Running stability analysis of the Semi-Crawler Type Mini-Forwarder by Using a Dynamic Analysis Program

Inaccurate results are usually produced due to lack of precise dynamic parameters when analyzing the running stability of railway vehicles. In this paper, a new solution is proposed to conduct the running stability analysis of railway vehicles supported by their three-dimensional (3D) CAD models, which are realized based on the intrinsic mapping relationship between the dynamic model and the 3D CAD model of railway vehicles. First, a dynamic model library of railway vehicles is established, and for each model type the software package for running stability analysis is programmed with Matlab. Then according to the requested parameters of each model, the corresponding dynamic parameter extraction flow based on 3D CAD model is designed by the secondary development of CAD software. The user chooses CAD objects and sets part of dynamic parameters using a wizard-style guiding dialogs; the background program will automatically and accurately extract the physical and geometric parameters from the CAD model, and then call the Matlab software package and transfer the parameter values, with analysis results presented in CAD environment. The case study shows that, this method can not only ensure the precision of dynamic parameters, but also improve the dynamic modeling efficiency for running stability analysis of railway vehicles.

An asymptotic error analysis of the conventional discrete dynamic programming (DDP) method is presented, and upper bounds of the error in the control policy (i.e., the difference of the estimated and true optimal control) at each operation period are computed. This error is shown to be of the order of the state discretization interval (ΔS), a result with significant implications in the optimization of multistate systems where the “curse of dimensionality” restricts the number of states to a relatively small number. The error in the optimal cost varies with ΔS2. The analysis provides useful insights into the effects of state discretization on calculated control and cost functions, the comparability of results from different discretizations, and criteria about the required number of nodes. In an effort to reduce the discretization error in the case of smooth cost functions, a new discrete dynamic programming method, termed gradient dynamic programming (GDP), is proposed. GDP uses a piecewise Hermite interpolation of the cost‐to‐go function, at each stage, which preserves the values of the cost‐to‐go function and of its first derivatives at the discretization nodes. The error in the control policy is shown to be of the order of (ΔS)3 and the error in the cost to vary with ΔS4. Thus as ΔS decreases, GDP converges to the true optimum much more rapidly than DDP. Another major advantage of the new methodology is that it facilitates the use of Newton‐type iterative methods in the solution of the nonlinear optimization problems at each stage. The linear convergence of DDP and the superlinear convergence of GDP are illustrated in an example.

FuS-GCN: Efficient B-rep based graph convolutional networks for 3D-CAD model classification and retrieval

Introduction. The research is aimed at developing a methodology for determining the optimal location of material flows’ distribution center, taking into account the formation of ring routes based on the use of the fictitious nodes and branches’ method (FNB), in order to minimize overall logistical costs. Despite the sufficient number of existing ways to solve this problem, they have some disadvantages: they are not entirely realistic and do not completely meet the requirements of logistical optimization. Namely, existing algorithms do not take into account the need to visit the branches of the transport graph several times and the curvature of the movement trajectory.The developed technique has greater practical application because it deals with determining the optimal location of the distribution center based on the criterion of full vehicle loading, using piecewise linear approximation to account for the curvature of routes, forming delivery routes using the accurate fictitious nodes and branches’ method (FNB) to optimize transportation and minimize overall logistical costs. This technique can be used by both providers to analyze and select the location of a logistics distribution center taking into account the formation of optimal routes for the delivery of goods, and by owners of large retailers.Materials and methods. The developed methodology includes several stages. At the first stage, the area of the most probable location of the distribution center (DC) is determined. We calculate the coordinates of cargo center of gravity using the formulas for the strength of materials. As its weight, we take the amount of cargo in receiving points. We accept the hypothesis that the placing area for distribution center is located around the cargo center of gravity. Its boundary passes through the nodes closest to it. The nodes are cargo points, road intersections and points of abrupt changes in the direction of movement. The expert can assign additional nodes to clarify the influence of geometry, length, and other parameters of the trajectory of movement. As a rule, there is no road between the center of gravity and the nodes. At the second stage, a rational location of the regional center is determined. There is no road between the center of gravity and the nodes. Therefore, ring routes are calculated that originate from nodal points using the method of fictitious nodes and branches. The routing problem is reduced to finding one ring that passes through the selected nodal point several times. The constraint is taken into account by the blocking method. At the third stage, we replace the branches of the curvilinear route of movement with piecewise linear interpolation. We determine the transport work and the coordinates of the center of gravity of the rectangular diagram on each branch of the route. We find the value of the total transport work around the coordinate axes. We calculate the coordinates of the regional center. We accept its rational coordinates according to the average values obtained for each selected node.Result. The application of the developed methodology for the network delivering goods from the distribution center to the Public Joint Stock Company “Magnit” trading points per shift has reduced the number of routes, time on the route by 10% and the length of the route by 16%.Conclusion. The methodology for determining the optimal location of the distribution center of material flows has been provided. The program has been developed on the basis of the proposed methodology. Results of the use of the proposed methodology have been obtained by testing on the example of Public Joint Stock Company “Magnit”.

