73,317 research outputs found
Variational Methods for Biomolecular Modeling
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
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
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
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
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
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
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.
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
- …