A spatial operator algebra for manipulator modeling and control

A recently developed spatial operator algebra, useful for modeling, control, and trajectory design of manipulators is discussed. The elements of this algebra are linear operators whose domain and range spaces consist of forces, moments, velocities, and accelerations. The effect of these operators is equivalent to a spatial recursion along the span of a manipulator. Inversion of operators can be efficiently obtained via techniques of recursive filtering and smoothing. The operator algebra provides a high level framework for describing the dynamic and kinematic behavior of a manipulator and control and trajectory design algorithms. The interpretation of expressions within the algebraic framework leads to enhanced conceptual and physical understanding of manipulator dynamics and kinematics. Furthermore, implementable recursive algorithms can be immediately derived from the abstract operator expressions by inspection. Thus, the transition from an abstract problem formulation and solution to the detailed mechanizaton of specific algorithms is greatly simplified. The analytical formulation of the operator algebra, as well as its implementation in the Ada programming language are discussed

An Agent-Based Collaborative Approach to Graphing Causal Maps for Situation Formulation

We provide a background discussion of group support systems (GSS) research into aiding strategic management processes. GSS support for strategic management has been primarily focused on qualitative analysis and the communication processes surrounding strategic planning. While fully developed in common decision-support systems, powerful simulation modeling and quantitative analytical tools have been difficult to integrate into GSS system configurations because they require increased cognitive load and expert modeling support, a central problem now addressed by collaboration engineering. A conceptual and functional bridge is needed to integrate the qualitative and quantitative approaches, reduce cognitive load, and provide modeling support that does not require experts. Acar’s analytical causal mapping is introduced as a structured method for situational formulation and analysis of unstructured strategic problems. This form of causal mapping includes specific processes and analytical approaches offering cognitive modeling support for problem formulation. Its computational capabilities provide support for Systems Thinking approaches in a system easy to learn and use. Using the methodological template of the design science paradigm, we contribute a prototype system for the development and simulation of causal maps that uses RePast 2.0, a Java agent-based modeling (ABM) and simulation library

Sensitivity analysis methods for uncertainty budgeting in system design

Quantification and management of uncertainty are critical in the design of engineering systems, especially in the early stages of conceptual design. This paper presents an approach to defining budgets on the acceptable levels of uncertainty in design quantities of interest, such as the allowable risk in not meeting a critical design constraint and the allowable deviation in a system performance metric. A sensitivity-based method analyzes the effects of design decisions on satisfying those budgets, and a multi-objective optimization formulation permits the designer to explore the tradespace of uncertainty reduction activities while also accounting for a cost budget. For models that are computationally costly to evaluate, a surrogate modeling approach based on high dimensional model representation (HDMR) achieves efficient computation of the sensitivities. An example problem in aircraft conceptual design illustrates the approach.United States. National Aeronautics and Space Administration. Leading Edge Aeronautics Research Program (Grant NNX14AC73A)United States. Department of Energy. Applied Mathematics Program (Award DE-FG02-08ER2585)United States. Department of Energy. Applied Mathematics Program (Award DE-SC0009297

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design

Programmed design of ship forms

This paper describes a new category of CAD applications devoted to the definition and parameterization of hull forms, called programmed design. Programmed design relies on two prerequisites. The first one is a product model with a variety of types large enough to face the modeling of any type of ship. The second one is a design language dedicated to create the product model. The main purpose of the language is to publish the modeling algorithms of the application in the designer knowledge domain to let the designer create parametric model scripts. The programmed design is an evolution of the parametric design but it is not just parametric design. It is a tool to create parametric design tools. It provides a methodology to extract the design knowledge by abstracting a design experience in order to store and reuse it. Programmed design is related with the organizational and architectural aspects of the CAD applications but not with the development of modeling algorithms. It is built on top and relies on existing algorithms provided by a comprehensive product model. Programmed design can be useful to develop new applications, to support the evolution of existing applications or even to integrate different types of application in a single one. A three-level software architecture is proposed to make the implementation of the programmed design easier. These levels are the conceptual level based on the design language, the mathematical level based on the geometric formulation of the product model and the visual level based on the polyhedral representation of the model as required by the graphic card. Finally, some scenarios of the use of programmed design are discussed. For instance, the development of specialized parametric hull form generators for a ship type or a family of ships or the creation of palettes of hull form components to be used as parametric design patterns. Also two new processes of reverse engineering which can considerably improve the application have been detected: the creation of the mathematical level from the visual level and the creation of the conceptual level from the mathematical level. © 2012 Elsevier Ltd. All rights reserved. 1. Introductio

Modeling, simulation, and design criteria for photoelectrochemical water-splitting systems

