Modular design for simulation

This paper presents a modular design approach for the implementation of process-oriented or event-oriented discrete systems simulation software. Requirements for such a simulation facility are discussed, to include list processing capabilities, data structuring capabilities, dynamic allocation of data storage, statistics collection and number-crunching capabilities, and subprograms. Specific focus is placed upon implementing the process view which requires constructs in the language for initiating, controlling and terminating a process. Resource management facilities are also considered, to include a means of defining a resource with its associated resource handler and a set of primitives for requesting, releasing and obtaining status information regarding a resource. HPSIM, an organized collection of modules written in Modula-2, was designed to facilitate both event-oriented and process-oriented discrete systems simulation, Modula-2 was chosen for its data abstraction facilities, its software engineering capabilities, its execution efficiency, its ability for separate compilation and its implementation of co-routines. The modeller encapsulates the conceptual model of the system into a software module which is interfaced with the HPSIM modules. The IMPORT statement in Modula-2 allows the modeller to access any of the routines provided by HPSIM as required. An example involving a single-server CPU system highlights the process/resource features of HPSIM.     

The PIAM approach to modular integrated assessment modelling

The next generation of integrated assessment modelling is envisaged as being organised as a modular process, in which modules encapsulating knowledge from different scientific disciplines are independently developed at distributed institutions and coupled afterwards in accordance with the question raised by the decision maker. Such a modular approach needs to respect several stages of the model development process, approaching modularisation and integration on a conceptual, numerical, and technical level. The paper discusses the challenges at each level and presents partial solutions developed by the PIAM (Potsdam Integrated Assessment Modules) project at the Potsdam Institute for Climate Impact Research (PIK). The challenges at each level differ greatly in character and in the work done addressing them. At the conceptual level, the notion of conceptual consistency of modular integrated models is discussed. At the numerical level, it is shown how an adequate modularisation of a problem from climate–economy leads to a modular configuration into which independently developed climate and economic modules can be plugged. At the technical level, a software tool is presented which provides a simple consistent interface for data transfer between modules running on distributed and heterogeneous computer platforms.     

使用程序聚类技术的模块重构风险分析方法

随着软件系统的演化,其模块化结构会逐渐退化。软件重构是调整系统结构的重要手段,但哪些模块最需要重构却难以预测。提出了一种基于程序聚类技术的模块重构风险分析方法,该方法通过对目标系统进行结构聚类和语义聚类获得其参考模块化结构,然后比较现实模块化结构与参考模块化结构之间的差异,对程序模块的设计质量进行评价,识别出系统中重构风险较高的模块。实验以三个开源软件的演化历史作为研究对象,与传统的模块化度量方法进行了比较,结果表明采用所提方法获得的预测结果与实际重构活动有较好的吻合度,从而验证了该方法的有效性。     

横切侵入性和横切不变性

由于面向方面语言的不知觉性和多量化特点,模块分析和模块推理比传统方法学更加困难.为了解决面向方面语言的横切安全和横切质量问题,使用前提条件和后验条件约束横切模块和被横切模块,然而在横切过程中寻找前提条件和后验条件的失败原因十分微妙和复杂.为了分析一个横切关注点的行为影响,程序员需要考虑方面本身和这个方面影响的系统其他部分.当几个方面编织在同一个切入点,危险干扰分析变得更加复杂.类似面向对象语言中的行为子类型概念,引入横切不变性概念.为了检查由于破坏横切不变性引起的行为错误和其他4种简单行为错误,基于软件行为契约提出一个横切不变性检测算法.为了形式化这个算法,提出Crosscutting Contract演算和一组契约求解规则,并通过定义和证明契约完备性来保证契约求解过程的正确性.还使用一个例子说明如何使用这些契约求解规则检测和分析行为错误.     

