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Micro Transactions and Automation of Industrial Assembly Planning
No full textThis thesis discusses two subjects: distributed ledgers scalable enough to support micro-transactions, and automating assembly planning in manufacturing industries. Established blockchain solutions achieve high robustness and reliability. By being distributed and decentralized, they avoid a single point of failure, and fault-tolerant consensus mechanisms ensure that the system works as intended in the presence of malicious participants. However, their main weakness is scalability. The two most popular and well-known blockchain solutions require all nodes to store all transactions, and the transaction throughput is far too low to compete with traditional, centralized transaction processing systems. To improve scalability, systems have been developed that split the network nodes into groups that can process transactions in parallel, also known as sharding. We propose a novel approach to sharding, called ScaleGraph, which uses concepts from distributed hash tables to define shards dynamically. Nodes store and validate only transactions involving those accounts that are close to the node according to a logical distance metric. This greatly reduces the storage burden on each node and allows any number of transactions involving distinct accounts to be validated in parallel. By employing a synchronous consensus protocol, shards can be kept smaller without sacrificing fault tolerance, especially in a permissioned environment where participation can be controlled and a small fraction of malicious nodes can be assumed. Manufacturing is a highly complex process in many industries, involving many different planning problems, and increasing automation has the potential to make manufacturing more efficient. This thesis presents a proof-of-concept solution to the kitting layout planning problem, where a list of parts has to be placed on a kitting wagon for delivery to an assembly line station. However, some problems have proven difficult to automate in practice, despite decades of research. One such problem, assembly line balancing, is analyzed in depth. We identify fundamental challenges that make the goal of complete automation implausible in some industries, such as automotive manufacturing. Human intervention is thus unavoidable, suggesting that assisted planning is a more promising approach for achieving increased automation in practice. Therefore, we make the case that bridging the gap between theory and practice requires decision-support systems that enable an iterative and interactive workflow
On-site residual prestress assessment for service life estimation of prestressed concrete bridges
No full textIn recent decades, assessing the performance of existing structures has become increasingly crucial, especially as many post-war structures approach the end of their design lifespan. Among these, prestressed concrete bridges are particularly concerning because they are inherently vulnerable to deterioration caused by time-dependent prestress losses. Recent inspections of prestressed concrete bridges with internally grouted tendons have uncovered hidden defects beneath a seemingly intact and robust exterior, raising concerns about their structural integrity. Notable bridge collapses, including the Koror–Babeldaob Bridge (1996), Nanfang’ao Bridge (2019), the Polcevera Viaduct (Morandi bridge, 2018) and Carola Bridge (2024) highlight the critical need for accurately assessing the structural condition of aging bridges. These cases underscore vulnerabilities in prestressing systems and underline key gaps in understanding degradation mechanisms, long-term performance, and failure factors in prestressed concrete structures. Conventional investigation techniques and visual inspections often fail to capture the true condition of these structures, necessitating specialized evaluation methods. As a result, there is a pressing need for reliable, user-friendly, and nondestructive techniques to assess their structural performance throughout their life cycle. Such assessments play a vital role in early diagnostics, helping to prevent cracking and deflections that could jeopardize a bridge’s structural integrity and safety. A major challenge in evaluating the structural performance of existing prestressed concrete bridges is assessing the time-dependent loss of prestress. This loss serves as both an indicator and a warning sign of potential structural deterioration. However, accurately measuring prestress loss is difficult due to uncertainties in material properties, environmental conditions, and long-term degradation processes. Simplified code-conforming models