Generally for any new design initially a concept layout in 2D CAD is generated. But sometimes, if the geometry of the product becomes complicated, then 3D CAD model is preferred, because 3D CAD model can give us a complete all side view at a time like a real product, but in a virtual world. The present case study will show the utilisation of 3D CAD at the concept design stage of a complicated shaped product for a new system. This will also give an idea about cost and time comparison. This will also show how 3D CAD model can also helps to analyse the product. Thus, this paper will describe about the importance of 3D CAD tools for product development.

Keywords Invasive species, Economics, Californian thistle, New Zealand, Stochastic, Dynamic programming, Biological control, Extinction risk, Herbivory, Dispersal, Competition Invasive species are one of the most significant threats to biodiversity and agricultural production systems leading to huge worldwide economic damages. This thesis has two main aims. The first aim is to analyse the control of an invasive plant in an agricultural system, using the case study of the Californian thistle in New Zealand. The second aim is to study the negative externalities that controlling invasion in agriculture can pose to ecosystems. To achieve the first aim, both deterministic and stochastic dynamic programming models are set up to find cost effective methods to tackle the problem of Californian thistle. I make a contribution to the literature by performing a dynamic and stochastic programming analysis in which two different categories of control strategies are considered, each with different dynamics. Models are set up with a discrete decision variable consisting of 62 feasible combinations of integrated control strategies. For the second aim I introduce a novel modelling approach in which two compartments are distinguished: a managed compartment where locally a herbivore is introduced to control a weed, and a natural compartment where the same herbivore species can attack a wild plant species. The main processes are herbivory, competition, dispersal and control. I conclude that bioeconomic modelling is an important tool in analysing optimal management strategies for the control of invasive species and that annual and once and for all choices need to be integrated in the analysis. A stochastic approach is appropriate but does not necessarily lead to different results, depending on the parameter values and the setup of the model. Finally, the method illustrates that an integrated analysis of the economic system and the ecological system is required to assess the risk of extinction of natural plant species. This risk depends on species interactions which in this thesis are competition, dispersal and herbivory. I conclude that a control measure can protect the desirable wild plant species and increase benefits obtained from the ecosystem. For the policy implications, I conclude that there are several strategies to control invasive species, which can be integrated combinations of control options. The optimal strategy depends on the costs and benefits of the control options. In the case study for the Californian thistle I found that the optimal strategy is a combination of methods. For the interaction between agricultural and natural system I conclude that introducing a biological agent to the agricultural system can cause extinction of a desirable plant in the natural system. The main processes are competition, herbivory and dispersal. These processes are important and need to be analysed in detail before introducing the biological agent. I conclude that the optimal strategy to control the introduced biological agent also depends on interaction of species through competition, dispersal and herbivory.

