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Ϯ͘ ŝĂŵĞƚĞƌƐƉĞĐƚƌĂůƌĞĨůĞĐƚŝǀŝƚǇŝƐĚĞƌŝǀĞĚƵƐŝŶŐǀƚ;ͿĂĐŚŝĞǀĞĚďǇWĂƌƐŝǀĞůŽďƐĞƌǀĂƚŝŽŶƐ͗߲‫ݒ‬௧ߟ௄ ሺ‫ܦ‬ሻ ൌ ߟ௄ ሺ‫ݒ‬ሻ߲‫ܦ‬ϯ͘ W^ŝƐŽďƚĂŝŶĞĚďǇĚŝǀŝĚŝŶŐɻďǇʍ;Ϳ͕ĂŶĚŝƚŝƐŝŶĚĞƉĞŶĚĞŶƚŽĨƚŚĞƌĂĚĂƌǁĂǀĞůĞŶŐƚŚ͗ܰሺ‫ܦ‬ሻ ൌߟ௄ ሺ‫ܦ‬ሻ ߟௐ ሺ‫ܦ‬ሻൌߪ௄ ሺ‫ܦ‬ሻ ߪௐ ሺ‫ܤ‬ሻϰ͘ ŽŵďŝŶŐƉƌĞǀŝŽƵƐĞƋƵĂƚŝŽŶƐ͗ߟௐ ሺ‫ܦ‬ሻ ߟ௄ ሺ‫ܦ‬ሻ ߟ௄ ሺ‫ݒ‬ሻ ߲‫ݒ‬ൌൌߪௐ ሺ‫ܦ‬ሻ ߪ௄ ሺ‫ܦ‬ሻ ߪ௄ ሺ‫ܦ‬ሻ ߲‫ܦ‬ϱ͘ KďƚĂŝŶŝŶŐ͗ߟௐ ሺ‫ݒ‬ሻ ൌ ߟ௄ ሺ‫ݒ‬ሻߪௐ ሺ‫ܦ‬ሻߪ௄ ሺ‫ܦ‬ሻdŚĞƚĞƌŵŽŶƚŚĞƌŝŐŚƚŚĂƐŵĞĂƐƵƌĞŵĞŶƚƐĨƌŽŵDZZĂŶĚƚŚĞƌĂƚŝŽŽĨďĂĐŬƐĐĂƚƚĞƌŝŶŐĐƌŽƐƐƐĞĐƚŝŽŶĨŽƌĂŐŝǀĞŶĚŝĂŵĞƚĞƌĂŶĚĂŐŝǀĞŶĐůĂƐƐŽĨƉĂƌƚŝĐůĞdŚĞŵĞƚŚŽĚĐĂŶďĞĞǆƚĞŶĚĞĚĂůƐŽƚŽĂŶǇƚĂƌŐĞƚďĂŶĚ͕ƐƵĐŚĂƐ<Ă͘ƉƉůŝĐĂƚŝŽŶŽĨ<ϮtƚŽƚŚĞEǇůĞƐƵŶĚĂƚĂƐĞƚdŚĞĚĂƚĂƵƐĞĚŚĂǀĞďĞĞŶĐŽůůĞĐƚĞĚĚƵƌŝŶŐƚŚĞǁŝŶƚĞƌͬƐƉƌŝŶŐƐĞĂƐŽŶƐϮϬϭϴĂƚƚŚĞt/Ws&ƌĞŶĐŚͲ'ĞƌŵĂŶƌĐƚŝĐƌĞƐĞĂƌĐŚďĂƐĞŝŶƚŚĞEŽƌǁĞŐŝĂŶĂƌĐŚŝƉĞůĂŐŽŽĨ^ǀĂůďĂƌĚ͕ƐƉĞĐŝĨŝĐĂůůǇŝŶƚŚĞǀŝůůĂŐĞŽĨEǇͲ ůĞƐƵŶĚ;ĨƌŽŵ ŶŽǁ ŽŶ EǇͿ ;ĐŽŽƌĚŝŶĂƚĞƐ ϳϴ͘ϵE͕ ϭϭ͘ϵ͕ ϵŵ Ă͘Ɛ͘ů͘Ϳ ůŽĐĂƚĞĚ ĂůŽŶŐ ƚŚĞ <ŽŶŐƐĨũŽƌĚ͕ ŶĞƐƚůĞĚ ŶĞĂƌŵŽƵŶƚĂŝŶƐ ƚŚĂƚ ƌƵŶ ƉĂƌĂůůĞů ƚŽ ƚŚĞ ĨũŽƌĚ ĨƌŽŵ ƚŚĞ ŶŽƌƚŚǁĞƐƚ ƚŽ ƚŚĞ ƐŽƵƚŚĞĂƐƚ͘ dŚĞ ŽďƐĞƌǀĂƚŝŽŶƐ ŽĨ ϯĚŝĨĨĞƌĞŶƚ ƐŶŽǁĨĂůů ĞǀĞŶƚƐ ;ϳ &ĞďƌƵĂƌǇ͕ϭϲDĂƌĐŚ͕ ĂŶĚ ϭϲ ƉƌŝůͿ ĂƌĞ ĂǀĂŝůĂďůĞ ƚŽƚŚĞ ƉƵďůŝĐ ƚŚƌŽƵŐŚƚŚĞĞŶŽĚŽƌĞƉŽƐŝƚŽƌǇĂŶĚĐŽŶƚĂŝŶŵĞĂƐƵƌĞŵĞŶƚƐŽĨƚŚĞ<ͲďĂŶĚDZZ͕ƚŚĞtͲďĂŶĚƌĂĚĂƌDŝZͲ;ĨƌŽŵŶŽǁŽŶ DŝƌĂͿ ŵĂŶƵĨĂĐƚƵƌĞĚ ďǇ ZW' ZĂĚŝŽŵĞƚĞƌ WŚǇƐŝĐƐ 'ŵď,͕ ĂŶĚ ŽĨ ƚŚĞ KddͲWĂƌƐŝǀĞů ĚŝƐĚƌŽŵĞƚĞƌ͘ dŚĞĂƐƐĞƐƐŵĞŶƚŽĨ<ϮtŝƐĐŽŶĚƵĐƚĞĚĂŐĂŝŶƐƚĂĐŽůůŽĐĂƚĞĚŐƌŽƵŶĚͲďĂƐĞĚϵϰƌĂĚĂƌƚŚƌŽƵŐŚƚŚĞĨŽůůŽǁŝŶŐƐƚĞƉƐ͗ĂͿ ^ŶŽǁWĂƌƚŝĐůĞůĂƐƐŝĨŝĐĂƚŝŽŶ͗^ŶŽǁƉĂƌƚŝĐůĞƐǁĞƌĞĐůĂƐƐŝĨŝĞĚĂƐĂŐŐƌĞŐĂƚĞŽƌƉƌŝƐƚŝŶĞďǇĐŽŵƉĂƌŝŶŐ
DZZƌĂĚĂƌƌĞĨůĞĐƚŝǀŝƚǇǁŝƚŚƌĂĚĂƌƐŝŵƵůĂƚŝŽŶƐĚĞƌŝǀĞĚĨƌŽŵĚŝƐĚƌŽŵĞƚĞƌĚĂƚĂĂŶĚĂĚĂƚĂďĂƐĞ͖ďͿ sĞůŽĐŝƚǇͲŝĂŵĞƚĞƌZĞůĂƚŝŽŶƐŚŝƉ͗ŝƐĚƌŽŵĞƚĞƌĚĂƚĂǁĞƌĞĂŶĂůǇǌĞĚƚŽĞƐƚĂďůŝƐŚǀĞůŽĐŝƚǇͲĚŝĂŵĞƚĞƌƌĞůĂƚŝŽŶƐŚŝƉƐĨŽƌƚŚĞǀĂƌŝŽƵƐƐŶŽǁĨĂůůĞǀĞŶƚƐĂŶĚĚŝĨĨĞƌĞŶƚƚŝŵĞǁŝŶĚŽǁƐ͖ĐͿ ƉƉůŝĐĂƚŝŽŶ͗ ƋƵĂƚŝŽŶƐ ĚĞƐĐƌŝďĞĚ ĂďŽǀĞ ǁĞƌĞ ĂƉƉůŝĞĚ ƚŽ DZZ ŽƉƉůĞƌ ƐƉĞĐƚƌĂ͕ ǁŝƚŚ ǀĞůŽĐŝƚǇͲĚŝĂŵĞƚĞƌƌĞůĂƚŝŽŶƐŚŝƉƐĚĞƌŝǀĞĚĨƌŽŵĚŝƐĚƌŽŵĞƚĞƌĚĂƚĂ͕ƚŚĞƐĐĂƚƚĞƌŝŶŐĚĂƚĂďĂƐĞ͕ĂŶĚƐŶŽǁĨĂůůƉĂƌƚŝĐůĞĐůĂƐƐŝĨŝĐĂƚŝŽŶŽďƚĂŝŶĞĚŝŶƐƚĞƉĂͿ͖ĚͿ ŽŵƉĂƌŝƐŽŶŽĨZĞƐƵůƚƐ͗dŚĞƌĞƐƵůƚŝŶŐ<ϮtƌĞĨůĞĐƚŝǀŝƚǇǀĂůƵĞƐǁĞƌĞĐŽŵƉĂƌĞĚǁŝƚŚŵĞĂƐƵƌĞĚtͲďĂŶĚƌĞĨůĞĐƚŝǀŝƚǇĂƚƚŚĞĨŝƌƐƚƌĞůŝĂďůĞƌĂŶŐĞŐĂƚĞ;ŝ͘Ğ͕͘ϵϬŵ'>ĨŽƌDZZĂŶĚϭϬϱŵ'>ĨŽƌDŝƌĂͿ͘ZĞƐƵůƚƐ&ŝŐ͘ϭĂ͕ϭď͕ĂŶĚϭĐĚĞƉŝĐƚƚŚĞŽƵƚĐŽŵĞƐŽĨƚŚŝƐĐŽŶǀĞƌƐŝŽŶŵĞƚŚŽĚŽůŽŐǇĨŽƌƚŚĞƚŚƌĞĞƐŶŽǁĨĂůůĞǀĞŶƚƐĂŶĚĨŽƌĂƚŝŵĞǁŝŶĚŽǁŽĨϯϬŵŝŶƵƚĞƐ͘/ƚŝƐŝŵƉŽƌƚĂŶƚƚŽŶŽƚĞƚŚĂƚƚŚĞƚŝŵĞǁŝŶĚŽǁƌĞĨĞƌƐƚŽƚŚĞƚŝŵĞŝŶƚĞƌǀĂůĐŽŶƐŝĚĞƌĞĚĨŽƌĚĞƌŝǀŝŶŐƚŚĞǀĞůŽĐŝƚǇͲĚŝĂŵĞƚĞƌƌĞůĂƚŝŽŶƐŚŝƉƐĨƌŽŵWĂƌƐŝǀĞůŵĞĂƐƵƌĞŵĞŶƚƐ͘/ƚŝƐǁĞůůͲŬŶŽǁŶƚŚĂƚ ƐĞǀĞƌĂů ĨĂĐƚŽƌƐ͕ ǁŝƚŚ ǁŝŶĚ ďĞŝŶŐ ƚŚĞ ŵŽƐƚ ƐŝŐŶŝĨŝĐĂŶƚ͕ ĐĂŶ ĂĚǀĞƌƐĞůǇ ĂĨĨĞĐƚ ƚŚĞ ƌĞůŝĂďŝůŝƚǇ ŽĨ ůĂƐĞƌĚŝƐĚƌŽŵĞƚĞƌƉĞƌĨŽƌŵĂŶĐĞĂŶĚƵƚŝůŝǌŝŶŐĂƉƉƌŽƉƌŝĂƚĞƚŝŵĞǁŝŶĚŽǁƐŝƐĞǆƉĞĐƚĞĚƚŽĞŶŚĂŶĐĞƚŚĞƌŽďƵƐƚŶĞƐƐŽĨǀĞůŽĐŝƚǇͲĚŝĂŵĞƚĞƌƌĞƚƌŝĞǀĂů͕ĂŝŵŝŶŐƚŽŵŝƚŝŐĂƚĞďŽƚŚĐŚĂŶŐĞƐŝŶƐŶŽǁĨůĂŬĞĐŚĂƌĂĐƚĞƌŝƐƚŝĐƐĂŶĚƐƚƌŽŶŐǁŝŶĚƐ ůĞĂĚŝŶŐ ǀĂƌŝĂďŝůŝƚǇ ŝŶ ƐŶŽǁĨĂůů ĞƐƚŝŵĂƚŝŽŶ ďǇ ĚŝƐĚƌŽŵĞƚĞƌƐ͘ ĂĐŚ ĐŽŵƉĂƌĂƚŝǀĞ ƉůŽƚ ŝŶĐůƵĚĞƐ ƚŝŵĞƐĞƌŝĞƐŽĨƚŚĞŵĞĂƐƵƌĞĚDZZ<ͲďĂŶĚƌĞĨůĞĐƚŝǀŝƚǇĂƚϵϬŵ'>͕ƚŚĞŵĞĂƐƵƌĞĚtͲďĂŶĚƌĞĨůĞĐƚŝǀŝƚǇďǇDŝƌĂĂƚϭϬϮŵ'>͕ĂŶĚƚŚĞtϮtĞƐƚŝŵĂƚĞĚtͲďĂŶĚƌĞĨůĞĐƚŝǀŝƚǇ͘dŚĞĐŽŶǀĞƌƐŝŽŶŵĞƚŚŽĚŽůŽŐǇĂƉƉĞĂƌƐƚŽƉĞƌĨŽƌŵǁĞůů͕ŽĨƚĞŶĂĐĐƵƌĂƚĞůǇŵŝŵŝĐŬŝŶŐƚŚĞtͲďĂŶĚŽďƐĞƌǀĂƚŝŽŶƐĂůƚŚŽƵŐŚ<ϮtĨƌĞƋƵĞŶƚůǇĨĂŝůƐƚŽƌĞƉůŝĐĂƚĞƚŚĞtͲďĂŶĚƌĞĨůĞĐƚŝǀŝƚǇ͕ǁŝƚŚƚŚĞƌĞĨůĞĐƚŝǀŝƚŝĞƐĂůŵŽƐƚƉĞƌĨĞĐƚůǇƐƵƉĞƌŝŵƉŽƐĞĚǁŝƚŚĞDZZ͕ŝŶĚŝĐĂƚŝŶŐŝŵƉĞƌĨĞĐƚŽƉĞƌĂƚŝŽŶŽĨ<Ϯt͘dǁŽĨĂĐƚŽƌƐĐŽƵůĚŚĂǀĞƉůĂǇĞĚĂĐƌŝƚŝĐĂůƌŽůĞ͗ƐƚƌŽŶŐǁŝŶĚƐĂĨĨĞĐƚŝŶŐWĂƌƐŝǀĞůŽďƐĞƌǀĂƚŝŽŶƐĂŶĚĐĂůŝďƌĂƚŝŽŶŝƐƐƵĞƐ ǁŝƚŚ ƚŚĞ DŝƌĂ͘ ^ƚƌŽŶŐ ǁŝŶĚƐ ĂŶĚ ƚŚĞ ŐĞŽŵĞƚƌǇ ŽĨ ƚŚĞ ŝŶƐƚƌƵŵĞŶƚ ĂĨĨĞĐƚƐ ĚŝƐĚƌŽŵĞƚĞƌŵĞĂƐƵƌĞŵĞŶƚƐ͕ůĞĂĚŝŶŐƚŽǁŽƌƐĞŶƚŚĞƋƵĂůŝƚǇŽĨŽďƐĞƌǀĂƚŝŽŶƐ͘hŶĨŽƌƚƵŶĂƚĞůǇ͕ǁŝŶĚŽďƐĞƌǀĂƚŝŽŶƐǁĞƌĞŶŽƚĂǀĂŝůĂďůĞĨŽƌƚŚĞEǇůĞƐƵŶĚĐĂƐĞƐ͕ĂŶĚƚŚŝƐĂƐƉĞĐƚĐŽƵůĚŶŽƚďĞĨƵƌƚŚĞƌŵŝƚŝŐĂƚĞĚ͘/ŶƐƚĞĂĚ͕ƚŚĞƉŽƐƐŝďůĞĐĂůŝďƌĂƚŝŽŶŝƐƐƵĞŚĂƐďĞĞŶƚŚŽƌŽƵŐŚůǇŝŶǀĞƐƚŝŐĂƚĞĚ͘ĐŽŵƉĂƌŝƐŽŶďĞƚǁĞĞŶƌĂĚĂƌƌĞĨůĞĐƚŝǀŝƚǇŵĞĂƐƵƌĞĚďǇ
D/ZĂŶĚƚŚĂƚĚĞƌŝǀĞĚĨƌŽŵĚŝƐĚƌŽŵĞƚĞƌŽďƐĞƌǀĂƚŝŽŶƐĂŶĚĚĂƚĂďĂƐĞĨŽƌtͲďĂŶĚƌĞǀĞĂůĞĚĂĐŽŶƐƚĂŶƚƵŶĚĞƌĞƐƚŝŵĂƚŝŽŶŽĨƚŚĞDŝƌĂǀĂůƵĞƐĨŽƌƚŚĞϯĚĂǇƐĐŽŶƐŝĚĞƌĞĚ͘dŚŝƐŝƐĐŽŶƐŝƐƚĞŶƚǁŝƚŚŚĞůůŝŶŝĞƚĂů͘;ĂƌƚŚ^ǇƐƚĞŵ^ĐŝĞŶĐĞĂƚĂ͕ϮϬϮϯͿǁŚŝĐŚƌĞƉŽƌƚƐĐĂůŝďƌĂƚŝŽŶŽĨĨƐĞƚǀĂůƵĞƐĨŽƌDŝƌĂĂƚEǇŽĨĂďŽƵƚϯĚĨŽƌƚŚĞŵŽŶƚŚƐŽĨ&ĞďƌƵĂƌǇ͕DĂƌĐŚĂŶĚƉƌŝůϮϬϭϴ͕ĐŽŶĨŝƌŵŝŶŐŽƵƌŝŶƚĞƌƉƌĞƚĂƚŝŽŶ͘^ƵĐŚǀĂůƵĞŝƐĐŽŶƐŝƐƚĞŶƚǁŝƚŚǁŚĂƚǁĞŚĂǀĞĨŽƵŶĚŝŶƚŚĞĞDŝƌĂĂŶĚĞWĂƌƐŝǀĞůĐŽŵƉĂƌŝƐŽŶ͘
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Figure 1 – Time series of radar reflectivity for the 3 case studies: the black line represents K-band reflectivity(ZeMRR), the red line represents W-band reflectivity (ZeMira), and the yellow line depicts converted W-bandreflectivity (ZeK2W).