fail to account for the combined effects of environmental wear and fatigue, leading to discrepancies between measured and predicted prestress losses. This study examines various testing methods for estimating residual prestress, highlighting their features and experimental approaches through a case study of the Kalix Bridge, a 66-year-old prestressed box-girder bridge in northern Sweden. This bridge posed unique challenges due to the complexity of its prestress system, the non-homogenous concrete curing process induced by due to multiple construction stages and the long-term deformations at the pendulum joint associated with creep. A numerical model was developed and calibrated using proof-loading test data and material characterization from extracted concrete cores. This updated model was later used to calculate residual prestress, which was then compared with predictions from standard formulations. Advanced probabilistic methods, including Bayesian updating and time-dependent reliability analysis, were also employed to refine residual prestress estimations and improve longterm reliability assessments. These methods allowed for the probabilistic analysis of uncertainties in estimating the service life of bridges, particularly when updating prestress levels retrieved through testing. By incorporating uncertainties related to material properties, environmental conditions, and degradation processes, these approaches enhance the accuracy of predictions about how long a bridge can remain serviceable after prestress updates. This refined approach provided valuable insights for optimizing maintenance strategies and ensuring extended service life and durability of prestressed concrete structures
Engineered Fluorine-Free Electrolytes for Next-Generation Batteries
No full textDue to the successful commercialization of lithium-ion batteries (LIBs), there is a growing interest in developing new battery materials with improved properties. The uneven distribution of natural resources, the low abundance of battery materials in the Earth’s crust, and the growing geopolitical concerns should also be considered and addressed. In this context, alternative battery technologies, such as sodium-ion batteries (SIBs) and lithium metal batteries (LMBs), are getting attention by researchers, due to the low cost of readily available sodium resources and the very high capacity of a lithium metal anode, etc. Conventional electrolytes of any battery technology are today heavily based on fluorinated salts and volatile organic solvents, posing serious safety issues all the way from synthesis to application and recycling. Additionally, the increasing concerns of per- and polyfluoroalkyl substances (PFAS) highlight the urgent demand to explore performant fluorine-free electrolytes, ideally also non-flammable. In this study, novel fluorine-free ionic materials and electrolytes have been designed and their physical and electrochemical properties thoroughly investigated. In the first part (Paper I), fluorine-free “solvent-in-salt” (SIS) sodium electrolytes based on sodium bis(2-(2-ethoxyethoxy)ethyl) phosphate (NaDEEP) salt and tris(2-(2-ethoxyethoxy)ethyl) phosphate (TEOP) solvent are presented. The addition of TEOP increased the electrochemical oxidation stability of the SIS electrolytes and an unusual ionic conductivity behavior is observed – the ionic conductivities of the electrolytes increase with increasing salt concentration. In the second paper (Paper II), a series of new orthoborate-based ionic materials, containing the bis(glycolato)borate (BGB) anion and phosphonium/ammonium cations are prepared and compared with the popular bis(oxalato)borate (BOB) salts. Some of these ionic materials are room temperature ionic liquids (RTILs), while others are organic ionic plastic crystals (OIPCs). The tetrabutylphosphonium bis(glycolato)borate ([P4444][BGB]) OIPC displays much higher decomposition temperature than the structural analogous [P4444][BOB] IL, and multinuclear solid-state NMR spectroscopy indicated weaker cation-anion interactions in phosphonium-based salts than the ammonium-based ones. Given the excellent moisture and thermal stabilities brought by the BGB anion, a family of BGB-based alkali and alkaline metal salts were synthesized and characterized (Paper III). The LiBGB-based electrolytes using dimethyl sulfoxide (DMSO), triethyl phosphate (TEP) and trimethyl phosphate (TMP) have excellent moisture stability, optimal ionic conductivity, better aluminum (Al) passivation and long-term Li plating-stripping performance. Sequentially, the next study (Paper IV) is focused on investigating the effect of additives on the performance of these electrolytes, such as vinylene carbonate (VC), fluoroethylene carbonate (FEC), etc. Finally, in the fifth paper (Paper V), two- and three-component eutectic electrolytes based on pyrrolidinium saccharinate [Pyrr][Sac], lithium saccharinate Li[Sac] and/or [P4444][BGB] salts were created. The physicochemical properties of these salts as well as the Li compatibility and cell performance are thoroughly investigated. Overall, these studies identified several new fluorine-free salts and electrolytes with beneficial properties that can potentially be used in next-generation batteries
