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A comparative analysis of functional performance in additively manufactured NiTi, Ti-6Al-4V, and 316L stainless steel architected metastructures
Get PDFAdditive Manufacturing (AM) offers unique capabilities for creating complex designs, such as architected structures, that are typically unattainable through conventional manufacturing methods. Recent advancements in 3D printing of shape memory alloys (SMAs) have enabled the design and development of smart structures capable of recovering their original shape after deformation. This innovation holds immense potential for applications such as biomedical implants and stents, where structures regain their original shape during loading and unloading cycles. This study investigates the functional performance of NiTi-based shape memory lattice structures in comparison to two commonly used commercial alloys: 316L stainless steel and Ti-6Al-4V titanium, both widely utilized in biomedical applications. For that, a lattice design with auxetic behavior and a negative Poisson's ratio was fabricated using the Laser Powder Bed Fusion (LPBF) technique. The samples underwent rigorous quality and performance evaluations, including microstructural analysis and cyclic compression testing to assess mechanical properties and energy dissipation capacity. The results reveal that NiTi samples exhibit distinct superelastic behavior and significantly higher energy dissipation under cyclic compression compared to 316L stainless steel and Ti-6Al-4V alloys. This study underscores the potential of NiTi-based architected metamaterials for achieving superior energy dissipation, positioning them as a promising solution for applications in the medical, aerospace, and automotive industries.</p
Anatomically Accurate Modeling of Spine Movement to Depict the Scoliosis Condition
No full textLittle attention has been paid to how scoliosis movements deviate from intact spines and the consequent response to surgical instrumentation. Embedding such deviations into scoliosis simulation models can significantly improve their predictive capability for surgical outcome and to mitigate complication risks and thus bring more satisfaction to patients and clinicians. Scoliosis models are mainly intact spine models adapted by merely adjusting model parameters to produce scoliotic-like asymmetry, overlooking that the scoliosis condition results in significant deviations of movements. Thus, these adapted models might provide misleading predictive information. This paper aims to uncover the behaviors emerging out of scoliotic spine movements for simulation. A multibody model with micro-scale motion segments was utilized to study movement of nine adolescent idiopathic scoliosis patients. Statistical analysis was used to identify the shared movement behavior and to test their significance in terms of occurrence and their effects on the simulation results and prediction accuracy. Four movement behaviors were uncovered: (1) negligible change of spinal length, (2) bounded rotational displacements, (3) unilateral rotational displacements of certain vertebrae, (4) negligible rotational displacements around inflection vertebrae. Simulation results were improved significantly by incorporating these findings: location and orientation errors of vertebrae from 2.9±2.5 mm to 1.1±0.4 mm and 2.0±1.3° to 1.0±0.4° , respectively, approximation error of spine curvature from 2.1±2.0 mm to 0.6±0.3 mm. Therefore, scoliosis exhibits unique movements, and it is essential that scoliosis models comply for improved predictive capability.</p
When do Lyapunov Subcenter Manifolds become Eigenmanifolds?
Get PDFMulti-body mechanical systems have rich internal dynamics, which can be exploited to formulate efficient control targets. For periodic regulation tasks in robotics applications, this motivated the extension of the theory on nonlinear normal modes to Riemannian manifolds, and led to the definition of Eigenmanifolds. This definition is geometric, which is advantageous for generality within robotics but also obscures the connection of Eigenmanifolds to a large body of results from the literature on nonlinear dynamics. We bridge this gap, showing that Eigenmanifolds are instances of Lyapunov subcenter manifolds (LSMs), and that their stronger geometric properties with respect to LSMs follow from a time-symmetry of conservative mechanical systems. This directly leads to local existence and uniqueness results for Eigenmanifolds. Furthermore, we show that an additional spatial symmetry provides Eigenmanifolds with yet stronger properties of Rosenberg manifolds, which can be favorable for control applications, and we present a sufficient condition for their existence and uniqueness. These theoretical results are numerically confirmed on two mechanical systems with a non-constant inertia tensor: a double pendulum and a 5-link pendulum
Educational design research for relevant & robust scholarship
Get PDFResearch on computing in higher education research has been dominated by studies on things that work (or not). While useful, the field now needs more research on authentic tech-related problems of practice and viable solutions that resolve them. This article describes one such approach: Educational Design Research (EDR). It begins with a brief portrayal of the research we have, and elaborates on the research we need now, before introducing EDR as one way to meet today’s needs. The evolutionary nature of EDR is discussed and multiple illustrations are given before a generic model is presented, together with a detailed example. Challenges are discussed as well as ways to support design researchers in facing these challenges. With the goal of increasing the relevance and robustness of scholarship in our field, the piece concludes with a call for increased use of EDR approaches.</p
Hybrid Schrödinger-Liouville and projective dynamics
Get PDFQuantum dynamics provides the arguably most fundamental example of hybrid dynamics: As long as no measurement takes place, the system state is governed by the Schr\"odinger-Liouville differential equation, which is however interrupted and replaced by projective dynamics at times when measurements take place. We show how this alternatingly continuous and projective evolution can be cast in form of one single differential equation for a refined state space manifold and thus be made amenable to standard port-theoretic analysis and control techniques
Effects of drought experience on farmer decision-making and sustainable water management practices in Salland, the Netherlands