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Figure 2 – Density scatter plot between ZeMira at 102 ma.g.l. (after calibration correction) and converted ZeK2W at
90 m AGL. Dots are colored according to the density ofdata (dark red = high density, dark blue = low density),
whereas the dotted line stands for the bisecting lineŽŶĐůƵƐŝŽŶƐ^ĂƚĞůůŝƚĞŽďƐĞƌǀĂƚŝŽŶƐĨƌŽŵŵŝƐƐŝŽŶƐůŝŬĞůŽƵĚ^ĂƚĂŶĚĂƌƚŚZ͕ĞƋƵŝƉƉĞĚǁŝƚŚtͲďĂŶĚWZ͕ĂƌĞĐƌƵĐŝĂůĨŽƌŐůŽďĂůƉƌĞĐŝƉŝƚĂƚŝŽŶĞƐƚŝŵĂƚŝŽŶĚƵĞƚŽƚŚĞŝƌĂďŝůŝƚǇƚŽĐŽǀĞƌǀĂƐƚĂƌĞĂƐ͘ŬĞǇĂƐƉĞĐƚŽĨƐĂƚĞůůŝƚĞŵŝƐƐŝŽŶƐŝƐƚŚĞǀĂůŝĚĂƚŝŽŶĂŶĚĐĂůŝďƌĂƚŝŽŶŽĨŵĞĂƐƵƌĞŵĞŶƚƐ͕ǁŚŝĐŚƌĞůŝĞƐŽŶŝŶĚĞƉĞŶĚĞŶƚŵĞĂƐƵƌĞŵĞŶƚƐƚǇƉŝĐĂůůǇĐŽůůĞĐƚĞĚďǇŐƌŽƵŶĚͲďĂƐĞĚŽďƐĞƌǀĂƚŝŽŶĂůƐŝƚĞƐ͘^ĞǀĞƌĂůƐƚĂƚŝŽŶƐŝŶŶƚĂƌĐƚŝĐĂĂƌĞĞƋƵŝƉƉĞĚǁŝƚŚĂDZZ<ͲďĂŶĚƉƌŽĨŝůĞƌĂŶĚĂĚŝƐĚƌŽŵĞƚĞƌ͕ƚŚĞ<ϮtŵĞƚŚŽĚŽůŽŐǇĞŶŚĂŶĐĞƚŚĞŽƉƉŽƌƚƵŶŝƚŝĞƐƚŽǀĂůŝĚĂƚĞϵϰ',ǌƌĂĚĂƌŵĞĂƐƵƌĞŵĞŶƚƐ͘<ϮtƐŝŵƵůĂƚĞƐtͲďĂŶĚƉƌŽĨŝůĞƐƵƐŝŶŐ<ͲďĂŶĚŽƉƉůĞƌ^ƉĞĐƚƌĂĂŶĚǀ;ͿƌĞůĂƚŝŽŶƐŚŝƉƐĨƌŽŵĚŝƐĚƌŽŵĞƚĞƌŽďƐĞƌǀĂƚŝŽŶƐůĞĂĚŝŶŐƚŽĚŝƌĞĐƚĐŽŵƉĂƌŝƐŽŶǁŝƚŚWZĚĂƚĂ͘dŚĞĞĨĨĞĐƚŝǀĞŶĞƐƐŽĨ<ϮtŝƐĞǀĂůƵĂƚĞĚĂŐĂŝŶƐƚĂŐƌŽƵŶĚͲďĂƐĞĚtͲďĂŶĚƌĂĚĂƌŝŶEǇ ůĞƐƵŶĚ͕ďƵŝůĚŝŶŐƵƉŽŶƚŚĞŽƌŝŐŝŶĂůĐŽŵƉĂƌŝƐŽŶĐŽŶĚƵĐƚĞĚĚƵƌŝŶŐĂůŽƵĚ^ĂƚŽǀĞƌƉĂƐƐŽǀĞƌƚŚĞDĂƌŝŽƵĐĐŚĞůůŝ^ƚĂƚŝŽŶŝŶŶƚĂƌĐƚŝĐĂ͘ZĞƐƵůƚƐŝŶĚŝĐĂƚĞƚŚĂƚĞǀĞŶŝĨĚŝƐĚƌŽŵĞƚĞƌĚĂƚĂĐŽƵůĚŶŽƚďĞĐŽƌƌĞĐƚĞĚĨŽƌǁŝŶĚĂƌƚŝĨĂĐƚƐ;ĂƐƌĞĐŽŵŵĞŶĚĞĚďǇ<ϮtͿ͕ƚŚĞĐŽŵƉĂƌŝƐŽŶďĞƚǁĞĞŶĞ;<ϮtͿĂŶĚĞ;DŝƌĂͿĂƚƚŚĞĨŝƌƐƚƵƐĞĨƵůƌĂŶŐĞŐĂƚĞƐŚŽǁƐƉƌŽŵŝƐŝŶŐƌĞƐƵůƚƐ ƉƌŽǀŝĚĞĚ ƚŚĂƚ ƚŚĞ DŝƌĂ ĐĂůŝďƌĂƚŝŽŶ ŝƐƐƵĞ ŝƐ ĂĚĚƌĞƐƐĞĚ͕ ƚŚŝƐ ĐŽŶĨŝƌŵŝŶŐ ƚŚĞ ĨĞĂƐŝďŝůŝƚǇ ĂŶĚ ƚŚĞĞĨĨĞĐƚŝǀĞŶĞƐƐŽĨ<Ϯt͘>ŝƐƚŽĨƉƵďůŝĐĂƚŝŽŶƐ:ŽƵƌŶĂůƉĂƉĞƌƌĂĐĐŝ͕ <͘ ^ĂƚŽ͕ >͘ ĂůĚŝŶŝ͕&͘ WŽƌĐƶ͕ ,͘ KŬĂŵŽƚŽ͕ ϮϬϮϯ͗ ĞǀĞůŽƉŵĞŶƚ ŽĨ Ă ŵĞƚŚŽĚŽůŽŐǇ ĨŽƌ ĞǀĂůƵĂƚŝŶŐƐƉĂĐĞďŽƌŶĞtͲďĂŶĚŽƉƉůĞƌƌĂĚĂƌďǇĐŽŵďŝŶĞĚƵƐĞŽĨDŝĐƌŽZĂŝŶZĂĚĂƌĂŶĚĂĚŝƐĚƌŽŵĞƚĞƌŝŶŶƚĂƌĐƚŝĐĂZĞŵŽƚĞ^ĞŶƐŝŶŐŽĨƚŚĞŶǀŝƌŽŶŵĞŶƚ͕Ϯϵϯ͕ϭϭϯϲϯϬ͕ϮϬϮϯ͘K/͗ϭϬ͘ϭϬϭϲͬũ͘ƌƐĞ͘ϮϬϮϯ͘ϭϭϯϲϯϬ^ƵŵŵĂƌǇƉĂƉĞƌƌĂĐĐŝ͕<͘^ĂƚŽ͕>͘ĂůĚŝŶŝ͕,͘KŬĂŵŽƚŽ͕ϮϬϮϱ͗ƐƐĞƐƐŝŶŐϵϰͲ',ǌZĂĚĂƌƐƚŝŵĂƚĞƐŝŶWŽůĂƌZĞŐŝŽŶƐƚŚƌŽƵŐŚƚŚĞ<ϮtDĞƚŚŽĚŽůŽŐǇ͕^ƵŵŵĂƌǇƉĂƉĞƌƐƵďŵŝƚƚĞĚƚŽϰƚŚhZ^/dͲZ^͕'ƌĂŶĂŶĂƌŝĂ͕ϭϵͲϮϰDĂǇϮϬϮϰ

