VTT Research System
Not a member yet
161399 research outputs found
Sort by
Feasibility of evacuation from the front line using unmanned ground vehicles during platoon-level defensive combat
No full textIntroduction Advancements in technology and intelligence, as well as deliberate targeting of medical personnel and vehicles, have made casualty extraction increasingly hazardous. The Russo-Ukrainian War has further demonstrated that the rapid development of unmanned technologies may also enable novel approaches. Although some of these systems have been deployed, reporting on their performance is scarce and understandably incomplete, which limits their evidence-based and effective integration with fighting forces. This paper addresses this gap by presenting preliminary findings on potential ranges of evacuation unmanned ground vehicles (UGVs) utilisation. Methods A virtual simulation experiment was conducted, where a platoon defended against a mechanised infantry company. The experiment was a repeated military exercise with different groups of participants. The defending force had evacuation UGVs, which were placed close behind the defensive line. The aim was to determine whether UGVs could survive long enough to support evacuation and whether evacuation could be carried out before the conflict ended. Furthermore, the availability of UGVs and the likelihood that an evacuation attempt could avoid enemy interference were assessed. The experiment involved 470 participants divided into 11 groups. Each participant completed four combat scenarios. Players of each group switched sides and environments. In total, 44 instances of skirmishes were fought in a virtual simulation environment. Results The simulation results indicated UGV loss rate of 53%. Evacuations were attempted in 45% of skirmishes. Furthermore, 81% of initiated evacuation attempts were successful. Conclusions The experiment provided estimates of evacuation UGV loss rates near the defence line amid active conflict. It also offered evidence on the feasibility of initiating evacuation before the active conflict had fully ceased, and the likelihood of the moving evacuation vehicle encountering enemy fire. These findings can guide decisions on whether the risk of losing small evacuation vehicles and their equipment is acceptable when deployed near front lines.</p
Extreme fitness: Applying ecophysics to reduce human stress in everyday extreme environments
No full textIt has been proposed that ergonomics and human factors (EHF) can be advanced by moving beyond old methodologies, by strengthening theoretical basis, and by making more use of artificial intelligence. Here, with the example of human remote operation of robots, i.e., teleoperation, it is argued that progress towards realising proposals for advancing EHF can be made by increasing reference to ecophysics. That is by increasing reference to science concerned with interactions between ecological systems and physical laws. In this document, human stress associated with remote operations work is situated in the broader context of extreme work environments. Those being environments that many people experience every workday, such as typical factories and offices, which are far from the natural environments in which humans evolved. With reference to ecological fitness, morphological fitness, and tripartite entropy, it is explained how application of ecophysics in EHF has potential to reduce human work stress
Large Language Model hallucination mitigation in three industrial use cases
No full textLarge-language models (LLMs) can produce factually false or ungrounded information. This occurs when the language model, being fundamentally a statistical model, generates inaccurate or non-existent information with high confidence in response to a given query. This phenomenon is particularly dangerous in safety-critical systems and involves risks when LLMs are used to access or control hardware such as robots, sensors, and other internet-of-things (IoT) applications. Additionally, in automation-rich industrial environments, effective human-machine cooperation depends on maintaining a shared and adaptive understanding of complex situations. Distributed Situation Awareness (DSA) provides a framework for how awareness emerges collectively across networks of operators, robots, sensors, digital interfaces, and LLM based artificially intelligent systems. LLMs can fuse fragmented data streams into coherent, actionable context, enabling Extended Reality (XR) technologies to strengthen DSA by embedding digital cues into physical workflows. While this process improves coordination and adaptability, it also makes reliable and verifiable model outputs essential, as hallucinations can erode operator trust and compromise distributed decision-making. Therefore, mitigation of hallucinations becomes essential for sustaining stable human–AI teaming. We present three industrial projects where LLMs are at the forefront, highlighting practical approaches for hallucination mitigation and demonstrating a transition from online to offline model. Scope is to demonstrate through architectural means how established mitigation mechanisms can be used in industrial systems.</p
Future energy scenarios with renewables and flexibilities in distribution grids – National case study in France
