Direct additive manufacturing of melt growth Al2O3-ZrO2 functionally graded ceramics by laser directed energy deposition

Functionally graded ceramics (FGC), which combine properties of different ceramics in one part, usually have better comprehensive function and structural efficiency. In this study, four different gradient transition Al₂O₃-ZrO₂ FGC samples were prepared by laser directed energy deposition (LDED) method. The results show that there is an obvious interface in direct transition sample. The transition section bears tensile stress caused by difference of thermophysical properties of materials, resulting in significant longitudinal cracks. Element transition in interface region shows a step sharp transition. The direct transition sample shows intergranular fracture and the bonding strength is very low. Gradient transition mode can effectively suppress cracks, and avoid the step transition of microstructure and elements. Elements, microhardness of 25, 20 wt% FGC samples realized a nearly linear smooth transition. The interface fracture of FGC samples changed to transgranular fracture, bonding strength was significantly improved, and the maximum flexural strength reached 160.19 MPa.     

How to accelerate green technology diffusion? Directed technological change in the presence of coevolving absorptive capacity

The time window for effective climate change mitigation is closing. Technological change needs to be accelerated to limit global warming to a manageable level. Path dependence of technological change is one explanation for sluggish diffusion of green technologies. Firms acquire capital that differs by technology type and build up type-specific technological know-how needed to use capital efficiently. Path dependence emerges from cumulative knowledge stocks manifested in the productivity of supplied capital and firms’ capabilities. Increasing returns arise from induced innovation feedbacks and learning by doing. Relatively lower endowments with technological knowledge are a barrier to diffusion for new technologies. This paper shows how the evolution of relative stocks of technological knowledge explains different shapes of diffusion curves. Using an eco-technology extension of the macroeconomic agent-based model Eurace@unibi, it is shown how the effectiveness of different climate policies depends on the type and strength of diffusion barriers. Environmental taxes can outweigh lower productivity and subsidies perform better if lacking capabilities hinder firms to adopt a sufficiently mature technology.     

Control of self-assembly in micro- and nano-scale systems

Control of self-assembling systems at the micro- and nano-scale provides new opportunities for the engineering of novel materials in a bottom-up fashion. These systems have several challenges associated with control including high-dimensional and stochastic nonlinear dynamics, limited sensors for real-time measurements, limited actuation for control, and kinetic trapping of the system in undesirable configurations. Three main strategies for addressing these challenges are described, which include particle design (active self-assembly), open-loop control, and closed-loop (feedback) control. The strategies are illustrated using a variety of examples such as the design of patchy and Janus particles, the toggling of magnetic fields to induce the crystallization of paramagnetic colloids, and high-throughput crystallization of organic compounds in nanoliter droplets. An outlook of the future research directions and the necessary technological advancements for control of micro- and nano-scale self-assembly is provided.     

Distributed adaptive neural networks leader-following formation control for quadrotors with directed switching topologies

The leader-following formation problem is discussed for a team of quadrotors under directed switching topologies. To obtain a more general dynamic model, we describe the quadrotor system in a non-affine pure-feedback form with mismatched unknown nonlinearities. By employing an adaptive neural networks state observer to approximate the unknown nonlinear functions and to reconstruct the immeasurable inner states, we propose a novel distributed output feedback formation control protocol with the backstepping method combining with the dynamic surface control technique. From the Lyapunov stability theorem, all signals in the closed-loop formation system are proven to be cooperatively semiglobally uniformly ultimately bounded for any given bounded initial conditions. Finally, we proved that we verify the performance of the proposed formation control approach by a simulation study.     

Alloy design via additive manufacturing: Advantages,challenges, applications and perspectives

Additive manufacturing (AM) has rapidly changed both large- and small-scale production environments across many industries. By re-envisioning parts from the ground up, not limited to the challenges presented by traditional manufacturing techniques, researchers and engineers have developed new design strategies to solve large-scale materials and design problems worldwide. This is particularly true in the world of alloy design, where new metallic materials have historically been developed through tedious processes and procedures based primarily on casting methodologies. With the onset of directed energy deposition (DED) and powder bed fusion (PBF)-based AM, new alloys can be innovated and evaluated rapidly at a lower cost and considerably shorter lead time than has ever been achieved. This article details the advantages, challenges, applications, and perspectives of alloy design using primarily laser-based AM. It is envisioned that researchers in industry and academia can utilize this work to design new alloys leveraging metallic AM processes for various current and future applications.     

