VERIFICATION OF A MARINE POLLUTANT SURFACE PLUME MODEL FOR USE IN THE DEVELOPMENT OF AUTONOMOUS VEHICLE TRACKING SYSTEMS

2017 ◽  
Vol 2017 (1) ◽  
pp. 1612-1628
Author(s):  
Laura M. Fitzpatrick ◽  
A Zachary Trimble ◽  
Brian S. Bingham
Keyword(s):  
Control Systems ◽  
Surface Concentration ◽  
Computational Effort ◽  
Computational Time ◽  
Type Model ◽  
Fine Scale ◽  
Multiple Model ◽  
Robotic Control ◽  
Statistical Parameters ◽  
Tuning Parameters

ABSTRACT A marine pollutant spill environmental model that can accurately predict fine scale pollutant concentration variations on a free surface is needed in early stages of testing robotic control systems for tracking pollutant spills. The model must reproduce, for use in a robotic control system simulation environment, the fine-scale surface concentration variations observed by a robot. Furthermore, to facilitate development of robotic control systems, the model must reproduce sample spill distributions in minimal computational time. A combination Eulerian-Lagrangian type model, with two tuning parameters, was developed to produce, with minimal computational effort, the fine scale concentrations that would be observed by a robot. Multiple model scenarios were run with different tuning parameters to determine the effects of those parameters on the model’s ability to reproduce an experimental measured pollutant plume’s structure. A qualitative method for analyzing the concentration variations was established using amplitude and temporal statistical parameters. The differences in the statistical parameters between the model and experiment vary from 69%–316%. After tuning, the model produces a sample spill, which includes a high frequency concentration component not observed in the experimental data, but that generally represents the real-time, fine scale pollutant plume structure and can be used for testing control algorithms.

Replication of left ventricular haemodynamics with a simple planar mitral valve model

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Anna Daub ◽  
Jochen Kriegseis ◽  
Bettina Frohnapfel
Keyword(s):  
Mitral Valve ◽  
Computational Models ◽  
Vortex Formation ◽  
Flow Characteristics ◽  
Left Ventricular ◽  
Computational Effort ◽  
Type Model ◽  
Diastolic Phase ◽  
Valve Model ◽  
Modelling Approach

AbstractTools for the numerical prediction of haemodynamics in multi-disciplinary integrated heart simulations have to be based on computational models that can be solved with low computational effort and still provide physiological flow characteristics. In this context the mitral valve model is important since it strongly influences the flow kinematics, especially during the diastolic phase. In contrast to a 3D valve, a vastly simplified valve model in form of a simple diode is known to be unable to reproduce the characteristic vortex formation and unable to promote a proper ventricular washout. In the present study, an adaptation of the widely used simplest modelling approach for the mitral valve is employed and compared to a physiologically inspired 3D valve within the same ventricular geometry. The adapted approach shows enhanced vortex formation and an improved ventricular washout in comparison to the diode type model. It further shows a high potential in reproducing the main flow characteristics and related particle residence times generated by a 3D valve.

Integrated Redesign of Large-Scale Structures by Large Admissible Perturbations

2003 ◽  
Vol 125 (4) ◽  
pp. 234-241 ◽  
Author(s):  
Vincent Y. Blouin ◽  
Michael M. Bernitsas ◽  
Denby Morrison
Keyword(s):  
Degrees Of Freedom ◽  
Large Scale ◽  
Direct Method ◽  
Computational Effort ◽  
Forced Response ◽  
Response Amplitude ◽  
Computational Time ◽  
Performance Constraints ◽  
Large Admissible Perturbations ◽  
Design Selection

In structural redesign (inverse design), selection of the number and type of performance constraints is a major challenge. This issue is directly related to the computational effort and, most importantly, to the success of the optimization solver in finding a solution. These issues are the focus of this paper, which provides and discusses techniques that can help designers formulate a well-posed integrated complex redesign problem. LargE Admissible Perturbations (LEAP) is a general methodology, which solves redesign problems of complex structures with, among others, free vibration, static deformation, and forced response amplitude constraints. The existing algorithm, referred to as the Incremental Method is improved in this paper for problems with static and forced response amplitude constraints. This new algorithm, referred to as the Direct Method, offers comparable level of accuracy for less computational time and provides robustness in solving large-scale redesign problems in the presence of damping, nonstructural mass, and fluid-structure interaction effects. Common redesign problems include several natural frequency constraints and forced response amplitude constraints at various frequencies of excitation. Several locations on the structure and degrees of freedom can be constrained simultaneously. The designer must exercise judgment and physical intuition to limit the number of constraints and consequently the computational time. Strategies and guidelines are discussed. Such techniques are presented and applied to a 2,694 degree of freedom offshore tower.

scholarly journals Numerical Solution of SDRE Control Problem – Comparison of the Selected Methods

