Sintering Preparation of 15 wt% Cr Cast Iron as well as Its Mechanical Properties and Impact Abrasive Wear

15 wt% Cr sintered High Chromium Cast Iron (HCCI) with full density was successfully prepared by Super-solidus Liquid Phase Sintering (SPLS) technique, with water atomized 15 wt% Cr high chromium cast iron powder as initial materials. Its densification behavior and microstructure evolution in SPLS process and mechanical properties were investigated systematically. Additionally, the impact abrasive wear resistance under different impact energies were also analyzed and compared with another sintered HCCI with 20 wt% Cr. The results indicated that sintering temperature has a strong influence on the sintered alloy’s density, hardness, impact toughness and bending strength. The M7C3 type (M is Cr and Fe) carbides were obviously coarsened as temperature increased and their rod-shaped branches were fully developed at the same time, thereby resulting in carbide network formation in the matrix. The reasonable sintering temperature range was 1195–1205 °C, and the optimum mechanical properties had the hardness of 63.9 HRC, bending strength of 2112.65 MPa and impact toughness of 7.92 J/cm2. What is more important impact abrasive wear test results indicated 15 wt% Cr sintered HCCI’s wear resistance could be comparable to 20 wt% Cr sintered HCCI under impact energy 1~3 J/cm2, and it is more cost effective

Nonuniform Microwave Photonic Delay-Line Filter For Optical Sensor Network Interrogation

We propose a new design of nonuniform spaced microwave photonic delay-line filter based generic optical fiber sensors interrogation platform. Both the amplitude and phase response of the microwave filter are used to demodulate optical sensors. Therefore, a large sensor network with different types of optical sensors can be interrogated simultaneously. The concept of this new microwave photonics enabled interrogation approach is presented and verified by simulations where four different types of optical sensors are simultaneously interrogated via inverse Fourier transform of filter frequency response

MetaGPT: Meta Programming for Multi-Agent Collaborative Framework

Recently, remarkable progress has been made in automated task-solving through the use of multi-agents driven by large language models (LLMs). However, existing works primarily focuses on simple tasks lacking exploration and investigation in complicated tasks mainly due to the hallucination problem. This kind of hallucination gets amplified infinitely as multiple intelligent agents interact with each other, resulting in failures when tackling complicated problems.Therefore, we introduce MetaGPT, an innovative framework that infuses effective human workflows as a meta programming approach into LLM-driven multi-agent collaboration. In particular, MetaGPT first encodes Standardized Operating Procedures (SOPs) into prompts, fostering structured coordination. And then, it further mandates modular outputs, bestowing agents with domain expertise paralleling human professionals to validate outputs and reduce compounded errors. In this way, MetaGPT leverages the assembly line work model to assign diverse roles to various agents, thus establishing a framework that can effectively and cohesively deconstruct complex multi-agent collaborative problems. Our experiments conducted on collaborative software engineering tasks illustrate MetaGPT's capability in producing comprehensive solutions with higher coherence relative to existing conversational and chat-based multi-agent systems. This underscores the potential of incorporating human domain knowledge into multi-agents, thus opening up novel avenues for grappling with intricate real-world challenges. The GitHub repository of this project is made publicly available on: https://github.com/geekan/MetaGP

Temporal and Spatial Dynamics of Carbon Fixation by Moso Bamboo (Phyllostachys pubescens) in Subtropical China

To study the temporal and spatial dynamics of carbon fixation by Moso bamboo (Phyllostachys pubescens) in subtropical China, carbon fixation of leaves within the canopy of P. pubescens was measured with a LI-6400 portable photosynthesis system. The results showed that the capability of carbon fixation of P. pubescens leaves had obvious temporal and spatial dynamic variations. It was revealed that there were two peak periods and two low periods in the season variation of carbon fixation capability. Data also revealed that the capability of carbon fixation by five-year-old P. pubescens was more than that of one-year-old and three-year-old. Daily and seasonal carbon fixation showed a negative correlation with the CO2 concentration. The temporal and spatial dynamics of carbon fixation by P. pubescens described above provided a scientific basis for development of technologies in bamboo timber production

Smoothed Particle Hydrodynamics (SPH) modelling of transient heat transfer in pulsed laser ablation of Al and associated free-surface problems