Technology advancements in future waste biorefineries: Focus on low carbon fuels and renewable chemicals
No full textTransitioning from fossil fuels to renewable energy sources is essential for combating climate change and minimizing greenhouse gas emissions. Innovative biorefineries are at the forefront of this shift, designed for enhanced productivity and carbon neutrality. These facilities can extract low-carbon fuels and biobased materials from renewable feedstocks, presenting opportunities for diverse product development and low-carbon outputs. Recent advancements in acidogenic and methanogenic biorefineries showcase their potential to produce valuable compounds, including carboxylates, alcohols, and biopolymers while generating fuels like hydrogen and methane. This article explores biorefineries extracting low-carbon fuels and biobased materials from renewable feedstocks, emphasizing advancements in renewable fuel and chemical production. It focuses on acidogenic and methanogenic biorefineries, highlighting synergies in extracting and utilizing compounds such as carboxylates, alcohols, and biopolymers. Additionally, it addresses the production of hydrogen, methane, bioelectricity, and bio-ammonium, emphasising their role in carbon farming and the associated challenges in optimizing these processes for sustainable energy solutions. Validerad;2025;Nivå 2;2025-08-07 (u8);Funder: JSPS KAKENHI (24K11471); Iwatani Foundation for the Promotion of Science and Engineering, Japan;Full text license: CC BY-NC-ND</p
Enhancing Tunnel Fire Safety in Design and Operation: Computational Modeling and Risk Mitigation Strategies for Passenger and Goods Carrier
No full textRoad tunnels need a robust risk management strategy being critical component of modern transportation network. Change in vehicle types with intrinsic hazard source change due to evolution of power sources (H2, EV etc.), tunnels must evolve into intelligent infrastructures to safeguard lives through robust engineering and proactive risk governance mechanism. The risk profile within a road tunnel fluctuates instantaneously based on the types and volumes of vehicles present. Traditional design-stage risk assessments, often grounded in conservative assumptions, fall short in managing such dynamic infrastructure. Advancements in high-performance computing and computer vision technology, a real-time tunnel risk estimation can be achieved. This necessitates a robust methodology for continuous risk quantification, enabling proactive monitoring and timely intervention to manage risk. The primary objective of this research work was to develop dynamic risk estimation framework for road tunnels, forming the basis for a smart tunnel Risk Monitor that evaluates real-time risk based on vehicle types, traffic volume, and hazard potential. Applied to the Bhatan tunnel under simplified traffic assumptions and simulated traffic flow conditions, to derive a correlation between overtaking and severe accident collision probability. The methodology models event progression using an event tree and estimates risk every second over a one-year period. The framework demonstrates scalability across diverse tunnel configurations, vehicle categories, and traffic volumes. As secondary objective, it provided the method to derive the URCL, the Upper Risk Control Limit and ARTL, the Acceptable Risk Threshold Limit for effective risk management of a tunnel and demonstrated the evaluation using the estimated one-year risk profile for Bhatan tunnel. Further, it recommended administrative actions and restrictions that can be initiated triggered once instantaneous risk reaches the URCL and stopped with the restoration of ARTL. Computational fluid dynamics (CFD) simulations were used to estimate peak heat release rates (HRR), aligning closely with results from the Runehamar tunnel fire experiment involving heavy goods vehicles (~200 MW). Simulations were extended to five vehicle categories viz. cars, SUVs, six and ten-wheeler trucks and buses with certain substitute material fire properties like n-heptane as engine oil and mixture of polyvinyl chloride (PVC) & urethane as burnable materials in all vehicles. The observed peak HRR