Land-use change simulation and assessment of driving factors in the loess hilly region - a case study as Pengyang County

The main objective of this study is to evaluate the land-use change and its relationship with its driving factors in the loess hilly region. In this study, a case study was carried out in Pengyang County. We set two land-use demand scenarios (a baseline scenario (scenario 1) and a real land-use requirement scenario (scenario 2)) during year 2001-2005 via assuming the effect of driving factors on land-use change keeps stable from 1993 to 2005. Two simulated land-use patterns of 2005 are therefore achieved accordingly by use of the conversion of land use and its effects model at small regional extent. Kappa analyses are conducted to compare each simulated land-use pattern with the reality. Results show that (1) the associated kappa values were decreased from 0.83 in 1993-2000 to 0.27 (in scenario 1) and 0.23 (in scenario 2) in 2001-2005 and (2) forest and grassland were the land-use types with highest commission errors, which implies that conversion of both the land-use types mentioned above is the main determinant of change of kappa values. Our study indicates the land-use change was driven by the synthetic multiply factors including natural and social-economic factors (e.g., slope, aspect, elevation, distance to road, soil types, and population dense) in 1993-2000 until "Grain for Green Project" was implemented and has become the dominant factor in 2001-2005

Irreducible representations of GLn(C)\textrm{GL}_n(\mathbb{C}) of minimal Gelfand-Kirillov dimension

In this article, by studying the Bernstein degrees and Goldie rank polynomials, we establish a comparison between the irreducible representations of $G=\textrm{GL}_n(\mathbb{C})$ possessing the minimal Gelfand-Kirillov dimension and those induced from finite-dimensional representations of the maximal parabolic subgroup of $G$ of type $(n-1,1)$. We give the transition matrix between the two bases for the corresponding coherent families.Comment: To appear in Acta Mathematica Sinica, English Serie

Characterisation of thrust performance of micro-nozzle machined by micro end-milling

Micro thruster is the power plant of mini-spacecraft. It enables the mini-spacecraft to realize orbit adjustment, station keeping and attitude controlling. Micro nozzle is one of key parts of the micro thruster. The surface roughness of its inner surface significantly influences the thrust performance of the thruster. In this paper, a residual surface model is developed for micro-nozzle obtained by micro machining using a ball end mill and a taper end mill. The residual surface model is then used to investigate the relationship between the surface quality and nozzle thrust performance in nozzle flow field. A thrust measuring apparatus is designed and manufactured to inspect the thrust performance of the machined micro nozzles. Both simulation and experiment results indicate that good machined surface quality is obtained with taper end mill. The nozzle machined with the taper end mill has better thrust performance than that with the ball end mill under the same inlet pressure

Milling stability prediction based on the hybrid interpolation scheme of the Newton and Lagrange polynomials

The stability lobe diagram (SLD) is commonly used to determine the suitable cutting parameters of the machining system in order to achieve a chatter-free machining process. An improved full-discretization method (FDM) is proposed to predict the SLD based on the hybrid interpolation scheme of the Newton and Lagrange polynomials. In order to solve the SLD, a third-order Newton polynomial is employed to interpolate the state term of the physical space equation of the system. Meanwhile, to investigate the influence of the interpolation order on predicting the SLD, the delayed term is estimated using the Lagrange polynomials of orders one to four successively. Subsequently, after constructing the transition matrix, a series of calculation for the stability prediction are carried out by applying Floquet theory. The calculated results from these constructed methods demonstrate that the FDM with a second-order Lagrange polynomial is optimal, and further has better computational performance compared with some existing discretization methods. Lastly, the influences of the dynamic parameters on chatter stability are analyzed based on the proposed FDM. When the stiffness and damping ratio increase, the limit cutting depth will be enhanced. The increasing natural frequency not only causes an obvious shift of the lobes to the right, but also raises the limit cutting depth to some extent. These theoretical analyses can guide the prediction and improvement of the chatter stability of a machining system

Quantum PT-Phase Diagram in a Non-Hermitian Photonic Structure

Photonic structures have an inherent advantage to realize PT-phase transition through modulating the refractive index or gain-loss. However, quantum PT properties of these photonic systems have not been comprehensively studied yet. Here, in a bi-photonic structure with loss and gain simultaneously existing, we analytically obtained the quantum PT-phase diagram under the steady state condition. To characterize the PT-symmetry or -broken phase, we define an Hermitian exchange operator expressing the exchange between quadrature variables of two modes. If inputting several-photon Fock states into a PT-broken bi-waveguide splitting system, most photons will concentrate in the dominant waveguide with some state distributions. Quantum PT-phase diagram paves the way to the quantum state engineering, quantum interferences, and logic operations in non-Hermitian photonic systems.Comment: 6 pages, 3 figure

Three-dimensional modeling and simulation of muscle tissue puncture process

Needle biopsy is an essential part of modern clinical medicine. The puncture accuracy and sampling success rate of puncture surgery can be effectively improved through virtual surgery. There are few three-dimensional puncture (3D) models, which have little significance for surgical guidance under complicated conditions and restrict the development of virtual surgery. In this paper, a 3D simulation of the muscle tissue puncture process is studied. Firstly, the mechanical properties of muscle tissue are measured. The Mooney-Rivlin (M-R) model is selected by considering the fitting accuracy and calculation speed. Subsequently, an accurate 3D dynamic puncture model is established. The failure criterion is used to define the breaking characteristics of the muscle, and the bilinear cohesion model defines the breaking process. Experiments with different puncture speeds are carried out through the built in vitro puncture platform. The experimental results are compared with the simulation results. The experimental and simulated reaction force curves are highly consistent, which verifies the accuracy of the model. Finally, the model under different parameters is studied. The simulation results of varying puncture depths and puncture speeds are analyzed. The 3D puncture model can provide more accurate model support for virtual surgery and help improve the success rate of puncture surgery

Advancements in material removal mechanism and surface integrity of high speed metal cutting : a review

The research and application of high speed metal cutting (HSMC) is aimed at achieving higher productivity and improved surface quality. This paper reviews the advancements in HSMC with a focus on the material removal mechanism and machined surface integrity without considering the effect of cutting dynamics on the machining process. In addition, the variation of cutting force and cutting temperature as well as the tool wear behavior during HSMC are summarized. Through comparing with conventional machining (or called as normal speed machining), the advantages of HSMC are elaborated from the aspects of high material removal rate, good finished surface quality (except surface residual stress), low cutting force, and low cutting temperature. Meanwhile, the shortcomings of HSMC are presented from the aspects of high tool wear rate and tensile residual stress on finished surface. The variation of material dynamic properties at high cutting speeds is the underlying mechanism responsible for the transition of chip morphology and material removal mechanism. Less surface defects and lower surface roughness can be obtained at a specific range of high cutting speeds, which depends on the workpiece material and cutting conditions. The thorough review on pros and cons of HSMC can help to effectively utilize its advantages and circumvent its shortcomings. Furthermore, the challenges for advancing and future research directions of HSMC are highlighted. Particularly, to reveal the relationships among inherent attributes of workpiece materials, processing parameters during HSMC, and evolution of machined surface properties will be a potential breakthrough direction. Although the influence of cutting speed on the material removal mechanism and surface integrity has been studied extensively, it still requires more detailed investigations in the future with continuous increase in cutting speed and emergence of new engineering materials in industries

Intrinsic and post-hoc XAI approaches for fingerprint identification and response prediction in smart manufacturing processes

In quest of improving the productivity and efficiency of manufacturing processes, Artificial Intelligence (AI) is being used extensively for response prediction, model dimensionality reduction, process optimization, and monitoring. Though having superior accuracy, AI predictions are unintelligible to the end users and stakeholders due to their opaqueness. Thus, building interpretable and inclusive machine learning (ML) models is a vital part of the smart manufacturing paradigm to establish traceability and repeatability. The study addresses this fundamental limitation of AI-driven manufacturing processes by introducing a novel Explainable AI (XAI) approach to develop interpretable processes and product fingerprints. Here the explainability is implemented in two stages: by developing interpretable representations for the fingerprints, and by posthoc explanations. Also, for the first time, the concept of process fingerprints is extended to develop an interpretable probabilistic model for bottleneck events during manufacturing processes. The approach is demonstrated using two datasets: nanosecond pulsed laser ablation to produce superhydrophobic surfaces and wire EDM real-time monitoring dataset during the machining of Inconel 718. The fingerprint identification is performed using a global Lipschitz functions optimization tool (MaxLIPO) and a stacked ensemble model is used for response prediction. The proposed interpretable fingerprint approach is robust to change in processes and can responsively handle both continuous and categorical responses alike. Implementation of XAI not only provided useful insights into the process physics but also revealed the decision-making logic for local predictions