The state-of-art 6D object pose detection methods use convolutional neural networks to estimate objects' 6D poses from RGB images. However, they require huge numbers of images with explicit 3D annotations such as 6D poses, 3D bounding boxes and 3D keypoints, either obtained by manual labeling or inferred from synthetic images generated by 3D CAD models. Manual labeling for a large number of images is a laborious task, and we usually do not have the corresponding 3D CAD models of objects in real environment. In this paper, we develop a keypoint-based 6D object pose detection method (and its deep network) called Object Keypoint based POSe Estimation (OK-POSE). OK-POSE employs relative transformation between viewpoints for training. Specifically, we use pairs of images with object annotation and relative transformation information between their viewpoints to automatically discover objects' 3D keypoints which are geometrically and visually consistent. Then, the 6D object pose can be estimated using a keypoint-based geometric reasoning method with a reference viewpoint. The relative transformation information can be easily obtained from any cheap binocular cameras or most smartphone devices, thus greatly lowering the labeling cost. Experiments have demonstrated that OK-POSE achieves acceptable performance compared to methods relying on the object's 3D CAD model or a great deal of 3D labeling. These results show that our method can be used as a suitable alternative when there are no 3D CAD models or a large number of 3D annotations.

Concurrency programs are hard to test or debug due to their non-deterministic nature. Existing dynamic program analysis approaches tried to address this by carefully examine a recorded execution trace. However, developing such analysis tools is complicated, requiring to take care of many tedious implementation details, and comparing and evaluating different analysis approaches are also subject to various biases, due to lack of a common base platform. This motivates us to design DPAC, an infrastructure that support in building dynamic program analysis tools for concurrency Java programs. DPAC takes events and their various processing mechanisms as its underlying model to facilitate monitoring and manipulation of program executions as required by dynamic program analysis. Various analysis tools can be implemented by customizing their required event types and processing mechanisms. We show two concrete case studies how our DPAC helps building existing dynamic program analysis approaches, as well as tuning subtle implementation details for supporting customized function implementation and code transformation.

Dynamic program analysis is extremely successful both in code debugging and in malicious code attacks. Fuzzing, concolic, and monkey testing are instances of the more general problem of analysing programs by dynamically executing their code with selected inputs. While static program analysis has a beautiful and well established theoretical foundation in abstract interpretation, dynamic analysis still lacks such a foundation. In this paper, we introduce a formal model for understanding the notion of precision in dynamic program analysis. It is known that in sound-by-construction static program analysis the precision amounts to completeness. In dynamic analysis, which is inherently unsound, precision boils down to a notion of coverage of execution traces with respect to what the observer (attacker or debugger) can effectively observe about the computation. We introduce a topological characterisation of the notion of coverage relatively to a given (fixed) observation for dynamic program analysis and we show how this coverage can be changed by semantic preserving code transformations. Once again, as well as in the case of static program analysis and abstract interpretation, also for dynamic analysis we can morph the precision of the analysis by transforming the code. In this context, we validate our model on well established code obfuscation and watermarking techniques. We confirm the efficiency of existing methods for preventing control-flow-graph extraction and data exploit by dynamic analysis, including a validation of the potency of fully homomorphic data encodings in code obfuscation.

Programming tools have expanded both in scope of the problems they solve, and in the kinds of techniques they use. Traditionally, programming tools have focused on detecting errors in programs. Recently, this scope has broadened to help with other programming tasks, including inferring specifications, helping diagnose root cause of errors during debugging, and managing knowledge in large projects. Also, traditionally programming tools have been based on either static or dynamic program analysis. Modern programming tools combine static and dynamic program analysis together with techniques from other disciplines such as statistical and probabilistic inference, and information retrieval. This paper reports on some such tools built by the Rigorous Software Engineering group at Microsoft Research India.

