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  1. Abstract

    The direct selective laser sintering (SLS) process was successfully demonstrated for additive manufacturing of high-entropy carbide ceramics (HECC), in which a Yb fiber laser was employed for ultrafast (in seconds) reactive sintering of HECC specimens from a powder mixture of constitute monocarbides. A single-phase non-equiatomic HECC was successfully formed in the 4-HECC specimen with a uniform distribution of Zr, Nb, Hf, Ta, and C. In contrast, a three-layer microstructure was formed in the 5-HECC specimen with five metal elements (Zr, Nb, Hf, Ta and Ti), consisting of a TiC-rich top layer, a Zr–Hf–C enriched intermediate layer, and a non-equiatomic Zr–Ta–Nb–Hf–C HECC layer. Vickers hardness of 4- and 5-HECC specimens were 22.2 and 21.8 GPa, respectively, on the surface. These findings have important implications on the fundamental mechanisms governing interactions between laser and monocarbide powders to form a solid solution of HECCs during SLS.

    Graphical abstract

  2. Free, publicly-accessible full text available August 1, 2023
  3. Free, publicly-accessible full text available July 25, 2023
  4. In this paper, we propose a convex optimization approach to chance-constrained drift counteraction optimal control (DCOC) problems for linear systems with additive stochastic disturbances. Chance-constrained DCOC aims to compute an optimal control law to maximize the time duration before the probability of violating a prescribed set of constraints can no longer be maintained to be below a specified risk level. While conventional approaches to this problem involve solving a mixed-integer programming problem, we show that an optimal solution to the problem can also be found by solving a convex second-order cone programming problem without integer variables. We illustrate the application of chance-constrained DCOC to an automotive adaptive cruise control example.
  5. Abstract

    As femtosecond (fs) laser machining advances from micro/nanoscale to macroscale, approaches capable of machining macroscale geometries that sustain micro/nanoscale precisions are in great demand. In this research, an fs laser sharp shaping approach was developed to address two key challenges in macroscale machining (i.e. defects on edges and tapered sidewalls). The evolution of edge sharpness (edge transition width) and sidewall tapers were systematically investigated through which the dilemma of simultaneously achieving sharp edges and vertical sidewalls were addressed. Through decreasing the angle of incidence (AOI) from 0° to −5°, the edge transition width could be reduced to below 10µm but at the cost of increased sidewall tapers. Furthermore, by analyzing lateral and vertical ablation behaviors, a parameter-compensation strategy was developed by gradually decreasing the scanning diameters along depth and using optimal laser powers to produce non-tapered sidewalls. The fs laser ablation behaviors were precisely controlled and coordinated to optimize the parameter compensations in general manufacturing applications. The AOI control together with the parameter compensation provides a versatile solution to simultaneously achieve vertical sidewalls as well as sharp edges of entrances and exits for geometries of different shapes and dimensions. Both mm-scale diameters and depths were realized with dimensional precisionsmore »below 10µm and surface roughness below 1µm. This research establishes a novel strategy to finely control the fs laser machining process, enabling the fs laser applications in macroscale machining with micro/nanoscale precisions.

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  6. Drift counteraction optimal control (DCOC) aims at optimizing control to maximize the time (or a yield) until the system trajectory exits a prescribed set, which may represent safety constraints, operating limits, and/or efficiency requirements. To DCOC problems formulated in discrete time, conventional approaches were based on dynamic programming (DP) or mixed-integer programming (MIP), which could become computationally prohibitive for higher-order systems. In this paper, we propose a novel approach to discrete-time DCOC problems based on a nonlinear programming formulation with purely continuous variables. We show that this new continuous optimization-based approach leads to the same exit time as the conventional MIP-based approach, while being computationally more efficient than the latter. This is also illustrated by numerical examples representing the drift counteraction control for an indoor airship.