Modular manufacturing

This paper discusses requirements to be satisfied by future manufacturing systems and proposes a new concept of modular manufacturing to integrate intelligent and complex machines. In large-scale systems such as manufacturing systems, modularization is indispensable for clarifying logical structure and assuring a high degree of ease of construction. The parts, products and manufacturing equipments as well as the design and operating activities themselves are all described in units called modules. A manufacturing system is constructed and operated by combining these in building-block style. The creation of this manufacturing system relies on construction and operating systems that enable design and simulation in the virtual world, and production and control in the real world, in a unified approach. Hardware modules and software modules are compiled flexibly and hierarchically to fulfil specified tasks. A system in which modular manufacturing as a concept of system integration is applied to manufacturing robots is called a modular robot system. The robots are embedded in manufacturing systems as the highest application of model-based robotics.     

Modular product design with grouping genetic algorithm—a case study

Modular products are products that fulfill various functions through the combination of distinct modules. These detachable modules are constructed both according to the maximum physical and functional relations among components and maximizing the similarity of specifically modular driving forces. Accordingly, a non-linear programming is proposed to identify separable modules and simultaneously optimize the number of modules. This paper presents a systematic approach to accomplish modular product design in four major phases. Phase 1 is by means of functional and physical interaction analysis to format a component-to-component correlation matrix. Phase 2 is the exploration of design requirements to evaluate the relative importance of each modular driver. In phase 3, non-linear programming is used to formulate the objective function. In the final phase, a heuristic grouping genetic algorithm is adopted to search for the optimal or near-optimal modular architecture. This process and its application are illustrated by a real case of an electrical consumer product provided by an Original Design Manufacturer. The results demonstrate that the designer could direct a new approach to establish product modules according to the relative importance of modular drivers and the interaction among components.     

Modular Simulation in Multibody System Dynamics

The dynamic analysis of complex engineering systems likeautomobiles is often relieved by a modular approach to make it treatableby a team of engineers. The modular decomposition is based onengineering intuition of corresponding engineering disciplines. In thispaper, a modular formulation of multibody systems is proposed which isbased on the block representation of a multibody system withcorresponding input and output quantities. Advantages of this modularapproach range from independent and parallel modeling of subsystems overthe easy exchange of the resulting modules to the use of differentsoftware for each module. However, the modular simulation of the globalsystem by coupling of simulators may result in an unstable integrationif an algebraic loop exists between the subsystems. This numericalphenomenon is analyzed and a method of simulator coupling whichguarantees stability for general systems including algebraic loops isintroduced. Numerical results of the modular simulation of aslider-crank mechanism are presented.     

The Genealogy of the Moral Modules

This paper defends a cognitive theory of those emotional reactions which motivate and constrain moral judgment. On this theory, moral emotions result from mental faculties specialized for automatically producing feelings of approval or disapproval in response to mental representations of various social situations and actions. These faculties are modules in Fodor's sense, since they are informationally encapsulated, specialized, and contain innate information about social situations. The paper also tries to shed light on which moral modules there are, which of these modules we share with non-human primates, and on the (pre-)history and development of this modular system from pre-humans through gatherer-hunters and on to modern (i.e. arablist) humans. The theory is not, however, meant to explain all moral reasoning. It is plausible that a non-modular intelligence at least sometimes play a role in conscious moral thought. However, even non-modular moral reasoning is initiated and constrained by moral emotions having modular sources.     

Modeling and simulation of closed loop multibody systems with bodies-joints composite modules

Modular approaches are effective in improving the modeling efficiency in multibody system dynamics. A modular method, called bodies-joints composite simulation (BJCS) is presented in this paper. Two types of bodies-joints composite modules, i.e., f modules and 0 modules, are defined according to topology design rules of closed loop mechanisms. By this module partitioning, the differential-algebraic equations of motion of the system can be separated into purely algebraic and differential equations by structure decomposition. The stability criterion for the simulation is derived and a closed-form formulation to solve the algebraic loop problem is proposed. Simulation results of the forward dynamics of a 5R mechanism and a 6-UPS platform are presented to show the feasibility of the method. The CPU times of these two case studies are provided and compared with the generalized coordinate partitioning of Wehage and Haug and the modular simulation method of Kübler and Schiehlen, which indicate that the closed-form algebraic loop solver is more efficient than the numerical ones.     