values exceeded significantly for cars, SUV/LMVs (~25 MW vs ~ 5 MW) and bus (~ 200 MW vs ~ 20 MW) those suggested by some of the widely adopted international guidelines. This study therefore proposes revised HRR benchmarks for individual passenger and freight vehicles, intended for use in tunnel design-stage safety and risk assessments. This study introduced and applied a potential two-vehicle collision scenario weighted methodology to estimate the design fire load or peak heat release rate (HRR) for road tunnels. The approach was implemented for five reference vehicle categories in Bhatan to estimate the design basis peak HRR at 81 MW, offering a refined framework for evaluating fire severity under realistic multi-vehicle conditions. This study established the groundwork for the development of a Tunnel Risk Monitoring and Management System (TRMMS) for a smart tunnel. Integrating the proposed risk estimation framework with computer vision and deep learning for vehicle classification, hazard assessment, and speed detection can enable intelligent, real-time risk monitoring
Transcriptomic analysis of two wheat genotypes in the presence of the pathogen Zymoseptoria tritici and the biological control agent Clonostachys rosea
No full textBiological control agents (BCAs) are reported to control plant diseases by directly targeting pathogens or indirectly by enhancing the plant's immune system. It has also been reported that plants exhibit genetic variation for compatibility with BCAs, ultimately impacting biocontrol efficacy. This study explored transcriptomic host responses of two winter wheat genotypes differing for biocontrol efficacy of the fungal BCA C. rosea in controlling septoria tritici blotch disease caused by the fungus Zymoseptoria tritici . Leaves of winter wheat genotypes NGB6704 (high biocontrol efficacy) and NGB348 (low biocontrol efficacy) were spray inoculated with C. rosea , Z. tritici, or their co-inoculation and were harvested at 8 h, 16 h, 32 h, and 40 h for differential gene expression analysis. The results indicate genotype-dependent and time-dependent responses in gene expression towards C. rosea and Z. tritici . Induction of several defense-related genes associated with pattern-triggered immunity and effector-triggered immunity was also observed in interactions with C. rosea exclusively and in the presence of Z. tritici . NGB348 showed a stronger expression of defense-related genes when inoculated with C. rosea at early time points, while NGB6704 exhibited a stronger response at 40 h, emphasizing the differential responses to the presence of C. rosea by the two genotypes, ultimately affecting STB disease development. Cross-referencing differentially expressed genes with genes segregating for C. rosea biocontrol efficacy identified genes associated with receptor-like protein kinases, chitinases, oxalate oxidases, and E3 ubiquitin-protein ligases. Further microscopic and functional validation studies are recommended to determine the intricate nature of plant genotype-specific interactions
Disrupting tree continuity through clearcut forestry can alter the climate sensitivity of future tree growth in northern Sweden
No full textDisrupting tree continuity through clearcut forestry is a widespread management practice across the boreal biome. However, concerns remain that forests regenerated after clearcutting may be more sensitive to climatic fluctuations. We examined how clearcutting affects tree growth responses to weather variability, focusing particularly on the extreme 2018 drought. We collected tree-ring width data from forests in northern Sweden that either were clearcut similar to 60 years prior to the study or never had been clearcut but exposed to past selective logging. We tested whether growth responses to interannual weather variations variables differed between these forest types and assessed how the differences were mediated by soil organic matter, soil temperature stability, and variations in tree age, size, and early growth rates. Forests regenerated after clearcutting showed greater responsive to interannual variation in weather, being more negatively affected by increasing temperature but more positively affected by precipitation. During the 2018 drought, clearcut forests exhibited a mean growth reduction of 19 %, compared to 11 % in non-clearcut forests. The higher drought resistance in non-clearcut forests was primarily associated with greater mean tree age and slower early growth rate. However, as these variables are strongly correlated with clearcutting history, their independent mediation effects are difficult to interpret. Our results suggest that clearcut forestry may increase the sensitivity of regenerating forests to climatic variability. Further research is needed to disentangle the underlying mechanisms and to determine how forest management practices can promote greater climatic resilience in boreal ecosystems
