possesses more superior performance than the GA model and manual approach in optimizing the scheduling of RNs at the emergency department of Siriraj Hospital. <br /></div> <div><br /></div> <div>The MIP optimization in reducing work stress, promoting staff satisfaction, providing fairness, conforming to the policy, and cutting scheduling time can lead to excellence in service quality and care outcome while lowering the turnover rate. Consequently, the optimization of healthcare staff scheduling with the MIP model exerts the capability of human resource management to its greater extent.</div> <div><br /></div> Welcome to the presentation. <br />https://www.chalmers.se/sv/institutioner/fysik/kalendarium/Sidor/Masterpresentation-Arturo-Cevallos-Soto-210920.aspxhttps://www.chalmers.se/sv/institutioner/fysik/kalendarium/Sidor/Masterpresentation-Arturo-Cevallos-Soto-210920.aspxArturo Cevallos Soto<p>Online via Zoom</p><p>​Titel på masterarbete: Evolving protoplanetary disk composition: coupling full chemical network with transport dynamics in a 1-D model Följ presentationen online Lösenord: 654321</p><div><strong>​Sammanfattning:</strong></div> <div>Context. The Inside-Out Planet Formation (IOPF) theory proposes that close-in super-Earth planets<br />form in situ at the pressure maximum associated with the Dead Zone Inner Boundary (DZIB). The<br />chemical composition of pebbles and gas reaching this location would in<br />uence that of such planets:<br />both the planetary cores and any primordial atmosphere.<br />Aims. Our goal is to develop a combined model of physical and chemical evolution of protoplanetary<br />disk midplanes that follows gas advection, radial drift of pebbles and gas-grain chemistry to predict<br />the abundances of species from outer disk scales of up to 300 AU down to the small scales of the DZIB<br />near 0.1 AU.<br />Methods. We adopt a steady, thin, accretion disk structure that yields midplane properties (tem-<br />perature, density, etc.) for dierent accretion rates m_ in the range 10&#1048576;8 to 10&#1048576;9 M&#12; yr&#1048576;1 and a<br />viscosity parameter = 10&#1048576;4. A full chemical network including gas-phase, gas-grain/pebble inter-<br />actions and grain-surface chemistry evolves the composition of each radial location, which is coupled<br />with continuous gas and pebble transport for a duration of t = 105 years. Initial abundances are set<br />by assuming some prior chemical evolution at temperatures &lt; 20 K. The eect of dierent grain sizes<br />is also investigated.<br />Results. We find pebble drift has a large in<br />uence on the overall solid to gas ratio in the disk<br />midplane. This is most significant for models with large pebble sizes. It was found that the choice<br />of abundances for initial and boundary conditions can have a strong impact on the final composition<br />delivered to the inner region. We find that C and up to 90 % of O nuclei start locked in CO and O2 ice,<br />which keeps abundances of other species like CO2 and H2O one order of magnitude lower. Volatiles'<br />gas phases have their abundances enhanced by up to an order of magnitude at their respective iceline<br />locations due to the radial drift of icy pebbles. Gas advection then brings these species to the hot inner<br />disk. These region, with fastest gas advection velocities, show the largest dierences in abundances<br />compared to static models. CO2, which does not form close to the DZIB, is rather transported there<br />by this process. Lower accretion rates yield lower disk temperatures, which aects icelines' locations<br />by shifting them closer to the star. While transport does modify the C/O ratio for gases and solids, we<br />find that other model assumptions related to initial/boundary conditions and pebble size distribution<br />have an even larger influence.<br />Conclusions. We have demonstrated the importance of the combined physical and chemical evolution<br />to understand the composition of pebbles and gas for planet formation. In particular, we have explored<br />the sensitivity of key metrics, such as solid and gas phase element ratios to the choices of initial and<br />boundary conditions of such models.