Component-based Modeling Framework Research Articles

Parallel multi-objective calibration of a component-based river temperature model

Many recent modeling efforts have employed component-based modeling frameworks to take advantage of the flexibility they provide in representing systems more holistically. Despite the benefits that are driving this adoption, conducting model parameter estimation, uncertainty analysis, sensitivity assessment, and other simulations of this nature within component-based modeling frameworks has remained unexplored. Using a multi-objective calibration of a component-based river temperature model, we illustrate how the component cloning and parallel model execution interfaces we have implemented in the HydroCouple framework support such simulations. The river temperature model calibration application we present involves a heavily human mediated 13.6 km section of the Logan River in Utah, USA with limited information regarding variable inflows. Due to the flexibility in the modeling and calibration framework, results from the calibration effort were successful with root mean square errors of 0.4–0.7 °C and provided insights on mechanisms controlling river temperatures.

Advancing the Open Modeling Interface (OpenMI) for integrated water resources modeling

The use of existing component-based modeling frameworks for integrated water resources modeling is currently hampered for some important use cases because they lack support for commonly used, topology-aware, spatiotemporal data structures. Additionally, existing frameworks are often accompanied by large software stacks with steep learning curves. Others lack specifications for deploying them on high performance, heterogeneous computing (HPC) infrastructure. This puts their use beyond the reach of many water resources modelers. In this paper, we describe new advances in component-based modeling using a framework called HydroCouple. This framework largely adopts the Open Modeling Interface (OpenMI) 2.0 interface definitions but demonstrates important advances for water resources modeling. HydroCouple explicitly defines standard and widely used geospatial data formats and provides interface definitions to support simulations on HPC infrastructure. In this paper, we illustrate how these advances can be used to develop efficient model components through a coupled urban stormwater modeling exercise.

Development of a Component-Based Modeling Framework for Agricultural Water-Resource Management

Because hydrologic responses of an agricultural watershed are influenced by many natural and man-made factors including pond/reservoir, management practices, and/or irrigation/drainage, strategies of hydrological modeling for the watershed must be case-dependent and thus carefully designed to effectively reflect their roles as critical hydrologic components in simulation processes. In this study, we propose a component-based modeling framework that accommodates a flexible modeling approach to consider a variety of hydrologic processes and management practices, especially irrigation-reservoir operation and paddy-farming practices, in watershed-scale modeling. The objectives of this study are twofold: to develop a COmponent-based Modeling Framework for Agricultural water-Resources Management (COMFARM) using an object-oriented programming technique, and to evaluate its applicability as a modeling tool to predict the responses of an agricultural watershed characterized with diverse land uses in a case study. COMFARM facilitates quick and easy development of watershed-specific hydrologic models by providing multiple interchangeable simulation routines for each hydrologic component considered. COMFARM is developed with the JAVA programming language, using Eclipse software. The framework developed in this study is applied to simulating hydrologic processes of the Seon-Am irrigation-district watershed consisting primarily of reservoir-irrigated rice paddies in South Korea. The application study clearly demonstrates the applicability of the framework as a convenient method to build models for hydrologic simulation of an agricultural watershed. The newly developed modeling framework, COMFARM is expected to serve as a useful tool in watershed management planning by allowing quick development of case-oriented analysis tools and evaluation of management scenarios customized to a specific watershed.

Towards uncertainty quantification and parameter estimation for Earth system models in a component-based modeling framework

Component-based modeling frameworks make it easier for users to access, configure, couple, run and test numerical models. However, they do not typically provide tools for uncertainty quantification or data-based model verification and calibration. To better address these important issues, modeling frameworks should be integrated with existing, general-purpose toolkits for optimization, parameter estimation and uncertainty quantification.This paper identifies and then examines the key issues that must be addressed in order to make a component-based modeling framework interoperable with general-purpose packages for model analysis. As a motivating example, one of these packages, DAKOTA, is applied to a representative but nontrivial surface process problem of comparing two models for the longitudinal elevation profile of a river to observational data. Results from a new mathematical analysis of the resulting nonlinear least squares problem are given and then compared to results from several different optimization algorithms in DAKOTA.

Compact, Generalized Component Mode Mistuning Representation for Modeling Bladed Disk Vibration

New techniques are presented for generating reduced-order models of the vibration of mistuned bladed disks from parent finite element models. A novel component-based modeling framework is developed by partitioning the system into a tuned bladed disk component and virtual blade mistuning components. The mistuning components are defined by the differences between the mistuned and tuned blade mass and stiffness matrices. The mistuned-system model is assembled with a component mode synthesis technique, using a basis of tuned-system normal modes and attachment modes. The formulation developed is general and can be applied to any mistuned bladed disk, including those with large geometric mistuning (e.g., severe blade damage). In the case of small (i.e., blade frequency) mistuning, a compact reduced-order model is derived by neglecting the attachment modes. For this component mode mistuning model, the blade mistuning is projected first onto the component modes of a tuned, cantilevered blade, and then projected again onto the tuned-system normal modes via modal participation factors. In this manner, several natural frequencies of each mistuned blade can be used to capture systematically the effects of the complex physical sources of mistuning. A numerical validation of the developed methods is performed for both large and small mistuning cases using a finite element model of an industrial rotor.

A component-based approach to modeling and simulating mixed-signal and hybrid systems

Systems with both continuous and discrete behaviors can be modeled using a mixed-signal style or a hybrid systems style. This article presents a component-based modeling and simulation framework that supports both modeling styles. The component framework, based on an actor metamodel, takes a hierarchical approach to manage heterogeneity in modeling complex systems. We describe how ordinary differential equations, discrete event systems, and finite-state machines can be built under this metamodel. A mixed-signal system is a hierarchical composition of continuous-time and discrete event models, and a hybrid system is a hierarchical composition of continuous-time and finite-state-machine models. Hierarchical composition and information hiding help build clean models and efficient execution engines. Simulation technologies, in particular, the interaction between a continuous-time ODE solving engine and various discrete simulation engines are discussed. A signal type system is introduced to schedule hybrid components inside a continuous-time environment. Breakpoints are used to control the numerical integration step sizes so that discrete events are handled properly. A "refiring" mechanism and a "rollback" mechanism are designed to manage continuous components inside a discrete event environment. The technologies are implemented in the Ptolemy II software environment. Examples are given to show the applications of this framework in mixed-signal and hybrid systems.

Exploring component-based approaches in forest landscape modeling

Forest management issues are increasingly required to be addressed in a spatial context, which has led to the development of spatially explicit forest landscape models. The numerous processes, complex spatial interactions, and diverse applications in spatial modeling make the development of forest landscape models difficult for any single research group. New developments in component-based modeling approaches provide a viable solution. Component-based modeling breaks a monolithic model into small, interchangeable, and binary components. They have these advantages compared to the traditional modeling work: 1) developing a component is a much smaller task than developing a whole model, 2) a component can be developed using most programming languages, since the interface format is binary, and 3) new components can replace the existing ones under the same model framework; this reduces the duplication and allows the modeling community to focus resources on the common products, and to compare results. In this paper, we explore the design of a spatially explicit forest landscape model in a component-based modeling framework, based on our work on object-oriented forest landscape modeling. We examine the representation of the major components and the interactions between them. Our goal is to facilitate the use of the component-based modeling approach at the early stage of spatially explicit landscape modeling.