A validated multi-physics numerical model that accounts for charge and species conservation, fluid flow, and electrochemical processes has been used to analyze the performance of solar-driven photoelectrochemical water-splitting systems. The modeling has provided an in-depth analysis of conceptual designs, proof-of-concepts, feasibility investigations, and quantification of performance. The modeling has led to the formulation of design guidelines at the system and component levels, and has identified quantifiable gaps that warrant further research effort at the component level. The two characteristic generic types of photoelectrochemical systems that were analyzed utilized: (i) side-by-side photoelectrodes and (ii) back-to-back photoelectrodes. In these designs, small electrode dimensions (mm to cm range) and large electrolyte heights were required to produce small overall resistive losses in the system. Additionally, thick, non-permeable separators were required to achieve acceptably low rates of product crossover

Simultaneous mixed-integer disjunctive optimization for synthesis of petroleum refinery topology Processing Alternatives for Naphtha Produced from Atmospheric Distillation Unit

In this work, we propose a logic-based modeling technique within a mixed-integer disjunctive superstructure optimization framework on the topological optimization problem for determining the optimal petroleum refinery configuration. We are interested to investigate the use of logic cuts that are linear inequality/equality constraints to the conceptual process synthesis problem of the design of a refinery configuration. The logic cuts are employed in two ways using 0-l variables: ( l) to enforce certain design specifications based on past design experience, engineering knowledge, and heuristics; and (2) to enforce certain structural specifications on the interconnections of the process units. The overall modeling framework conventionally gives rise to a mixedinteger optimization framework, in this case, a mixed-integer linear programming model (because of the linearity of the constraints). But in this work, we elect to adopt a disjunctive programming framework, specifically generalized disjunctive programming (GDP) proposed by Grossmann and co-workers (Grossmann, l. E. (2002). Review of Nonlinear Mixed-Integer and Disjunctive Programming Techniques. Optimization & Engineering, 3, 227.) The proposed GOP-based modeling technique is illustrated on a case study to determine the optimal processing route of naphtha in a refinery using the GAMS/LogMIP platform, which yields practically-acceptable solution. The use of LogMIP obviates the need to reformulate the logic propositions and the overall disjunctive problem into algebraic representations, hence reducing the time involved in the typically time-consuming problem formulation. LogMIP typically leads to less computational time and number of iterations in its computational effort because the associated GDP formulation involves less equations and variables compared to MILP. From the computational experiments, it is found that logical constraints of design specifications and structural specifications potentially play an important role to determine the optimal selection of process units and streams. Hence, in general, the GDP formulation can be improved by adding or eliminating constraits that can accelerate or slow-down the problem solution respectively

Design for Additive Manufacturing: A Method to Explore Unexplored Regions of the Design Space

Additive Manufacturing (AM) technologies enable the fabrication of parts and devices that are geometrically complex, have graded material compositions, and can be customized. To take advantage of these capabilities, it is important to assist designers in exploring unexplored regions of design spaces. We present a Design for Additive Manufacturing (DFAM) method that encompasses conceptual design, process selection, later design stages, and design for manufacturing. The method is based on the process-structure-property-behavior model that is common in the materials design literature. A prototype CAD system is presented that embodies the method. Manufacturable ELements (MELs) are proposed as an intermediate representation for supporting the manufacturing related aspects of the method. Examples of cellular materials are used to illustrate the DFAM method.Mechanical Engineerin

Integrated Model-Centric Decision Support System for Process Industries

To bring the advances in modeling, simulation and optimization environments (MSOEs), open-software architectures, and information technology closer to process industries, novel mechanisms and advanced software tools must be devised to simplify the definition of complex model-based problems. Synergistic interactions between complementary model-based software tools must be refined to unlock the potential of model-centric technologies in industries. This dissertation presents the conceptual definition of a single and consistent framework for integrated process decision support (IMCPSS) to facilitate the realistic formulation of related model-based engineering problems. Through the integration of data management, simulation, parameter estimation, data reconciliation, and optimization methods, this framework seeks to extend the viability of model-centric technologies within the industrial workplace. The main contribution is the conceptual definition and implementation of mechanisms to ease the formulation of large-scale data-driven/model-based problems: data model definitions (DMDs), problem formulation objects (PFOs) and process data objects (PDOs). These mechanisms allow the definition of problems in terms of physical variables; to embed plant data seamlessly into model-based problems; and to permit data transfer, re-usability, and synergy among different activities. A second contribution is the design and implementation of the problem definition environment (PDE). The PDE is a robust object-oriented software component that coordinates the problem formulation and the interaction between activities by means of a user-friendly interface. The PDE administers information contained in DMD and coordinates the creation of PFOs and PIFs. Last, this dissertation contributes a systematic integration of data pre-processing and conditioning techniques and MSOEs. The proposed process data management system (pDMS) implements such methodologies. All required manipulations are supervised by the PDE, which represents an important advantage when dealing with high volumes of data. The IMCPSS responds to the need for software tools centered in process engineers for which the complexity of using current modeling environments is a barrier for broader application of model-based activities. Consequently, the IMCPSS represents a valuable tool for process industries, as the facilitation of problem formulation is translated into incorporation of plant data in less error-prone manner, maximization of time dedicated to the analysis of processes, and exploitation of synergy among activities based on process models