<br /><br /></div>https://www.chalmers.se/sv/institutioner/fysik/kalendarium/Sidor/Masterpresentation-Alfred-Stenseke-210923.aspxhttps://www.chalmers.se/sv/institutioner/fysik/kalendarium/Sidor/Masterpresentation-Alfred-Stenseke-210923.aspxAlfred Stenseke, MPAPP<p>Online via Zoom</p><p>​Titel på masterarbete: Predicting physical properties of NCMM cathode material using machine learning guided DFT simulations Följ presentationen online Lösenord: 399281</p><div><strong>​Sammanfattning: </strong><br /></div> <div>With the rapid increase in development of electric vehicles and energy storage systems over the last decades, the demand for long lasting batteries with high energy density is higher than ever before. One crucial aspect of a lithium battery is the longterm cycling performance -- to perform with high capacity even after thousands of charge-discharge cycles with as small degradation as possible. One cause for this degradation is the occurrence of small micro cracks in the cathode material due to small volume changes during charge-discharge cycles. To suppress this effect, state-of-the-art batteries today use metallic dopants such as aluminum in the cells of the cathode material. This project investigates other suitable dopants by implementing regression and gradient based prediction models on data acquired from supercomputer simulations using density functional theory (DFT). The results, while not fully conclusive, gives indications on what atomic features of dopants are interesting, as well as validates this relatively new machine learning approach in material science.<br /></div>https://www.chalmers.se/sv/institutioner/m2/kalendarium/Sidor/The-dynamics-of-a-wheel-loader-handling-unbound-granular-material.aspxhttps://www.chalmers.se/sv/institutioner/m2/kalendarium/Sidor/The-dynamics-of-a-wheel-loader-handling-unbound-granular-material.aspxThe dynamics of a wheel loader handling unbound granular material<p>CoG, meeting room, Hörsalsvägen 7A, M-huset. Eller online i Teams.</p><p>​Marsel Balla presenterar sitt examensarbete med titeln &quot;The dynamics of a wheel loader handling unbound granular material&quot;.</p>​<div>Student: Marsel Balla</div> <div><br /></div> <div>Handledare: Johannes Quist, Andrea Tonoli, Mathias Lidberg, Torbjörn Ekevid, Elianne Lindmark och Klas Jareteg</div> <div><br /></div> <div>Examinator: Mathias Lidberg</div> <div><br /></div> <div>Opponent: Athanasia Dineff</div>https://www.chalmers.se/sv/institutioner/m2/kalendarium/Sidor/Tractor-semitrailer-vehicle-model-validation-based-on-Bayesian-hypothesis-testing.aspxhttps://www.chalmers.se/sv/institutioner/m2/kalendarium/Sidor/Tractor-semitrailer-vehicle-model-validation-based-on-Bayesian-hypothesis-testing.aspxTractor-semitrailer vehicle model validation based on Bayesian hypothesis testing<p>CoG, meeting room, Hörsalsvägen 7A, M-huset. Eller online i Teams.</p><p>​Athanasia Dineff presenterar sitt examensarbete med titeln &quot;Tractor-semitrailer vehicle model validation based on Bayesian hypothesis testing&quot;.</p>​<div>Student: Athanasia Dineff</div> <div><br /></div> <div>Handledare: Peter Nilsson, Thorsten Helfrich och Mohamed Takkoush</div> <div><br /></div> <div>Examinator: Mathias Lidberg</div> <div><br /></div> <div>Opponenter: Nrupathunga Ashok och Liam Gerlin​</div>https://www.chalmers.se/sv/institutioner/e2/kalendarium/Sidor/Shreya-Pai.aspxhttps://www.chalmers.se/sv/institutioner/e2/kalendarium/Sidor/Shreya-Pai.aspxShreya Pai<p>Online</p><p>​Evaluation of circular economy in the life cycle of ABB’s low voltage distribution cabinet system</p><br /><div><strong>​Examinator: Jimmy Ehnberg</strong></div> <strong>Opponent: Safoora Qayyum</strong><br /><div><br /></div> <div><strong>Abstract: </strong></div> <div>The UN’s intergovernmental panel on climate change (IPCC) says that human activity is changing the climate change at unprecedented rate (UN IPCC 2021) and this has been described as ‘code red for humanity’ hence it’s important to act now more than ever. </div> <br /><div>The linear economy narrative of the traditional model based on a ‘take, make, consume, dispose’ is now changed to ‘cradle to cradle’ concept. The growing importance of implementing a more circular approach in terms of products and processes is paving path towards a sustainable society. Sustainability is a key part of ABB’s purpose and of the value created for all stakeholders. ABB’s business unit in Alingsås, Sweden (ABB Kabeldon) develop and manufacture electrical distribution products.</div> <br /><div>The objective of this thesis to facilitate the use of life cycle assessment method for evaluation and identify environmental footprint of ABB’s LV cabinet system and thereby explore options for circular economy. The LCA was conducted on SimaPro software and the results showed that the use phase was the most contributing factor within the investigated environmental categories and the total climate impact during the whole life cycle of the Cabinet (CDC 440)along with fuse switch disconnector (SLD 1) and connector (ADI 300) is 529 kg CO2 eq. </div> <br />There were three business models that were evaluated and studied in detail by having discussion and interviews with several experts at ABB. Three models being the product service system model where the product ownership was retained with the company and the function of the product is sold as a function, then the second was refurbishment/ remanufacturing model which emphasized on the take back system,<br />customer incentives and prolonged use of the product. Last but not the least was the most important model which is the recycling business model partnership, where partnership with Stena recycling was explored in order to complete the circular loop with recycled materials flows back into ABB’s loop and completes it making the process circular. The methods were criticized, strengths were highlighted to get racial view and it can be concluded that a Circular Economy Business Model can bring several benefits.