Anatomy-based organization of morphology and control in self-reconfigurable modular robots

In this paper, we address the challenge of realizing full-body behaviors in scalable modular robots. We present an experimental study of a biologically inspired approach to organize the morphology and control of modular robots. The approach introduces a nested hierarchy that decomposes the complexity of assembling and commanding a functional robot made of numerous simple modules. The purpose is to support versatility, scalability, and provide design abstraction. The robots we describe incorporate anatomy-inspired parts such as muscles, bones, and joints, and these parts in turn are assembled from modules. Each of those parts encapsulates one or more functions, e.g., a muscle can contract. Control of the robot can then be cast as a problem of controlling its anatomical parts rather than each discrete module. To validate this approach, we perform experiments with micron-scale spherical catom modules in simulation. The robots we simulate are increasingly complex and include snake, crawler, quadruped, cilia surface, arm-joint-muscle, and grasping robots. We conclude that this is a promising approach for future microscopic many-modules systems, but also that it is not applicable to relatively weak and slow homogeneous systems such as the centimeter-scale ATRON.     

Realization of task-based designs involving DH parameters: a modular approach

Task-based designs—proven to be successful for constrained environments—may face challenges at prototype development phase. To assist in generalized design and development of task-based serial manipulators for cluttered environments, a parameters-based modular approach is proposed. First, a task-based design strategy for serial manipulators is exhibited, using all the robotic parameters (DH parameters) as variables. The flexibility in robotic parameters enhances the possibility of good designs even for highly cluttered workspaces, but the realization of the resulting complicated designs is challenging. This work is an attempt to develop modular manipulators in correspondence to the task-based designs. The DH parameters-based proposed link modules, with reconfigurable architecture, can be adjusted and assembled to acquire the serial manipulators with designed robotic parameters. To validate the concept, some standardized 3R-configurations have been modelled using the proposed link modules. Case studies are presented on task-based design of robotic manipulators, with six and eight degrees of freedom, for service applications in realistic environments. The selected case studies include the robot design processes for applications of cleaning solar panels, and for the maintenance of the nuclear plants.     

A modular approach to the dynamics of complex multirobot systems

This work presents a modular approach for the dynamic modeling and efficient simulation of complex robot systems composed of multiple robots constrained by multiple concurrent contacts. The modular nature of the algorithm enables existing open-chain models for individual robots and other mechanisms to be incorporated without significant reprogramming, while a general contact model allows both holonomic and nonholonomic constraints in the system. An example is provided to illustrate the algorithm's modularity and demonstrate its application. In addition to the development of the dynamic equations, this paper will discuss the implementation of the simulation algorithm in detail, including issues of computational complexity.     

A paris-model approach to modular simulation

The development of complex models can be greatly facilitated by the utilization of libraries of reusable model components. In this paper we describe an object-oriented module specification formalism (MSF) for implementing archivable modules in support of continuous spatial modeling. This declarative formalism provides the high level of abstraction necessary for maximum generality, provides enough detail to allow a dynamic simulation to be generated automatically, and avoids the “hard-coded” implementation of space-time dynamics that makes procedural specifications of limited usefulness for specifying archivable modules. A set of these MSF modules can be hierarchically linked to create a parsimonious model specification, or “parsi-model”. The parsi-model exists within the context of a modeling environment (an integrated set of software tools which provide the computer services necessary for simulation development and execution), which can offer simulation services that are not possible in a loosely-coupled “federated” environment, such as graphical module development and configuration, automatic differentiation of model equations, run-time visualization of the data and dynamics of any variable in the simulation, transparent distributed computing within each module, and fully configurable space-time representations. We believe this approach has great potential for bringing the power of modular model development into the collaborative simulation arena.     

Modules Classification and Automatic Generation of Kinematics on Self-reconfigurable Modular Machines

Self-reconfigurable modular mechanical systems consist of a set of homogeneous units. We analyze the abstract modular structure of self-reconfigurable machines. A total of seven types of cuboid modules and two types of cubic modules have been classified. The concepts of basic group and basic cycle subgroup are proposed. The geometric relationships of each type of modules are derived with group theory. The transformation matrix T _L and other characteristic parameters can be obtained iteratively and simply. For the purpose of automatic generation of the forward kinematics, an approach has been adopted by a series of elemental matrixes multiplication with PME (product of matrix exponentials). The methods used are very general and can be applied easily to other modular robots. Examples of the kinematics for a quadruped and a morphing dual-arm reconfigurable robot are given to demonstrate the applicability and effectiveness of the proposed methods generating the kinematics.     

A novel modular Q-learning architecture to improve performance under incomplete learning in a grid soccer game

Multi-agent reinforcement learning methods suffer from several deficiencies that are rooted in the large state space of multi-agent environments. This paper tackles two deficiencies of multi-agent reinforcement learning methods: their slow learning rate, and low quality decision-making in early stages of learning. The proposed methods are applied in a grid-world soccer game. In the proposed approach, modular reinforcement learning is applied to reduce the state space of the learning agents from exponential to linear in terms of the number of agents. The modular model proposed here includes two new modules, a partial-module and a single-module. These two new modules are effective for increasing the speed of learning in a soccer game. We also apply the instance-based learning concepts, to choose proper actions in states that are not experienced adequately during learning. The key idea is to use neighbouring states that have been explored sufficiently during the learning phase. The results of experiments in a grid-soccer game environment show that our proposed methods produce a higher average reward compared to the situation where the proposed method is not applied to the modular structure.     

Multi-layered interactive energy space modeling for near-optimal electrification of terrestrial,shipboard and aircraft systems

In this paper, we introduce a basic multi-layered modeling framework for posing the problem of safe, robust and efficient design and control that may lend itself to ripping potential benefits from electrification. The proposed framework establishes dynamic relations between physical concepts such as stored energy, useful work, and wasted energy, on one hand; and modeling, simulation, and control of interactive modular complex dynamical systems, on the other. In particular, our recently introduced energy state-space modeling approach for electric energy systems is further interpreted using fundamental laws of physics in multi-physical systems, such as terrestrial energy-systems, aircrafts and ships. The interconnected systems are modeled as dynamically interacting modules. This approach is shown to be particularly well-suited for scalable optimization of large-scale complex systems. Instead of having to use simpler models, the proposed multi-layered modeling of system dynamics in energy space offers a promising basic method for modeling and controlling inter-dependencies across multi-physics subsystems for both ensuring feasible and near-optimal operation. It is illustrated how this approach can be used for understanding fundamental physical causes of inefficiencies created either at the component level or are a result of poor matching of their interactions.     

ANEMONE: An environment for modular ontology development

Many real-world ontologies contain thousands of terms and are developed by multiple participants. The use of monolithic ontologies can cause problems that affect various stages of the ontology life cycle. Thus, there is an urgent need for tools and methodologies that facilitate modular ontology design. The benefits of a modular approach include division of labor, scalability, partial reuse, and broadened participation. This article presents a methodology for modular ontology development. The main idea is to facilitate an interoperable hierarchical network of ontology modules. Modules are designed as a combination of more abstract modules in higher levels of the hierarchy. This methodology differs from previous methodologies in the way that it defines concrete development steps, to facilitate use by both naive and expert ontology developers. This methodology is also supported by ontology design patterns and a prototypical ontology development tool.     

Multiagent control of self-reconfigurable robots

We demonstrate how multiagent systems provide useful control techniques for modular self-reconfigurable (metamorphic) robots. Such robots consist of many modules that can move relative to each other, thereby changing the overall shape of the robot to suit different tasks. Multiagent control is particularly well-suited for tasks involving uncertain and changing environments. We illustrate this approach through simulation experiments of Proteo, a metamorphic robot system currently under development.