A Smoothed Particle Hydrodynamics (SPH) numerical model is developed to simulate pulsed-laser ablation processes for micro-machining. Heat diffusion behaviour of a specimen under the action of nanosecond pulsed lasers can be described analytically by using complementary error function solutions of second-order differential equations. However, their application is limited to cases without loss of material at the surface. Compared to conventional mesh-based techniques, as a novel meshless simulation method, SPH is ideally suited to applications with highly non-linear and explosive behaviour in laser ablation. However, little is known about the suitability of using SPH for the modelling of laser-material interactions with multiple phases at the micro scale. The present work investigates SPH modelling of pulsed-laser ablation of aluminium where the laser is applied directly to the free-surface boundary of the specimen. Having first assessed the performance of standard SPH surface treatments for functions commonly used to describe laser heating, the heat conduction behaviour of a new SPH methodology is then evaluated through a number of test cases for single- and multiple-pulse laser heating of aluminium showing excellent agreement when compared with an analytical solution. Simulation of real ablation processes, however, requires the model to capture the removal of material from the surface and its subsequent effects on the laser heating process. Hence, the SPH model for describing the transient behaviour of nanosecond laser ablation is validated with a number of experimental and reference results reported in the literature. The SPH model successfully predicts the material ablation depth profiles over a wide range of laser fluences 4–23 J/cm2 and pulse durations 6–10 ns, and also predicts the transient behaviour of the ejected material during the laser ablation process. Unlike conventional mesh-based methods, the SPH model was not only able to provide the thermo-physical properties of the ejected particles, but also the effect of the interaction between them as well as the direction and the pattern of the ejection

Contributions à la planification et à l'optimisation dans le système de santé moderne

La recherche opérationnelle (RO) joue un rôle important dans les systèmes de santé. Au cours des dernières années, l'hospitalisation à domicile comme les hôpitaux de réhabilitation ont émergé pour pallier aux coûts du système de santé et à la qualité de vie des patients. Dans les secteurs de la réhabilitation, la gestion des soins de santé est sous-développée et la plupart des hôpitaux de réhabilitation sont gérés uniquement par l’expérience. Dans cette thèse, nous traitons d'abord le problème de la planification des traitements dans les hôpitaux de réhabilitation afin de les optimiser. Notre travail vise à réduire le temps d’attente des patients hospitalisés et ainsi améliorer leur satisfaction. Afin de résoudre efficacement ce problème de planification de traitements complexes, nous proposons une approche basée sur un algorithme de recherche hybride de coucou qui est testée et validée dans un cas réel. Nous nous intéressons ensuite à l'hospitalisation à domicile qui constitue un autre problème réel compte tenu du vieillissement de la population. Dans la plupart des régions, un nombre croissant d’organisations à but lucratif et à but non lucratif s’associent pour offrir des soins aux patients. Elles ont tendance à atteindre un niveau hospitalier tant en quantité et qu'en qualité avec une flexibilité accrue par rapport aux services hospitaliers. Nous étudions les problèmes de planification et d'acheminement des soins à domicile en tenant compte de nombreuses contraintes liées à la fois aux patients et aux soignants. Le problème est un scénario pratique motivé et vise à minimiser les coûts d'exploitation totaux. Nous utilisons le solveur commercial Gurobi pour résoudre et valider le modèle avec des données réelles.Operations research (OR) plays an important role in healthcare system. In recent years, rehabilitation hospitals have been emerging to meet the increasing needs for rehabilitation services due to the ageing population trend. However, the healthcare management in rehabilitation sectors is undeveloped and most of the rehabilitation hospitals (departments) are managed by experience. In this thesis, we deal with a treatment scheduling problem in rehabilitation hospitals. The objective is to facilitate the scheduling process. More importantly, our work aims at reducing the waiting time of inpatients so as to improve inpatients’ satisfactions. In order to solve the complex treatment scheduling problem efficiently, we propose an approach based on a hybrid cuckoo search algorithm which is tested and validated in a real case. Moreover, home healthcare (HHC) is another real-world issue considering the aggravating trend of ageing population. In most areas, an increasing number of social-profit & non-profit organizations are joining in providing healthcare services to patients at their homes and it has a tendency to reach the hospital-level in both quantity and quality for the added flexibility than hospital's service. We investigate home healthcare scheduling and routing problem with consideration of many real-life factors, especially lunch break requirement. The problem is practical scenario motivated and aims at minimizing the total operating cost. We use the commercial solver Gurobi to solve and validate the model with real data

A Stability Training Method of Legged Robots Based on Training Platforms and Reinforcement Learning with Its Simulation and Experiment

This paper continues the proposed idea of stability training for legged robots with any number of legs and any size on a motion platform and introduces the concept of a learning-based controller, the global self-stabilizer, to obtain a self-stabilization capability in robots. The overall structure of the global self-stabilizer is divided into three modules: action selection, adjustment calculation and joint motion mapping, with corresponding learning algorithms proposed for each module. Taking the human-sized biped robot, GoRoBoT-II, as an example, simulations and experiments in three kinds of motions were performed to validate the feasibility of the proposed idea. A well-designed training platform was used to perform composite random amplitude-limited disturbances, such as the sagittal and lateral tilt perturbations (±25°) and impact perturbations (0.47 times the robot gravity). The results show that the proposed global self-stabilizer converges after training and can dynamically combine actions according to the system state. Compared with the controllers used to generate the training data, the trained global self-stabilizer increases the success rate of stability verification simulations and experiments by more than 20% and 15%, respectively