73,317 research outputs found

    Variational Methods for Biomolecular Modeling

    Full text link
    Structure, function and dynamics of many biomolecular systems can be characterized by the energetic variational principle and the corresponding systems of partial differential equations (PDEs). This principle allows us to focus on the identification of essential energetic components, the optimal parametrization of energies, and the efficient computational implementation of energy variation or minimization. Given the fact that complex biomolecular systems are structurally non-uniform and their interactions occur through contact interfaces, their free energies are associated with various interfaces as well, such as solute-solvent interface, molecular binding interface, lipid domain interface, and membrane surfaces. This fact motivates the inclusion of interface geometry, particular its curvatures, to the parametrization of free energies. Applications of such interface geometry based energetic variational principles are illustrated through three concrete topics: the multiscale modeling of biomolecular electrostatics and solvation that includes the curvature energy of the molecular surface, the formation of microdomains on lipid membrane due to the geometric and molecular mechanics at the lipid interface, and the mean curvature driven protein localization on membrane surfaces. By further implicitly representing the interface using a phase field function over the entire domain, one can simulate the dynamics of the interface and the corresponding energy variation by evolving the phase field function, achieving significant reduction of the number of degrees of freedom and computational complexity. Strategies for improving the efficiency of computational implementations and for extending applications to coarse-graining or multiscale molecular simulations are outlined.Comment: 36 page

    The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems

    Full text link
    Scenario-based testing for the safety validation of highly automated vehicles is a promising approach that is being examined in research and industry. This approach heavily relies on data from real-world scenarios to derive the necessary scenario information for testing. Measurement data should be collected at a reasonable effort, contain naturalistic behavior of road users and include all data relevant for a description of the identified scenarios in sufficient quality. However, the current measurement methods fail to meet at least one of the requirements. Thus, we propose a novel method to measure data from an aerial perspective for scenario-based validation fulfilling the mentioned requirements. Furthermore, we provide a large-scale naturalistic vehicle trajectory dataset from German highways called highD. We evaluate the data in terms of quantity, variety and contained scenarios. Our dataset consists of 16.5 hours of measurements from six locations with 110 000 vehicles, a total driven distance of 45 000 km and 5600 recorded complete lane changes. The highD dataset is available online at: http://www.highD-dataset.comComment: IEEE International Conference on Intelligent Transportation Systems (ITSC) 201

    GEANT4 : a simulation toolkit

    Get PDF
    Abstract Geant4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics. PACS: 07.05.Tp; 13; 2

    Model development and simulating of a spinning cone evaporator : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology at Institute of Technology and Engineering, Massey University, Palmerston North, New Zealand

    Get PDF
    The idea of milk pre-concentration at the farm has attracted worldwide interest for many years. A new pilot-scale evaporator (called spinning cone evaporator), which can be operated on the farm and has a compact and efficient design, has been developed at Massey University. However, there is a shortage of knowledge on the design, operation and control of this new evaporator. The main goal of this thesis is to develop a dynamic mathematical model in order to better utilize this evaporator and make further developments. This thesis consists of three parts. Firstly, a first-principles model of a pilot scale spinning cone evaporator is developed using the sub-system modelling techniques of the evaporator from the Laws of Thermodynamics and the general mass and energy balances. The model is dynamic and includes the evaporator, the compressor, the condenser and the product transport sections. The system model describes the dynamic relationships between the input variables (cooling water flowrate, M c , speed of compressor, N comp , feed flowrate, M f , feed temperature, T f and mass composition of feed dry matter, W f ) and the output variables (outlet temperature of cooling water, T co , evaporating temperature, T e , mass composition of product dry matter, w p and product flowrate, M p ), Secondly, the evaporator model was implemented using the software package Matlab along with its dynamic simulation environment Simulink. The differential equations for the evaporator model are embedded in a block diagram representation of the evaporator system. The evaporator Simulink model is divided into three levels, the blocks at the top represent the overall model and global constants used in it. The second level contains the individual sub-systems and the bottom level elements within each sub-system. Results of the model verification are satisfactory. Finally, the model validation is presented for both steady state and dynamic comparisons. The product flowrate (except in the case of feed temperature changes) and evaporation temperature can be predicted at a given time, and the outlet temperature of cooling water and product dry matter composition can also be predicted at a steady state. It can be seen that the results predicted using this spinning cone evaporator model, which accounts for the varying concentrate flowrate and evaporation temperature with time, are in good agreement with experimental data. This model provides a valuable tool to predict performance in a spinning cone evaporator and to modify the design parameters

    The role of learning on industrial simulation design and analysis

    Full text link
    The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

    Aeronautical Engineering: A special bibliography with indexes, supplement 62

    Get PDF
    This bibliography lists 306 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1975

    Modeling structural change in spatial system dynamics: A Daisyworld example

    Get PDF
    System dynamics (SD) is an effective approach for helping reveal the temporal behavior of complex systems. Although there have been recent developments in expanding SD to include systems' spatial dependencies, most applications have been restricted to the simulation of diffusion processes; this is especially true for models on structural change (e.g. LULC modeling). To address this shortcoming, a Python program is proposed to tightly couple SD software to a Geographic Information System (GIS). The approach provides the required capacities for handling bidirectional and synchronized interactions of operations between SD and GIS. In order to illustrate the concept and the techniques proposed for simulating structural changes, a fictitious environment called Daisyworld has been recreated in a spatial system dynamics (SSD) environment. The comparison of spatial and non-spatial simulations emphasizes the importance of considering spatio-temporal feedbacks. Finally, practical applications of structural change models in agriculture and disaster management are proposed

    A Review of Traffic Signal Control.

    Get PDF
    The aim of this paper is to provide a starting point for the future research within the SERC sponsored project "Gating and Traffic Control: The Application of State Space Control Theory". It will provide an introduction to State Space Control Theory, State Space applications in transportation in general, an in-depth review of congestion control (specifically traffic signal control in congested situations), a review of theoretical works, a review of existing systems and will conclude with recommendations for the research to be undertaken within this project
    corecore