Rapid and scalable combustion synthesis of (Mo2/3Y1/3)2AlC i-MAX as the precursor for vacancy-ordered MXene
No full textFor MXenes to be viable in commercial and industrial applications, their production must rely on processes that are energy-efficient, environmentally sustainable, and scalable. A critical factor influencing this viability is the synthesis route of the parent MAX phase. In this study, we report a novel and rapid approach for synthesizing a chemically ordered MAX phase (i-MAX), specifically the in-plane ordered (Mo2/3Y1/3)2AlC, using self-propagating high-temperature synthesis (SHS) completed in one minute. The target MAX phase yield was estimated using Rietveld refinement to be 73.6% with the main impurity phases identified as Mo3Al2C and YF3. Thermodynamic calculations combined with experimental characterizations indicate that the use of an aluminum-yttrium master alloy played a pivotal role in achieving high synthesis yield by facilitating a sequence of intermediate phase transformations that enhance reaction kinetics and i-MAX formation. This method involves the utilization of Poly(tetrafluoroethylene)- (C2F4)nas a promoter, which enables the formation of volatile fluorides and fluorine-containing intermediates, making the reaction self-sustaining. Etching and delamination of the SHS-produced i-MAX phase, resulted in a vacancy-ordered MXene with the formula Mo4/3CTx, with a yield value twice that obtained using the conventional MAX-phase parent material preparation route. This work demonstrates the method's effectiveness in achieving rapid, straightforward, and energy-efficient synthesis of a diverse range of MAX and i-MAX phases, thereby paving the way for scalable and efficient MXene production. (c) 2025 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Funding Agencies|Science Ministry of Education, Science, Culture and Sports of the Republic of Armenia [23LCG-2F001, 24FP-2B026]; Swedish Research Council; Swedish Foundation for Strategic Research for access to ARTEMI [2021-00171, RIF21-0026]; PLANSEE Composite Materials GmbH [AlY2.3, 2025, DALLE]</p
Digital transformation as a multi-phase process: a longitudinal study of corporate strategy and business unit adaptation
No full textThis study investigates how digital transformation unfolds over time within a multi-business manufacturing firm. Drawing on a longitudinal case study of SweX—a global industrial firm—we trace the dynamics of digital transformation across three empirically derived phases: experimentation, consolidation, and acceleration. Five interrelated patterns shape the process: (1) digital transformation unfolds recursively rather than linearly; (2) tensions arise between corporate strategy and business unit adaptation; (3) monetizing digital innovation remains challenging; (4) structural adjustments are needed to balance stability and change; and (5) temporal asymmetry—misalignments between technology deployment and customer readiness—can hinder digital transformation. We organize these insights around three overarching themes—organizational tension, structural adjustment, and organizational adaptation—developed through iterative analysis across corporate and business unit levels. The study advances process-oriented perspectives on strategy by showing how recursive patterns of tension, structural change, and organizational adaptation drive digital transformation in complex, multi-level firms. Funding Agencies|Vinnova - Sweden's Innovation Agency [2022-00301, 2024-03735]</p
Ore extensions of abelian groups with operators
No full textGiven a set A and an abelian group B with operators in A, in the sense of Krull and Noether, we introduce the Ore group extension B[x;\sigma_B,\delta_B] as the additive group B[x], with A[x] as a set of operators. Here, the action of A[x] on B[x] is defined by mimicking the multiplication used in the classical case where A and B are the same ring. We derive generalizations of Vandermonde's and Leibniz's identities for this construction, and they are then used to establish associativity criteria. Additionally, we prove a version of Hilbert's basis theorem for this structure, under the assumption that the action of A on B is what we call weakly s-unital. Finally, we apply these results to the case where B is a left module over a ring A, and specifically to the case where A and B coincide with a non-associative ring which is left distributive but not necessarily right distributive.CC BY 4.0© 2025 The Author(s)Corresponding author: [email protected] (P. Bäck)</p