Combined finite element and multi-body dynamics analysis of effects of hydraulic cylinder movement on ploughshare of horizontally reversible plough

Abstract: Hydraulic Cylinder (HC), one of the key components of Horizontally Reversible Plough (HRP), takes the responsibilities for the commuting soiltillage of HRP. The dynamic behaviors of HC surely affectthe tilling performances of HRP. Based on our previously related work, this paper further addresses the effects of HC movements during tillage on ploughshare, especially at share-point, of HRP. For HC, uniform motion was considered in this study. A combined finite element and multi-body dynamics analysis (MDA) was implemented to assess both tillage kinematics and kinetics of the ploughshare. These numerical predictions were primarily involved in five different HC movement velocities and two actual HRP tilling scenarios, respectively, where loading data due to the HC movements were obtained from an MDA and applied to load a finite element modal of the ploughshare. Our results show that the importance of performing MDA as a preliminary step FEA to obtain an insight into the actual stress and strain variations at the share-point. Our findings demonstrate that the different movements of HC have no adverse effects on the service life of the ploughshare though they result in the maximum stress and strain at the sharepoint during HRP tillage

Defense Against Model Extraction Attacks on Recommender Systems

The robustness of recommender systems has become a prominent topic within the research community. Numerous adversarial attacks have been proposed, but most of them rely on extensive prior knowledge, such as all the white-box attacks or most of the black-box attacks which assume that certain external knowledge is available. Among these attacks, the model extraction attack stands out as a promising and practical method, involving training a surrogate model by repeatedly querying the target model. However, there is a significant gap in the existing literature when it comes to defending against model extraction attacks on recommender systems. In this paper, we introduce Gradient-based Ranking Optimization (GRO), which is the first defense strategy designed to counter such attacks. We formalize the defense as an optimization problem, aiming to minimize the loss of the protected target model while maximizing the loss of the attacker's surrogate model. Since top-k ranking lists are non-differentiable, we transform them into swap matrices which are instead differentiable. These swap matrices serve as input to a student model that emulates the surrogate model's behavior. By back-propagating the loss of the student model, we obtain gradients for the swap matrices. These gradients are used to compute a swap loss, which maximizes the loss of the student model. We conducted experiments on three benchmark datasets to evaluate the performance of GRO, and the results demonstrate its superior effectiveness in defending against model extraction attacks

STUDY ON INNOVATION AND MANAGEMENT OF THE OBJECTIVE STAGE IN PRODUCT DESIGN

In this paper, innovation and management during the objective stage of the product design process are studied. The idea of innovation for the whole product concept at the objective design stage was put forward in view of the overall development trends and mode of product design. The strategies of product innovation as well as its related process are also discussed. Finally, some recommendations regarding diminishing uncertainty in this stage of product design process are being made

Uncertainty and disturbance estimator-based control of a flapping-wing aerial vehicle withwith unknown backlash-like hysteresis

Robust and accurate control of a flapping-wing aerial vehicle (FWAV) system is a challenging problem due to the existence of backlash-like hysteresis nonlinearity. This paper proposes uncertainty and disturbance estimator (UDE)-based control with output feedback for FWAV systems. The approach enables the acquisition of the approximate plant model with only a partial knowledge of system parameters. For the design of the controller, only the bandwidth information of the unknown plant model is needed, which is available through the UDE filter. The stability analysis of the closed-loop system with the UDE-based controller is presented. It is shown that the proposed control scheme can ensure the boundedness of the control signals. A number of numerical simulations are carried out to demonstrate the satisfactory trajectory tracking performance of the proposed method

Numerical investigation of the structure of a silicon six-wafer micro-combustor under the effect of hydrogen/air ratio

Research reports indicate that sufficiently high equivalence ratio of the hydrogen/air mixture leads to the upstream burning in the recirculation jacket, possibly damaging the micro- combustor due to the high wall temperature. This work investigates the influences of the equivalence ratio of the mixture on the structure of a micro-combustor device. Numerical simulation approaches focused on the structural design of the micro-combustor with the flame burning in the recirculation jacket. Combustion characteristics of the combustor were first analysed based on 2D computational Fluid Dynamics (CFD), and then thermo-mechanical analysis on the combustor was carried out by means of 3D Finite Element Analysis (FEA) method. The results showed that the most dangerous locations where the critical failure could possibly occur lay at the burning areas in the recirculation jacket due to the poor bonding, the high temperature and the residual stress. The results of this study can be used for the design and improvement of the micro-combustors

