Modelling and numerical simulation of technological welding processes is the creative experimental method. Simulation replaces a real system computer model. To create the model can be applied to many experiments under...
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In this presentation, we give an overview of our recent progress in exploiting direct-write two-photon lithography for additive 3D fabrication of freeform micro-optical elements. These elements can be printed with hig...
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In this presentation, we give an overview of our recent progress in exploiting direct-write two-photon lithography for additive 3D fabrication of freeform micro-optical elements. These elements can be printed with highest precision in direct contact with the facets of photonic integrated circuits or optical fibers, thereby greatly simplifying alignment and improving coupling efficiency. The approach offers new perspectives for a wide variety of applications, ranging from advanced photonic multi-chip modules for high-speed communications and optical sensing to highly efficient astro-photonic systems. We are currently working on transferring the concept from laboratory demonstrations to industrial manufacturing.
The application of the flow tracing method to power flows in and out of storage units allows to analyse the usage of this technology option in large-scale interconnected electricity systems. We apply this method to a ...
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In order to perform complex data processing and co-simulation workflows for research on data driven energy systems, a generic, modular and highly scalable process operation framework is presented in this article. This...
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ISBN:
(数字)9781538663981
ISBN:
(纸本)9781538663998
In order to perform complex data processing and co-simulation workflows for research on data driven energy systems, a generic, modular and highly scalable process operation framework is presented in this article. This framework consistently applies web technologies to build up a microservices architecture. It automates the startup, synchronization, and management of scientific data processing and simulation tools (e.g. Python, Matlab, OpenModelica) as part of larger transdisciplinary, multi-domain data processing and co-simulation workflows. It uses container virtualization on the underlying cluster computing environment to control and manage different simulation *** the framework's processing workflow, software executables can be distributed to different nodes on the cluster, easily access data and communicate with other components via communication adapters and a high-performance messaging channel infrastructure. By integrating Apache NiFi, the framework also provides an easy-to-use web user interface to allow users to model, perform and operate workflows for future energy system solutions. As soon as a complex workflow is set up in the process operation framework, researchers can use the workflow without any setup or configuration on their local workstations and without knowing any details of the underlying infrastructure or software environment.
Presented study deals with the formulation of a model of the postural system behavior in the form of transfer function derived from Development Statokinesigram Trajectory (DST). As compared with statokinesigram, a DST...
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The optimal power flow (OPF) problem—i.e., the task to minimize power system operation costs while maintaining technical and network limitations—is key for the operational planning of power systems. The influx of in...
The optimal power flow (OPF) problem—i.e., the task to minimize power system operation costs while maintaining technical and network limitations—is key for the operational planning of power systems. The influx of inherently volatile renewable energy sources calls for methods that allow to consider stochasticity directly in the OPF problem. Modeling uncertainties as second-order continuous random variables, the OPF problem subject to stochastic uncertainties can be posed as an infinite-dimensional L 2 -problem. A tractable and exact reformulation thereof can be obtained using polynomial chaos expansion, under mild assumptions. Polynomial chaos as such is a Hilbert space series expansion for random variables that is frequently employed for uncertainty propagation and uncertainty quantification. Polynomial chaos offers several advantages for OPF subject to stochastic uncertainties. For example, multivariate non-Gaussian uncertainties can be considered straightforwardly. Also, the solutions from polynomial chaos are effectively feedback laws in terms of the realizations of the uncertainty that are determined in a single numerical run.
For his work in the economics of climate change, Professor William Nordhaus was a co-recipient of the 2018 Nobel Memorial Prize for Economic Sciences. A core component of the work undertaken by Nordhaus is the Dynamic...
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The mitigation of climate change requires a fundamental transition of the energy system. Aordability, reliability and the reduction of greenhouse gas emissions constitute central but often conicting targets for this e...
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