2020 ◽  
Vol 45 (2) ◽  
pp. 79-95
Author(s):  
Krzysztof Hałas ◽  
Eugeniusz Krysiak ◽  
Tomasz Hałas ◽  
Sławomir Stępień
Keyword(s):  
Control Systems ◽  
Riccati Equation ◽  
Computational Effort ◽  
Linear Control ◽  
Algebraic Riccati Equation ◽  
Linear Control Systems ◽  
Nonlinear Constraints ◽  
State Dependent ◽  
Suboptimal Solution ◽  
Problem Comparison

AbstractMethods for solving non-linear control systems are still being developed. For many industrial devices and systems, quick and accurate regulators are investigated and required. The most effective and promising for nonlinear systems control is a State-Dependent Riccati Equation method (SDRE). In SDRE, the problem consists of finding the suboptimal solution for a given objective function considering nonlinear constraints. For this purpose, SDRE methods need improvement.In this paper, various numerical methods for solving the SDRE problem, i.e. algebraic Riccati equation, are discussed and tested. The time of computation and computational effort is presented and compared considering selected nonlinear control plants.

Evaluation of a Multi-Goal Solver for Use in a Blackboard Architecture

2014 ◽  
Vol 6 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Jeremy Straub
Keyword(s):  
Multiple Solutions ◽  
Computational Time ◽  
Problem Analysis ◽  
Robotic Control ◽  
Operating Environment ◽  
Blackboard Architecture ◽  
Rule Based ◽  
Multiple Levels ◽  
Time Required ◽  
Naive Approach

This article presents a multi-goal solver for problems that can be modeled using a Blackboard Architecture. The Blackboard Architecture can be used for data fusion, robotic control and other applications. It combines the rule-based problem analysis of an expert system with a mechanism for interacting with its operating environment. In this context, numerous control or domain (system-subject) problems may exist which can be solved through reaching one of multiple outcomes. For these problems which have multiple solutions, any of which constitutes an end-goal, a solving mechanism which is solution-choice-agnostic and finds the lowest-cost path to the lowest-cost solution is required. Such a solver mechanism is presented and characterized herein. The performance of the solver (including both the computational time required to ascertain a solution and execute it) is compared to the naïve Blackboard approach. This performance characterization is performed across multiple levels of rule counts and rule connectivity. The naïve approach is shown to generate a solution faster, but the solutions generated by this approach, in most cases, are inferior to those generated by the solver.

Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. II. Smoothed intramolecular potentials

2019 ◽  
Vol 75 (3) ◽  
pp. 423-433 ◽  
Author(s):  
Isaac J. Sugden ◽  
Claire S. Adjiman ◽  
Constantinos C. Pantelides
Keyword(s):  
Structure Prediction ◽  
Weighted Average ◽  
Lattice Energy ◽  
Comparative Investigation ◽  
Computational Effort ◽  
Flufenamic Acid ◽  
Computational Time ◽  
Crystal Structure Prediction ◽  
Efficient Representation ◽  
First Time

The application of crystal structure prediction (CSP) to industrially relevant molecules requires the handling of increasingly large and flexible compounds. A revised model for the effect of molecular flexibility on the lattice energy that removes the discontinuities and non-differentiabilities present in earlier models (Sugden et al., 2016), with a view to improving the performance of CSP is presented. The approach is based on the concept of computing a weighted average of local models, and has been implemented within the CrystalPredictor code. Through the comparative investigation of several compounds studied in earlier literature, it is shown that this new model results in large reductions in computational effort (of up to 65%) and in significant increases in reliability. The approach is further applied to investigate, for the first time, the computational polymorphic landscape of flufenamic acid for Z′ = 1 structures, resulting in the successful identification of all three experimentally resolved polymorphs within reasonable computational time.

P.C. Based Robotic Control Systems

1993 ◽  
Vol 26 (2) ◽  
pp. 515-518
Author(s):  
E.R. Fielding ◽  
E.D. Illos
Keyword(s):  
Control Systems ◽  
Robotic Control

A comparison of numerical methods for optimizing even aged stand management

1990 ◽  
Vol 20 (7) ◽  
pp. 961-969 ◽  
Author(s):  
Lauri T. Valsta
Keyword(s):  
Dynamic Programming ◽  
Species Composition ◽  
Random Search ◽  
Optimization Methods ◽  
Global Optimum ◽  
Computational Effort ◽  
Direct Search ◽  
Computational Time ◽  
Discrete State ◽  
Stand Management

A two-species, whole-stand, deterministic growth model was combined with three optimization methods to derive management regimes for species composition, thinnings, and rotation age, with the objective of maximizing soil expectation value. The methods compared were discrete time – discrete state dynamic programming, direct search using the Hooke and Jeeves algorithm, and random search. Optimum solutions for each of the methods varied considerably, required unequal amounts of computational time, and were not equally stable. Dynamic programming located global optimal solutions but did not determine them accurately, owing to discretized state space. Direct search yielded the largest objective function values with comparable computational effort, although the likelihood of finding a global optimum solution was high only for smaller problems with up to two or three thinnings during the rotation. Random search solutions varied considerably with regard to growing stock level and species composition and did not define a consistent management guideline. In general, direct search and dynamic programming appeared to be superior to random search.

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