Structural design of a silicon six-wafer micro-combustor under the effect of heat transfer boundary condition at the outer walls

The aim of this investigation was to establish a methodology for designing highly stressed micro fabricated structures by studying the structural design issues associated with a silicon six–wafer micro combustor under the effect of heat transfer boundary condition at the outer walls. Some experimental and numerical simulation results have indicated that the flame can not be sustained in the micro combustor if the poor heat transfer coefficients at the outer wall are present. This could cause the combustor wall temperature higher than the auto ignition temperature of reactants and results in the upstream burning. Since silicon has relatively poor high temperature strength and creep resistance when the temperature is above the brittle to ductile transition temperature (BDTT), e.g. 900K, the combustion in the recirculation jacket could possibly damage the micro combustor due to the high wall temperature

Experimental analyses to investigate the feasibility and effectiveness in using heat pipe-embedded drills

This paper presents an experimental investigation to verify the feasibility and effectiveness of heat pipe cooling in drilling operations. The basic idea is to insert a heat pipe at the center of the drill tool with the evaporator close to the drill tip and the condenser at the end of the drill. Consequently, the heat generated at the tool–chip interface can be removed by convection heat transfer. Experimental studies were involved in three cases, including solid drill without coolant, solid drill with coolant, and heat pipe drill. Drilling tests were conducted on a CNC machining center with full immersion cutting. The cast iron square block was used as the workpiece, and the high-speed steel was chosen for the drill tool material. Flank wear is considered as the criterion for tool failure, and the wear was measured using a Hisomet II Toolmaker’s microscope. The tests were conducted until the drill was rejected when an average flank wear greater than 0.10 mm was recorded. The results demonstrate that using a heat pipe in the drilling process can effectively perform thermal management comparable to the flooding coolant cooling used pervasively in the manufacturing industry, extending the tool life of the drill

Urinary Metabolomics on the Biochemical Profiles in Diet-Induced Hyperlipidemia Rat Using Ultraperformance Liquid Chromatography Coupled with Quadrupole Time-of-Flight SYNAPT High-Definition Mass Spectrometry

Ultraperformance liquid chromatography coupled with quadrupole time-of-flight synapt high-definition mass spectrometry metabolomics was used to characterize the urinary metabolic profiling of diet-induced hyperlipidaemia in a rat model. Analysis was done by orthogonal partial least squares discriminant analysis, correlation analysis, heat map analysis, and KEGG pathways analysis. Potential biomarkers were chosen by S-plot and were identified by accurate mass, isotopic pattern, and MS/MS fragments information. Significant differences in fatty acid, amino acid, nucleoside, and bile acid were observed, indicating the perturbations of fatty acid, amino acid, nucleoside, and bile acid metabolisms in diet-induced hyperlipidaemia rats. This study provides further insight into the metabolic profiling across a wide range of biochemical pathways in response to diet-induced hyperlipidaemia

Text-Video Retrieval via Variational Multi-Modal Hypergraph Networks

Text-video retrieval is a challenging task that aims to identify relevant videos given textual queries. Compared to conventional textual retrieval, the main obstacle for text-video retrieval is the semantic gap between the textual nature of queries and the visual richness of video content. Previous works primarily focus on aligning the query and the video by finely aggregating word-frame matching signals. Inspired by the human cognitive process of modularly judging the relevance between text and video, the judgment needs high-order matching signal due to the consecutive and complex nature of video contents. In this paper, we propose chunk-level text-video matching, where the query chunks are extracted to describe a specific retrieval unit, and the video chunks are segmented into distinct clips from videos. We formulate the chunk-level matching as n-ary correlations modeling between words of the query and frames of the video and introduce a multi-modal hypergraph for n-ary correlation modeling. By representing textual units and video frames as nodes and using hyperedges to depict their relationships, a multi-modal hypergraph is constructed. In this way, the query and the video can be aligned in a high-order semantic space. In addition, to enhance the model's generalization ability, the extracted features are fed into a variational inference component for computation, obtaining the variational representation under the Gaussian distribution. The incorporation of hypergraphs and variational inference allows our model to capture complex, n-ary interactions among textual and visual contents. Experimental results demonstrate that our proposed method achieves state-of-the-art performance on the text-video retrieval task