Conception et fabrication de moulages assistées par ordinateur

Freehand sketch on a paper is commonly seen being used as it is an effective convenient way to express rough ideas. The sketch is typically transformed to be a 3D CAD model by a designer for subsequent operations such as rapid prototyping process where a physical prototype is fabricated from a 3D CAD model. To speed up the realization of an idea, a research called adaptive layered manufacturing from overtraced freehand sketch has been being developed as an attempt to shorten steps from having a sketch drawing to obtaining a physical prototype. Presented in this paper is the current progress of the research. A single line drawing identification module is being developed to transform a paper-based overtraced freehand sketch to be a single line drawing. This module is required to generate more information about the sketch (i.e., the number of lines and their starting points and endpoints) since the initial information is limited to a batch of points. The algorithms developed for this module have been implemented on LabVIEW program. Some examples of sketch to a single line drawing transformation are also presented in this paper.

Abstract: Due to recent crises of electricity in the country, it is utmost need for the utilization of renewable energy resources abundantly available like hydropower. To overcome this problem of electricity shortage, hydro-power turbines can be used. Since every hydro site have different site conditions, so design and selection of the proper turbine type and size becomes more important. In this case, it is vital to adopt indigenous design and development of hydropower components. Hydro turbines are the most important part of hydro-power plant. In this research, development of turbines has been focused, mainly of low head turbines. The reason is that small low-head schemes can easily be executed on the run-off-rivers and canals. This paper presents the improvement technique administrated on a complex mathematics of blade profile through static and dynamic process analysis. It is used through modification of the blade profile geometry at five totally different angles within the 3D (Three Dimensional) CAD model. Blade advanced geometry and style are developed by victimization the coordinates purpose system on the blade in PRO-E/CREO software system. Five distinct blade models square measure developed for analysis purpose. Based on the rate of flow rate and heads, blade profiles square measure analysed using ANSYS software to check and compare the output results for optimization of the blades for improved results which show that by changing blade profile angle and its geometry, different blade sizes and geometry can be optimized using the computational techniques with changes in CAD models. After successful validation, five different blade profiles have been developed. Research results show improvement in the power output of the turbine with 5.43%. Future recommendations were also suggested to pave the way of further improvement in this area of specialization. Keywords: Low Head, Kaplan Turbine, Runner Blade, CFD, Optimization, Hydropower, Runof-River Cite this Article Om Prakash Sondhiya, Pinkesh Bhurlekar. Optimize the Efficiency of the Kaplan Turbine by Design and CFD Analysis of Runner Wheel Blades. Recent Trends in Fluid Mechanics. 2019; 6(1): 1–19p.

This study proposes a method for automating the determination of assembly order by automating the derivation of the necessary connection relationships between the parts. The proposed method minimizes the information required for the initial conditions and automatically determines the feasible assembly orders. As a general rule, based on the assumption that the assembly order for a product is the reverse of the disassembly order, once the disassembly order is derived based on the 3D CAD model and the connection relationships between the parts, the assembly order can be determined. Until now, however, the relationships between the parts are decided manually by the attendant engineers, thus, hindering the full automation of the determination of the assembly order. To achieve full automation realistically, the connection relationships between the parts should be derived automatically from the 3D CAD model, for which this study proposes an efficient method. The components were extracted from the 3D CAD model, and the bolts were identified. The connection relationships between the parts were derived from the interference conditions determined while moving each part minutely. An association chart diagram was created from the obtained connection relationships, from which multiple assembly order candidates could be derived.

Aged process plants have typically different configurations from those in the as-built status and thus 3D CAD models for the aged process plant have often been outdated due to the difficulty of data update activities. This situation disturbs the efficient and safe operation and maintenance of aged process plants. As a solution to this problem, 3D CAD models in the as-operated status are reversely generated from point cloud obtained using a laser scanning device. 3D modeling with a point cloud in a plant 3D CAD system needs retrieving catalogs for equipment and materials and placing them in 3D dimensional design space. To accomplish this, this study designs an AutoCAD Plant 3D-based plug-in type system for the shape similarity-based fitting retrieval and implements it according the design.