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1. Reusable Entry Vehicle Trajectory Optimization Using Multiple-Domain Radau Collocation

   https://doi.org/10.2514/6.2023-1168  

   Byczkowski, Cale A.; Rao, Anil V. (January 2023, American Institute of Aeronautics and Astronautics)

   The trajectory optimization of a reusable launch vehicle entry is studied. The objective is to maximize the crossrange during atmospheric entry subject to a constraint on the stagnation point heating rate. The problem is solved by partitioning the domain of the independent variable into multiple subdomains such that each subdomain consists of a segment where the heating rate constraint is either active or inactive. Additional necessary conditions for optimality are enforced in segments where the heating rate constraint is active. A multiple-domain Legendre-Gauss-Radau direct collocation method is then used to solve the partitioned problem. Key features of the stagnation point heating rate constraint are presented, and it is observed that the aforementioned approach is capable of solving the problem under consideration more accurately than traditional direct collocation methods. 

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2. A Method for Constraint Inference Using Pose and Wrench Measurements

   https://doi.org/arXiv:2010.15916  

   Subramani, Guru; Hagenow, Michael; Gleicher, Michael; Zinn, Michael (October 2020, ArXivorg)

   null (Ed.)

   Many physical tasks such as pulling out a drawer or wiping a table can be modeled with geometric constraints. These geometric constraints are characterized by restrictions on kinematic trajectories and reaction wrenches (forces and moments) of objects under the influence of the constraint. This paper presents a method to infer geometric constraints involving unmodeled objects in human demonstrations using both kinematic and wrench measurements. Our approach takes a recording of a human demonstration and determines what constraints are present, when they occur, and their parameters (e.g. positions). By using both kinematic and wrench information, our methods are able to reliably identify a variety of constraint types, even if the constraints only exist for short durations within the demonstration. We present a systematic approach to fitting arbitrary scleronomic constraint models to kinematic and wrench measurements. Reaction forces are estimated from measurements by removing friction. Position, orientation, force, and moment error metrics are developed to provide systematic comparison between constraint models. By conducting a user study, we show that our methods can reliably identify constraints in realistic situations and confirm the value of including forces and moments in the model regression and selection process. 

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3. How barriers become invisible: Children are less sensitive to constraints that are stable over time

   https://doi.org/10.1111/desc.13496  

   Amemiya, Jamie; Heyman, Gail D; Walker, Caren M (July 2024, Developmental Science)

   Abstract When making inferences about the mental lives of others (e.g., others’ preferences), it is critical to consider the extent to which the choices we observe are constrained. Prior research on the development of this tendency indicates a contradictory pattern: Children show remarkable sensitivity to constraints in traditional experimental paradigms, yet often fail to consider real‐world constraints and privilege inherent causes instead. We propose that one explanation for this discrepancy may be that real‐world constraints are often stable over time and lose their salience. The present research tested whether children (N = 133, 5‐ to 12‐year‐old mostly US children; 55% female, 45% male) becomelesssensitive to an actor's constraints after first observing two constrained actors (Stable condition) versus after first observing two actors in contexts with greater choice (Not Stable condition). We crossed thestabilityof the constraint with thetypeof constraint: either the constraint was deterministic such that there was only one option available (No Other Option constraint) or, in line with many real‐world constraints, the constraint was probabilistic such that therewasanother option, but it was difficult to access (Hard to Access constraint). Results indicated that children in the Stable condition became less sensitive to the probabilistic Hard to Access constraint across trials. Notably, we also found that children's sensitivity to constraints was enhanced in the Not Stable condition regardless of whether the constraint was probabilistic or deterministic. We discuss implications for children's sensitivity to real‐world constraints. Research HighlightsThis research addresses the apparent contradiction that children are sensitive to constraints in experimental paradigms but are ofteninsensitiveto constraints in the real world.One explanation for this discrepancy is that constraints in the real world tend to be stable over time and may lose their salience.When probabilistic constraints (i.e., when a second option is available but hard to access) are stable, children become de‐sensitized to constraints across trials.First observing contexts with greater choice increases children's sensitivity to both probabilistic and deterministic constraints. 

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4. Energy-Constrained Scheduling for Weakly Hard Real-Time Systems Using Standby-Sparing

   https://doi.org/10.1145/3631587  

   Niu, Linwei; Rawat, Danda B; Musselwhite, Jonathan; Gu, Zonghua; Deng, Qingxu (November 2023, ACM Transactions on Design Automation of Electronic Systems)

   For real-time embedded systems, QoS (Quality of Service), fault tolerance, and energy budget constraint are among the primary design concerns. In this research, we investigate the problem of energy constrained standby-sparing for both periodic and aperiodic tasks in a weakly hard real-time environment. The standby-sparing systems adopt a primary processor and a spare processor to provide fault tolerance for both permanent and transient faults. For such kind of systems, we firstly propose several novel standby-sparing schemes for the periodic tasks which can ensure the system feasibility under tighter energy budget constraint than the traditional ones. Then based on them integrated approachs for both periodic and aperiodic tasks are proposed to minimize the aperiodic response time whilst achieving better energy and QoS performance under the given energy budget constraint. The evaluation results demonstrated that the proposed techniques significantly outperformed the existing state of the art approaches in terms of feasibility and system performance while ensuring QoS and fault tolerance under the given energy budget constraint. 

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5. Efficient WENO-Based Prolongation Strategies for Divergence-Preserving Vector Fields

   https://doi.org/10.1007/s42967-021-00182-x  

   Balsara, Dinshaw S.; Samantaray, Saurav; Subramanian, Sethupathy (May 2022, Communications on Applied Mathematics and Computation)

   Abstract Adaptive mesh refinement (AMR) is the art of solving PDEs on a mesh hierarchy with increasing mesh refinement at each level of the hierarchy. Accurate treatment on AMR hierarchies requires accurate prolongation of the solution from a coarse mesh to a newly defined finer mesh. For scalar variables, suitably high-order finite volume WENO methods can carry out such a prolongation. However, classes of PDEs, such as computational electrodynamics (CED) and magnetohydrodynamics (MHD), require that vector fields preserve a divergence constraint. The primal variables in such schemes consist of normal components of the vector field that are collocated at the faces of the mesh. As a result, the reconstruction and prolongation strategies for divergence constraint-preserving vector fields are necessarily more intricate. In this paper we present a fourth-order divergence constraint-preserving prolongation strategy that is analytically exact. Extension to higher orders using analytically exact methods is very challenging. To overcome that challenge, a novel WENO-like reconstruction strategy is invented that matches the moments of the vector field in the faces, where the vector field components are collocated. This approach is almost divergence constraint-preserving, therefore, we call it WENO-ADP. To make it exactly divergence constraint-preserving, a touch-up procedure is developed that is based on a constrained least squares (CLSQ) method for restoring the divergence constraint up to machine accuracy. With the touch-up, it is called WENO-ADPT. It is shown that refinement ratios of two and higher can be accommodated. An item of broader interest in this work is that we have also been able to invent very efficient finite volume WENO methods, where the coefficients are very easily obtained and the multidimensional smoothness indicators can be expressed as perfect squares. We demonstrate that the divergence constraint-preserving strategy works at several high orders for divergence-free vector fields as well as vector fields, where the divergence of the vector field has to match a charge density and its higher moments. We also show that our methods overcome the late time instability that has been known to plague adaptive computations in CED. 

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