针对RSA-CRT数字签名的光故障攻击研究

通过研究密码芯片SRAM存储单元构造,利用激光改变进行运算的SRAM存储单元的逻辑状态,分析光注入对SRAM存储单元的影响。以Montgomery乘的 RSA－CRT数字签名算法为攻击对象,分析其算法的实现过程和故障注入机理。针对密码芯片实现的8位RSA－CRT签名算法,使用半导体激光作为注入光源,搭建光注入实验平台,在计算Sq时刻进行故障注入,从而得到故障签名,通过分析故障签名与N的关系,成功的获得了大素数q,验证了光故障攻击的有效性。     

Comparing the expressiveness of downward fragments of the relation algebra with transitive closure on trees

Motivated by the continuing interest in the tree data model, we study the expressive power of downward navigational query languages on trees and chains. Basic navigational queries are built from the identity relation and edge relations using composition and union. We study the effects on relative expressiveness when we add transitive closure, projections, coprojections, intersection, and difference; this for Boolean queries and path queries on labeled and unlabeled structures. In all cases, we present the complete Hasse diagram. In particular, we establish, for each query language fragment that we study on trees, whether it is closed under difference and intersection.     

GPR target detection using a neural network classifier designed by a multi-objective genetic algorithm

Ground Penetrating Radar (GPR) is an electromagnetic sensing technology employed for localization of underground utilities, pipes, and other types of objects. The radargrams typically obtained have a high dimensionality, containing a number of signatures with hyperbolic pattern shapes, and can be processed to retrieve information about the target’s locations, depths and material type of underground soil. The classical Hough Transform approach used to reconstruct these hyperbola shapes is computationally expensive, given the large dimensionality of the radargrams. In literature, several approaches propose to first approximate the location of hyperbolas to small segments through a classification stage, before applying the Hough transform over these segments. However, the published classifiers designed for this task present a relatively complex architecture.Aiming at an improved target localization, we propose an alternative classification methodology. The goal is to classify windows of GPR radargrams into two classes (with or without target) using a neural network radial basis function (RBF), designed via a multi-objective genetic algorithm (MOGA). To capture samples’ fine details, high order statistic cumulant features (HOS) were used. Feature selection was performed by MOGA, with an optional prior reduction using a mutual information (MIFS) approach. The obtained results demonstrate improvement of the classification performance when compared with other models designed with the same data and are among the best results available in the literature, albeit the large reduction in classifier complexity.     

异构分布式系统中一种新型主副版本调度算法

针对异构分布式系统中处理器数量相对较少时优先级约束条件带来的副版本调度易失败问题，提出一种新型高可靠性主副版本调度算法（HRPB）。任务模型以有向无环图（DAG）表示，该算法共计调度主、副两个版本的任务。在任务优先级排序阶段，根据任务执行时间及截止时限来制定新指标平均最晚开始时间（ALST）进行排序；在任务处理器分配阶段，采取多一重备份策略以解决处理器数量相对较少时优先级约束条件带来的副版本调度易失败问题，并且改进了副版本调度时的可靠性指标计算方法。通过随机生成DAG图进行算法仿真测试，实验结果表明，HRPB比eFRD具有更优的副版本调度成功率、更高的系统可靠性。     

Leader-following consensus for a class of second-order nonlinear multi-agent systems

This paper deals with the leader-following consensus problem for a class of multi-agent systems with nonlinear dynamics and directed communication topology. The control input of the leader agent is assumed to be unknown to all follower agents. A distributed adaptive nonlinear control law is constructed using the relative state information between neighboring agents, which achieves leader-following consensus for any directed communication graph that contains a spanning tree with the root node being the leader agent. Compared with previous results, the nonlinear functions are not required to satisfy the globally Lipschitz or Lipschitz-like condition and the adaptive consensus protocol is in a distributed fashion. A numerical example is given to verify our proposed protocol.