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ࡿࡇ࡜࡛◁ሻࡢⓎ⏕ࡍࡿ᮲௳࡟ࡘ࠸࡚ゎᯒࢆ⾜ࡗࡓࠋDust Detection over Mongolian Territory using Dust RGB Imagery
from Himawari-8/9 Geostationary Satellite
Contents
1. Introduction ............................................................................................................................................... 2
2. Materials ................................................................................................................................................... 3
2.1. The region of interest ......................................................................................................................... 3
2.2. Meteorological data ........................................................................................................................... 3
2.3. Satellite image processing.................................................................................................................. 3
2.4. Google base map ................................................................................................................................ 3
3. Dust outbreaks .......................................................................................................................................... 3
3.1 April 14, 2019 ..................................................................................................................................... 3
3.1.1. S – 1 ............................................................................................................................................ 3
3.1.2. S – 2 ............................................................................................................................................ 4
3.1.3. S – 3 ............................................................................................................................................ 4
3.1.4. S – 4 ............................................................................................................................................ 5
3.2. April 15, 2019 .................................................................................................................................... 6
3.3. April 16, 2019 .................................................................................................................................... 7
3.4.1. S–1 .............................................................................................................................................. 9
3.4.2. S–2: ............................................................................................................................................. 9
3.4.3. S–3 ............................................................................................................................................ 10
3.5. April 19, 2019 .................................................................................................................................. 11
3.5.1. S–1 ............................................................................................................................................ 11
3.5.2. S–2 ............................................................................................................................................ 12
3.5.3. S–3 ............................................................................................................................................ 13
3.6. April 22, 2019 .................................................................................................................................. 14
3.6.1. S–1 ............................................................................................................................................ 14
3.6.2. S–2 ............................................................................................................................................ 15
3.7. April 28, 2019 .................................................................................................................................. 16
3.7.1. S – 1 .......................................................................................................................................... 16
3.7.2. S – 2 .......................................................................................................................................... 16
3.7.3. S – 3 .......................................................................................................................................... 17
3.8. April 6, 2020 .................................................................................................................................... 18
3.8.1. S – 1 .......................................................................................................................................... 18
3.8.2. S – 2 .......................................................................................................................................... 193.9. April 7, 2020 .................................................................................................................................... 20
3.10. May 15, 2020 ................................................................................................................................. 22
3.10.1. S – 1 ........................................................................................................................................ 22
3.10.2. S – 2 ........................................................................................................................................ 23