<br /><div><br /></div> <div>Welcome to the presentation.<br /></div>https://www.chalmers.se/sv/institutioner/chem/kalendarium/Sidor/Exjobbspresentation-Wasinee-Charoenchang,-Kemi-och-kemiteknik.aspxhttps://www.chalmers.se/sv/institutioner/chem/kalendarium/Sidor/Exjobbspresentation-Wasinee-Charoenchang,-Kemi-och-kemiteknik.aspxExjobbspresentation Wasinee Charoenchang, Kemi och kemiteknik<p>Zoom</p><p>​Analysis of Fuel-Air Mixing in Jet in Crossflow</p>​<div><span style="background-color:initial">Supervisor: Daniel Lörstad, PhD, Siemens Energy AB</span><p class="MsoNormal"></p> <p class="MsoNormal"><span style="background-color:initial"><br /></span></p> <p class="MsoNormal"><span style="background-color:initial">Examiner: Ronnie Andersson</span><br /></p> <p class="MsoNormal"><span lang="EN-US"><br /></span></p> <p class="MsoNormal"><span lang="EN-US">24th September at 09:00 </span></p> <p class="MsoNormal"><br /></p> <p class="MsoNormal"><a href="https://chalmers.zoom.us/j/69764064377">https://chalmers.zoom.us/j/69764064377</a></p> <span style="background-color:initial">Password: 564985</span></div>https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Examensarbete210916.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Examensarbete210916.aspxPresentation av examensarbete<p>MV:H 11 och digitalt</p><p>​Henrik Berggren: Modelling Glioblastoma Growth in Anisotropic Tissue. Identification of Cell Line-Specific Parameters Governing Distinct Growth Patterns</p>https://www.chalmers.se/sv/institutioner/e2/kalendarium/Sidor/Yuling-Zhang-och-Yaxi-Xie.aspxhttps://www.chalmers.se/sv/institutioner/e2/kalendarium/Sidor/Yuling-Zhang-och-Yaxi-Xie.aspxYuling Zhang och Yaxi Xie<p>Online</p><p>​Object detection using deep learning and camera-lidar fusion methods</p><div><strong>​</strong></div> <div><strong>Examiner:</strong> Lars Hammarstrand</div> <div><strong><br /></strong></div> <div><strong>Abstract </strong></div> More reasonable decisions regarding path security rely on a better understanding of the surrounding environment. The perception collects measurements from the environment using sensors, such as cameras, lidars and radars. Based on the collected data, the location and class of objects are predicted by object detection algorithms.<br /><br />There are different detection methods based on single or multiple sensors. To fully use the characteristics from various sensors, combining the information from multiple sensors may be a potential prospect, so-called sensor fusion. Sensor fusion can<br />achieve more reliable results by the complementary information from different sensors. It is certified that trained deep neural networks have the strength to achieve accurate object detection. <br /><br />The main objective of this thesis is to investigate how the lidar-only deep model CenterPoint can be improved by also considering camera information. One of the common ways to extract object classification from a camera is semantic segmentation, partitioning the pixels with semantic labels. The semantic segmentation scores for relevant objects should help object detection. Hence, this thesis focuses on the following research questions: 1) Can the CenterPoint algorithm<br />be improved by including semantic information from a camera? If so, by how much? 2) Are there situations where fusing with the segmentation information degrade the result? 3) What are the reasons causing the differences?<br /><br />We propose a fusion strategy called Painted CenterPoint, inspired by the PointPainting fusion algorithm. After projecting lidar point clouds on images, points are painted with the corresponding segmentation scores. Then employ the CenterPoint on painted point clouds to achieve the final detection results. The segmentation methods would differ how PointPainting benefits the lidar detector in different metrics and scenarios, so we introduce three segmentation methods: DeepLabV3, DeepLabV3+ and Hierarchical Multi-scale Attention (HMA). We train the fusion models on a simple KITTI training set to detect and classify Vehicle, Pedestrian and Cyclist classes. Then the model is evaluated on KITTI metrics and also cross evaluated on nuScenes to test the robustness. The final results indicate that CenterPoint can be improved by the &quot;paint&quot; strategy. In conclusion, Painted CenterPoint with DeepLabV3 gives the most unstable results. And Painted CenterPoint with HMA gives the highest improvements and precision on KITTI. The performance of DeepLabV3+ is somewhere in between. Keywords: Deep Learning, Image Segmentation, Object Detection, Sensor Fusion.