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Politik und Wirtschaft sind auf eine fundierte, schnelle und flexible Bewertung der Ver-sorgungssicherheit mit Elektrizität als Grundlage strategischer Entscheidungen angewiesen. Dazu werden komplexe probabilistische Simulationsmodelle unter Einbeziehung einer hohen Anzahl möglicher Zukunftsszenarien verwendet. Allerdings schränken die langen Rechenlaufzeiten von mehreren Stunden pro Szenario die Analysetiefe ein. Zudem werden die Analysen durch die Prognose der zeitlich aufgelösten zukünftigen Randbedingungen erschwert.
Die vorliegende Arbeit zeigt, dass sich mit Methoden aus dem Bereich des Maschinellen Lernens (ML) in Kombination mit angepassten Methoden des Design of Experiments die Kennzahlen der Versorgungssicherheit mit Elektrizität aus einem komplexen Simulationsmodell auf Basis rekursiver Faltungen sehr gut approximieren lassen. Die Zeitreduktion im Vergleich zum nativen Simulationsmodell ist sehr hoch, bei gleichzeitig hoher Genauigkeit. Auch im Bereich der Prognose zeitlich aufgelöster Randbedingungen demonstrieren die Ergebnisse ein erhebliches Verbesserungspotenzial von ML-Methoden im Vergleich zu klassischen Verfahren. Zusammengefasst sind die untersuchten und vorgeschlagenen ML-Methoden in der Lage, die Versorgungssicherheit mit Elektrizität komplexitätsgerecht (tausende von Zukunftsszenarien) in praktikabel kurzer Zeit (weniger als eine Stunde) detailliert zu analysieren.
Lessons Learned: On the Potentials and Challenges of a Model Predictive Controlled DHN Heat Supply
(2023)
Dynamic Sound Sources for Virtual Acoustic Reality: Description, Implementation and Evaluation
(2024)
terns, especially those presented by natural sources such as musical instruments or human voices, is crucial. While static sound sources, such as loudspeakers, have a relatively consistent acoustic footprint, dynamic sources present a multi-faceted set of challenges. Musical instruments, for example, have dynamic radiation patterns. The directivity of these instruments changes not only with frequency, but also with the specific note being played, and with the performer's gestures. These dynamic effects of directivity influences both the perceived loudness and the timbre at a given location within the audience and shapes the spatial characteristics of the sound field produced. This modulation is crucial when recreating authentic acoustic environments, whether in a virtual environment or in real-world architectural designs. Essentially, for an acoustic simulation to be considered accurate, it must capture these nuances. The intricate interplay of directivity, pitch and motion significantly shapes the listening experience and requires deeper integration of these elements into future simulations and designs.
Unlike electro-acoustic sound sources, musical instruments have a time-varying, dynamic directivity, due to the note-dependent radiation behavior of the instrument and due to the expressive movements that musicians perform with their instrument. While previous studies have generally examined the directivity of the static, unmoved instrument for specific notes played, we show the individual and combined contributions of these two factors to a temporal modulation of the radiation behavior, based on motion tracking of typical movement patterns for all instruments of a classical symphony orchestra and on the directivity measured for all partials over the entire pitch range of these instruments. The effect of this modulation, which is manifested by changes in timbre and room acoustic excitation, was determined by spectral variations in the free field and under reverberant conditions, as well as by a modulation of room acoustic parameters. Our results show that these effects are well above the just noticeable differences for all musical instruments and all perceptual variables considered. While the effect of motion dominates for brass instruments, string and woodwind instruments exhibit large note-related differences, which should be taken into account in virtual acoustic realities if an auditory liveliness comparable to physical reality is to be achieved.