Get PDFEffects of drought experience on farmers’ decisions and water management practices remains poorly understood, particularly in regions where drought is historically uncommon. This paper investigates how farmers’ decisions on sustainable water management practices are influenced by their drought experience. We reviewed the scientific literature on the factors that affect farmers’ decisions and developed a conceptual model on the relationship of drought experience with those factors and the water management practices of farmers. We then applied and refined the model based on empirical data from the Salland region in the Netherlands. Our findings indicate that drought experience affects farmer decision-making through multiple factors, particularly the internal and external adaptive capacity of farmers, as well as belief in climate change and risk perception. The effect of drought experience through these factors is explained by farmers’ former adaptation responses. Furthermore, the experience of severe or frequent droughts results in higher risk perception by farmers. Drought experience influences the implementation of sustainable water management practices with varying levels of contribution to drought resilience. We identify three future research directions to build on our findings. First, it can be tested whether maladaptation is indeed an intervening factor between drought experience and the internal and external adaptive capacity. Second, the conditions that enable structural measures to enhance drought resilience can be investigated, as none of the implemented measures seems to have succeeded in making farmers fully drought resilient. Third, adaptation pathways can be incorporated into the conceptual model to prioritise and combine multiple strategies and the role of different policy instruments in water and agricultural sectors from a long-term perspective.</p
Bond graphs for quantitative fault diagnostics to support Bayesian filtering-based failure prognostics
Get PDFPredictive maintenance has a lot of potential in preventing catastrophic and expensive failures and in optimizing maintenance logistics. Bayesian filters can be used for prognostics as they can update physics-of-failure models, establishing a quantitative relation between asset usage and the remaining useful life. However, such filters require real-time direct condition measurements (e.g. crack length), while in many practical applications, only indirect condition measurements (e.g. vibrations), are available. A quantitative diagnostic algorithm that converts indirect into direct condition measurements is needed to create the required input for Bayesian filters. Such a diagnostic algorithm requires (labeled) degradation data, which are often unavailable for real-world applications. Therefore, simulation models can be helpful to generate synthetic degradation data. This paper proposes to use bond graphs for the generation of synthetic degradation data. Bond graphs are especially helpful due to their modularity and reusability. The creation of synthetic degradation data is demonstrated on a case study concerning outer race damage of a rolling-element bearing. An existing algorithm for fault size estimation is applied to the synthetic data generated by bond graphs. The fault size, derived by the quantitative diagnostics algorithm, is implemented in a prognostic framework based on a Bayesian filter. It is shown that the bond graph accurately creates synthetic failure data. Furthermore, it is demonstrated that existing diagnostic methods are insufficiently accurate to represent all damage shapes in bearings while bond graphs create vibration data for specific fault shapes. Therefore, bond graphs can improve quantitative diagnostics
SiamCircle:Trajectory Representation Learning in Free Settings
No full textTrajectory representation learning (TRL) is an intermediate step in handling trajectory data to realize various downstream machine-learning tasks. While most previous TRL research focuses on modeling structured movements in large-scale urban spaces (e.g., cars or pedestrians on streets), this paper focuses on a more challenging scenario of modeling free movement in small-scale social spaces (e.g., children playing in a schoolyard). We present a TRL model, SiamCircle, to process raw trajectories without additional feature extraction to prevent information loss. SiamCircle adopts a Siamese network with Circle Loss to learn trajectory embeddings. Furthermore, SiamCircle employs a data augmentation process to enable self-supervised learning and enrich the input data to address the limited access to high-quality data and ground truth. We evaluate the performance of SiamCircle in downstream tasks using trajectory ranking and clustering performance via seven evaluation metrics collectively. Using an ablation study, we explored the impact of different loss functions on the model’s performance. Accordingly, we selected a 2-D convolutional design with Circle Loss as the best-performing model. In a comparative study, we compared our model against three other baselines. We observed up to 19% improvements in trajectory ranking tasks and achieved the highest average rank in supervised clustering tasks.</p
Leadership for Student Participation in Data-Use Professional Learning Communities
Get PDFStudent participation in educational decision making, for example, through data-informed decision making, can have a positive effect on student well-being, engagement, and performance. Teachers play a crucial role in student participation, and leadership is a main factor influencing teacher professional development, which can lead to improved experiences and outcomes for students. In this study, we aimed to combine the benefits associated with data-informed decision making with those associated with Professional Learning Communities. Moreover, we included students as PLC participants. This study therefore focuses on the question how school leaders can support teachers in connection with student participation in data-use PLCs. Based on previous research, we used leadership core functions needed for successful PLCs to describe school leaders’ roles in an approach to student participation that combines the pedagogical analysis model and Shier’s model for student participation. School leaders and teachers from five schools participating in the previous study were interviewed to describe school leaders’ roles. The findings show what concrete school leader activities can support teachers in connection with student participation in data-use PLCs and what implications this has for practice, policy, and further research.</p
Factors influencing the implementation of a teacher professional development program to improve teaching quality
Get PDFIn this study, we examined why a Teacher Professional Development (TPD) program, designed to support teachers in using students’ perceptions of teaching quality (SPTQ) data, faced significant implementation challenges in 17 secondary schools in Chile. Despite voluntary participation and initial interest, 15 of the 17 schools dropped out within 2–3 months of starting the program. Through 12 semi-structured interviews with professional learning community coordinators from nine schools, we investigated four key attributes of the TPD program to understand implementation challenges: its added value, compatibility, clarity, and tolerance. While coordinators valued several aspects of the program (including its structured manual, evidence-based teaching strategies, and integration of SPTQ data) significant implementation barriers emerged. Time constraints, lack of technological infrastructure, and insufficient organizational routines made the implementation of the TPD program too burdensome for most schools. We discuss how compatibility between TPD programs and schools’ existing structures and routines acts as a critical bottleneck that can prevent successful implementation, even when participants see value in the program. This study provides important insights into the conditions necessary for successful TPD implementation in a global south country.</p