No full textMedium and low voltage distribution grids are at the core of the energy transition as they are expected to host a large share of renewables and flexible resources. Their modeling within decarbonization pathways is then of great importance in providing realistic future energy scenarios. This paper investigates different scenarios at the French national scale up to 2050 while varying the electricity demand, renewables installed in both transmission and distribution grids, and the considered flexibility technologies. The methodology relies on coupling a long-term energy model (POLES) and an open-source short-term optimization framework (Backbone). POLES produces long-term decarbonization scenarios, while Backbone enables the optimization of the power system. Technical and financial impacts are studied through ten scenarios regarding produced energy, installed capacities, and investment costs. The results highlight the importance of the load demand modeling assumptions, even raising the question of the feasibility of high-demand scenarios. Also, results show that demand-side flexibility can significantly reduce the requirements in conventional storage technologies (up to 98 %). Distributed flexibilities, such as electric vehicle smart charging, are especially effective. Considering multiple types of distribution grids allows, in the end, to show that installing renewable generation at the transmission or distribution level only moderately influences global costs, with a minor advantage for centralization to limit reverse flows on transformers. The paper concludes with a comparison with other scenarios (drawn from up-to-date literature) and a discussion of the environmental footprint of these scenarios, both in terms of mineral resource consumption (raw materials) and land footprint.</p
Coupling of shrinking core and Eulerian-Eulerian models for chemical looping combustion
No full textOne of the main barriers to the implementation of chemical looping combustion (CLC) on an industrial scale is the lack of knowledge about its operation at such scales. As a first step towards modeling industrial CLC devices, a consistent coupling between the shrinking core model (SCM) and the Eulerian-Eulerian multiphase framework with multicomponent phases was derived. This coupling enforces the constant volume assumption of a solid particle and allows for simple and consistent control of the oxygen transfer capacity. The derived approach was then applied to the chemical kinetic model of ilmenite redox reactions, which was sourced from the literature and was based on thermogravimetric analysis (TGA) data. Important corrections were made to the kinetic model parameters to ensure consistency with the present methodology, and the result was verified using a zero-dimensional TGA simulation setup. The methodology was further validated using experimental data from the literature for a laboratory-scale batch fluidized bed reactor. Three-dimensional simulations and an analytical one-dimensional quasi-steady-state model, derived on the basis of the coupling, have shown very close results to each other. However, as also previously observed in the literature, the conversion rates of H2 were severely underestimated by the TGA-based kinetic model. Finally, the developed approach was applied to a 300 W CLC reactor, previously experimentally studied at Chalmers University. The agreement with the experimental data was reasonably good, but the reactivity of H2 was higher than that reported in the experiments. The chemistry model source code and simulation configurations are made openly available.</p
CeOx-functionalized Pd nanoparticles on single-walled carbon nanotubes for alkaline hydrogen oxidation reaction
No full textThe sluggish kinetics of hydrogen oxidation reaction (HOR) in alkaline electrolytes highlight the strong need to develop next-generation catalyst materials for anion-exchange membrane fuel cells (AEMFC) anodes. In this study, CeOx is sequentially deposited on Pd nanoparticles supported on single-walled carbon nanotubes (SWNT) via atomic layer deposition (ALD). The obtained Pd@CeOx SWNT16 ALD cycles catalyst shows an excellent alkaline HOR performance with a specific exchange current of 166 mA mg−1Pd. This is three times higher than the commercially available Pd catalyst and the highest among reported Pd/CeOx catalyst materials with different CeOx overlayer coverages. By combining the X-ray diffraction, X-ray photoelectron spectroscopy, X-ray absorption spectroscopy and high-resolution scanning transmission electron microscopy, we confirm that the activity improvement is due to the highly conductive SWNT support enabling the fabrication of high surface area Pd clusters and CeOx overlayer. These methods reveal that the oxidation state of Ce is varying from Ce3+ to Ce4+ in relation to the CeOx overlayer thickness and the number of ALD cycles. Density functional theory calculations show that the presence of Ce/CeOx increases the diversity and population of Pd active sites with improved activity in its vicinity leading to enhanced overall catalytic performance. Moreover, this work provides a new perspective to develop highly active alkaline HOR catalysts for AEMFC
Depolymerisation of γ-Valerolactone Organosolv Lignins with Unsupported Molybdenum-Based Catalysts