1. Introduction
We are concentrating on the months of March, April, and May between 2018 and 2023 for ourdust survey in Mongolia. The selection of these months is based in environmental andmeteorological considerations specific to the region. Here are some general reasons why thesemonths might be suitable for a dust survey in Mongolia:
1. Springtime Conditions:xMarch, April, and May are spring months in Mongolia. During this time, the weather tends
to be transitional from winter to summer, with temperatures gradually rising.

x

Spring is characterized by the melting of snow and ice, leading to increased soil moisture.
This can impact dust emissions, making it an interesting period to assess dust levels.

2. Wind Patterns:xx

Mongolia is known for its dry and windy climate. Spring is a season when wind patterns
may play a crucial role in transporting dust particles.
Conducting a dust survey during these months allows researchers to investigate theprevalence and transport of dust due to seasonal wind patterns.

3. Potential for Dust Storms:xx

Dust storms are more likely to occur during the spring months in Mongolia. These storms
can contribute significantly to airborne dust concentrations at both local and regional
scales.
Monitoring dust levels during March, April, and May can help capture the impact of any
dust storms on air quality.

4. Agricultural Activities:xx

Spring is a critical time for agricultural activities such as plowing and seeding. These
activities can disturb the soil and contribute to dust emissions.
A dust survey during these months can help assess the influence of agricultural practices
on airborne dust concentrations

2. Materials
2.1. The region of interest
The region of interest is defined by the coordinates of the southwest (41°N, 93°E), northwest(50°N, 93°E), northeast (50°N, 112°E), and southeast (41°N, 112°E). Afterwards, we identified
dust outbreaks and analyzed them by maximizing the scale.

2.2. Meteorological data
We took into account two factors: wind speed and cloud cover in the Gobi region, which is themain source of natural dust in Mongolia. For meteorological data, we utilized the website ‘Visual
Crossing’, where weather history and forecasts are accessible (https://www.visualcrossing.com/).
After identifying the locations where dust dispersion started, we searched for data using the namesof the nearest places in the search box. Hourly data can be obtained from the website (in somecases, three-hourly data for wind gusts and air pressure, although this is not always available).

2.3. Satellite image processing
We used the dust RGB retrieval code for Himawari-8/9, the Japanese geostationary satellite,
provided by Kyushu University. To optimize the exact locations, we modified the region of interestfor each case.

2.4. Google base map
We identified the source area types by using Google Base Map as the background for the dust
RGB images. Next, the National Atlas of Mongolia [1] was employed for detecting geographicalobjects that are potential dust hotspots.

3. Dust outbreaks
3.1 April 14, 2019
On that day, we observed natural dust dispersing from four different locations. The meteorologicalparameters at the onset of the dust outbreak are presented in Tables 1, 2, 3, and 4, and Figure 1.
3.1.1. S – 1: The tailings pond of the Erdenet mine, one of the world's largest copper ore mining
and processing facilities, is discussed in more detail in Batbold et al. 2022 [2]. This case was notdiscussed in the results of our previous study [2].
Approximate coordinate: 49°5'0"N, 104°7'0"EMeteorology: White dust from the tailings pond was driven by a wind speed of around 8-11 m/s(refer to Table 1 and Figure 1). The wind direction was from the W and WNW. Dust dispersion
was observed to cease when the wind speed decreased to 4 m/s at 10 UTC (refer to Table 1 andFigure 1).

Table 1. Meteorological data nearby Erdenet city.
Wind
speed
(m/s)

Wind
direction(angle)8

WNW, 292

11

W, 27007

WNW, 294

0

15.5

0

7

WNW, 296

0.2

April 14, 2019 09:00

17.6

0

7

W, 270April 14, 2019 10:00

12.2

0

4

W, 300Date & Time (UTC)

Temp., Precip.
(°C)
(mm)

April 14, 2019 05:00

15.8

0

April 14, 2019 06:00

17.2

0

April 14, 2019 07:00

16

April 14, 2019 08:00

Wind
gust
(m/s)
15

18

Sea levelpressure
(hPa)

Cloud
cover
(%)
0

1005.31002.6

30

50
17.4

3.1.2. S – 2: The source was from nearby Elsen Tasarkhai, a part of the Mongol Els sand dunes
that stretch along the Tuv, Uvurkhangai, and Bulgan aimags (The term 'aimag' is equivalent to'province' and represents the largest sub-national administrative unit). The sand dunes stretch
around 80 km.
Approximate coordinate: 47°15'0"N, 103°44'0"EMeteorology: Dust dispersed from the sandy barren surface by the wind speed of 7-9 m/s. The
wind gust wasn't too high, approximately 9-10 m/s (refer to Table 2 and Figure 1).
Table 2. Meteorological data nearby Rashaant , Bulgan.
Wind
speed
(m/s)

Wind
direction(angle)

7

292

9

270

0

7

295

0

14.1

0

7

297

7.3

April 14, 2019 09:00

15.9

0

6

270

April 14, 2019 10:00

10.7

0

4

298

Date & Time (UTC)

Temp., Precip.
(°C)
(mm)

April 14, 2019 05:00

14.4

0

April 14, 2019 06:00

15.7

0

April 14, 2019 07:00

14.6

April 14, 2019 08:00

Wind
gust
(m/s)
10

9

Sea levelpressure (hPa)

Cloud
cover
(%)
0

1008.9

1006

0

30
68.1

3.1.3. S – 3: Dry lake beds: Many lakes remain dry until they receive floodwater during heavy
rain, making them a potential source of dust hotspots prone to wind velocity. The Kherlen Riveris the second-longest river running through Mongolian territory. S–3 area is along that river andincludes several detached seasonal lakes (Figure 1).
Approximate coordinate: 46°40'60"N, 107°55'0"E and 46°52'0"N, 109°18'0"E.