<br />https://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Examensarbete210924.aspxhttps://www.chalmers.se/sv/institutioner/math/kalendarium/Sidor/Examensarbete210924.aspx​Presentation av masterarbete<p>Pascal, Hörsalsvägen 1, och digitalt</p><p>​Helena Andersson: Multidimensional Data-Driven Modelling of Engine Test Cell Data. Using Gaussian Process Regression and Neural Networks to Model Volumetric Efficiency of Four-Stroke Internal Combustion Engines</p><p>​<br />Abstract:<br />In the journey towards a more sustainable vehicle fleet, requirements for lower emissions and improved energy efficiency in gasoline engines lead to more components being added to the internal combustion engines. This adds to the degrees of freedom when trying to model air flow in the engine using volumetric efficiency. This paper presents a way of modelling volumetric efficiency from engine test cell data provided by T-Engineering – a company that designs and develops control systems for vehicles. The model uses Gaussian process regression (GPR) for inter- and extrapolation, including noise reduction of the measurement data. Furthermore, a local interpretable model agnostic explainer (LIME) is used to find regions of uncertainty by explaining what features contribute to increasing the variance of the GPR predictions. In addition, a neural network model is implemented in order to improve the prediction runtime, with the purpose of enabling real-time predictions in the control systems.</p> <p>The model(s) were found to give a more physically accurate description of volumetric efficiency than the one currently used at T-Engineering. The runtime for making predictions for 50 data points with the neural network was ∼ 0.14 ms on an AMD Ryzen 7 PRO 4750U with Radeon Graphics 1.70 GHz and 32.0 GB RAM. It remains to investigate what the runtime on a limited CPU in the control systems will be.</p> <p>Handledare: Per Andersson-Hedberg, T-Engineering<br />Handledare: Anton Johansson, Matematiska vetenskaper<br />Examinator: Serik Sagitov</p>https://www.chalmers.se/sv/institutioner/fysik/kalendarium/Sidor/Masterpresentation-Thomas-Suphona-210927.aspxhttps://www.chalmers.se/sv/institutioner/fysik/kalendarium/Sidor/Masterpresentation-Thomas-Suphona-210927.aspxThomas Suphona, Fysik<p>Online via Zoom</p><p>​Titel på masterarbete: Collective behaviors of autonomous robots in complex environment Följ presentationen online Meeting ID: 685 1796 9304 Lösenord: 080939</p><div><strong>​Sammanfattning:<br /></strong></div> <div>Collective behaviours or collective motion is a common phenomena in nature where multiple organisms in a system undergo ordered movements. This can be observed in different scales, from the microscale with bacteria swarming to the macro scale with for example flocks of birds, schools of fish and even human crowds and car traffic.<br />All these systems are made up by self-propelling agents who are able to take up energy from their environment and converting it to directed motion. <br />Because of this<br />property of self-propulsion, their dynamics cannot be explained using conventional methods. Although significant efforts have been made in trying to explain collective behaviours from different perspective, using simulation tools and study systems in different scales as mentioned before, the subject is not as widely studied from the macroscale, especially with artificially made systems. In this thesis, a macroscale system was design with the purpose of providing conditions for collective behaviours to emerge and study how the behaviours changes depending on the surrounding conditions. Battery powered robots were used as self-propelling agents and they were placed in a confined space filled with obstacles. It was shown that when the number of robot and obstacles inside the system is large, the robots movements were significantly restricted. The weight of the obstacles do also affect the average motions of the robots where heavier obstacles hinders the robots by creating blockage leading to the robots having lower average velocity. At certain configuration of the parameters, the robots showed collective behaviours where they for example form channels between the obstacles, making ”roads” for other robots to reuse, or helping each other to move by pushing away chunks of obstacles or pushing onto each other. Even though these robots are simple agents, they have manage to manifest cooperative actions towards other agents.<br /><br /><strong></strong></div>