No full textLignin is an attractive feedstock for a wide variety of applications ranging from aromatic chemicals and transportation fuels to resins and coatings. Emerging biorefinery concepts, like the organosolv process, enable the separation of all the lignocellulose components, and moreover, produce lignins of high quality and purity susceptible to valorisation by depolymerisation. In this work, we focus on the depolymerisation of lignins obtained by γ-valerolactone (GVL) organosolv fractionation of four biomass feedstocks, eucalyptus, white birch, sugarcane bagasse and Scots pine. We demonstrate that lignins extracted with the GVL process are depolymerised using unsupported molybdenum-based catalysts under reductive conditions in supercritical ethanol. As a result, over 90% yields of low-molecular-weight lignin oils are obtained with minimal char formation, yields of the aromatic monomers being 7–16 wt%. Furthermore, the design of experiments method is used to analyse the effect of depolymerisation conditions, catalyst, hydrogen loading and temperature, on the yields and properties of the product fractions. Notably, we show that the properties of the lignin oils and monoaromatics can be tuned towards the targeted application by modifying the depolymerisation conditions.</p
Extreme fitness: Applying ecophysics to reduce human stress in everyday extreme environments
No full textIt has been proposed that ergonomics and human factors (EHF) can be advanced by moving beyond old methodologies, by strengthening theoretical basis, and by making more use of artificial intelligence. Here, with the example of human remote operation of robots, i.e., teleoperation, it is argued that progress towards realising proposals for advancing EHF can be made by increasing reference to ecophysics. That is by increasing reference to science concerned with interactions between ecological systems and physical laws. In this document, human stress associated with remote operations work is situated in the broader context of extreme work environments. Those being environments that many people experience every workday, such as typical factories and offices, which are far from the natural environments in which humans evolved. With reference to ecological fitness, morphological fitness, and tripartite entropy, it is explained how application of ecophysics in EHF has potential to reduce human work stress
Anisotropic plasticity and damage of additively manufactured 316L stainless steel by multiscale approach
No full textStainless steel 316L produced by laser powder bed fusion (L-PBF) technique exhibits distinctly patterned microstructures due to directional rapid cooling of successive layers. Thus, its tensile properties are highly anisotropic depending on applied build strategies that often led to inferior performance compared to conventional 316L steel. In this work, a multiscale modeling approach was proposed for more precisely describing effects of complex printed microstructure characteristics on local and overall deformation behaviors of the steel. Micro-scale models incorporated grain morphologies and crystallographic textures developed in different melt pools. Hereby, the strain gradient crystal plasticity (CP) model was used to thoroughly reveal anisotropic stress-strain responses which were primarily driven by crystallographic features. Subsequently, a meso-scale model was employed to elucidate the heterogeneous deformation occurring at the melt pool boundaries, particularly in relation to the specified scanning patterns. Homogenized stress-strain properties of each meso-scale region were obtained from the micro-scale models in conjunction with the Hill48 yield criterion. Furthermore, the Hosford-Coulomb ductile damage model was defined on the meso-scale for representing crack initiations at crucial sites of the melt pools. The model showed that the grain configurations of 45°/0°/45° and −90°/0°/90° in melt pools strongly governed the anisotropic strain hardening behavior of printed samples. Local stress incompatibilities induced by grain and melt pool arrangements according to the defined scanning strategies resulted in different strain localizations and following damages. The approach can further serve as a framework for 3D printed material designs requiring more accurate microstructure-properties relationships.</p
Robot arm control based on online resolution of nonlinear equation systems using novel matrix-pseudoinverse-free neurodynamics
No full textRobot arm control plays a pivotal role in modern industrial automation. Designing a controller without matrix-pseudoinverse computation for robot arms from the acceleration-layer control perspective is a challenging topic. In this article, based on the temporal-variant nonlinear equation system (TVNES) problem, we propose a novel acceleration-layer TVNES (AL-TVNES) problem. By constructing an output function and an energy function, and applying twice Zhang neurodynamics (ZN) design formula, a new matrix-pseudoinverse-free acceleration-layer ZN (MPF-ALZN) controller is proposed. The controller effectively avoids the complicated computation of the temporal-variant matrix pseudoinverse, thereby reducing computational complexity. In addition, theoretical analyses and numerical experiments show the convergence and robustness of the MPF-ALZN controller. Finally, the proposed MPF-ALZN controller is successfully applied to the control of the Kinova Jaco2, Franka Emika Panda, and Kinova Gen3 robot arms, with the tracking errors between the desired paths and the actual trajectories being below 0.01 mm, which validates the efficiency of the proposed controller. Through various experiments in MATLAB, CoppeliaSim, and physical platforms, the high tracking accuracy and robustness of the MPF-ALZN controller are confirmed, indicating its practicality.</p