Meteorology: Dust was dispersed from the temporary dry lake beds with a wind speed of 9-10m/s (Table 3).
Table 3. Meteorological data nearby Bayan, Tuv.
Wind
speed
(m/s)

Wind
direction(angle)

9

285

10

280

0

9

289

0

14.1

0

9

292

0

April 14, 2019 09:00

15.1

0

10

300

April 14, 2019 10:00

9.8

0

5

293

Date & Time (UTC)

Temp., Precip.
(°C)
(mm)

April 14, 2019 05:00

14.4

0

April 14, 2019 06:00

14.4

0

April 14, 2019 07:00

14.6

April 14, 2019 08:00

Wind
gust
(m/s)
12

12

Sea levelpressure (hPa)

Cloud
cover
(%)
0

1008

1005.800
03.1.4. S – 4: From dry lake beds: Many lakes remain dry until they receive floodwater during
heavy rain. Consequently, for the rest of the time, they tend to be sources of dust hotspots prone
to wind velocity. Several lakes exist near a specially protected area called “Altan Ovoo”, primarily
sustained by rainwater but also groundwater.
Approximate coordinate: 45°30'0"N, 113°11'0"E
Meteorology: Dust was dispersed from the temporary dry lake beds with a wind speed of 8-11
m/s (Table 4 and Figure 1).
Table 4. Meteorological data nearby Dariganga, Sukhbaatar .
Date & Time (UTC)

Temp., Precip.
(°C)
(mm)

Wind
gust
(m/s)

Wind
speed
(m/s)

Wind
direction(angle)Sea levelpressure
(hPa)

Cloud
cover
(%)

April 14, 2019 05:00

13.6

0

N/A

11

WNW, 288

N/A

0

April 14, 2019 06:00

14

0

N/A

11

WNW, 290

N/A

0

April 14, 2019 07:00

14.1

0

N/A

10

WNW, 289

N/A

0

April 14, 2019 08:00

13.6

0

N/A

10

WNW, 288

N/A

0

April 14, 2019 09:00

12.6

0

N/A

8

WNW, 286

N/A

0

April 14, 2019 10:00

8

0

N/A

8

WNW, 284

N/A

0Figure 1. Dust RGB extraction using Himawari-8 geostationary satellite on April 14, 2019.

3.2. April 15, 2019
Dispersion of mining dust, commonly known as white dust, from the tailings pond.
Approximate coordinate: 47°15'0"N, 103°44'0"EMeteorology: White dust was transported from the tailings pond by a westerly wind speed of 8-9
m/s (refer to Table 5 and Figure 2). The fluctuation of white dust outbreaks has been increasingover the years. The tailings pond is located in the north of Mongolia. Although this area is notgeographically very vulnerable, the tailings pond consistently becomes a primary source near thearea due to its non-soil surface.
Table 5. Meteorological data nearby Erdenet, Orkhon.
Date & Time (UTC)

Temp., Precip.
(°C)
(mm)

Wind
gust
(m/s)

Wind
speed
(m/s)

Wind
direction(angle)Sea levelpressure
(hPa)

Cloud
cover
(%)

April 15, 2019 03:00

14.2

0

12

8

W, 2701003.730

April 15, 2019 04:00

14.8

0

9

W, 2850April 15, 2019 05:00

15.6

0

9

W, 2820.7

April 15, 2019 06:00

17.1

0

12

W, 270April 15, 2019 07:00

16.7

0

10

W, 275

20

998.7

40
16.5

Figure 2. Dust RGB extraction using Himawari-8 geostationary satellite on April 15, 2019.

3.3. April 16, 2019
Baruun-Urt is the center of Sukhbaatar aimag, and there are some seasonal lakes in the south of
Baruun-Urt. The dry beds of several small lakes and the surrounding areas near them became theinitial source of dust in this dust event.
Approximate coordinate: 46°35'0"N, 113°21'0"E
Meteorology: As seen in Figure 3, Dust plume started to transport near that area with the eastsoutheasterly wind with 11 m/s. Around 01:00 and 02:00 UTC, wind speed was decelerated to 23 m/s (Table 6). During that time, dust plume moved towards the northwest (Figure 3).
Table 6. Meteorological data nearby Baruun-Urt, Sukhbaatar
Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

Wind
gust
(m/s)

Wind
speed
(m/s)

Wind
direction(angle)Sea levelpressure
(hPa)

Cloud
cover (%)

April 16, 2019 00:00

3.7

0

11

11

ESE, 1101006

80

April 16, 2019 01:00

8.5

0

2

WSW, 250

58.6

April 16, 2019 02:00

11.4

0

3

SW, 225

32.1

April 16, 2019 03:00

8.7

0

11

SE, 140

April 16, 2019 04:00

17.1

0

6

WSW, 255

11

1002.4

Figure 3. Dust RGB extraction using Himawari-8 geostationary satellite on April 16, 2019.

3.4. April 17, 2019
Here, we identified three distinct dust source places.

80
20.7

3.4.1. S–1: The first site shown on the map (Figure 4) is located at the center of the country. A
weak dust plume dispersed from the dry beds of gullies and seasonal lakes in the geographicalsteppe zone can be seen.
Approximate coordinate: 46°57'0"N, 106°12'0"EMeteorology: The north-northwesterly wind of 10 m/s initiated the dust outbreak at 04:00 UTC(Table 7). Although the dust plume is weak, our previous study on mine dust dispersion suggested
that using dust RGB images with a 10-minute interval allows us to track the spatiotemporaldispersion effectively when we superimpose them.
Table 7. Meteorological data nearby Bayan-unjuul, Tuv .
Wind
speed
(m/s)

Wind
direction(angle)010NNW, 340

47.9

4.9

0

10

NNW, 340

20.7

April 17, 2019 06:00

6.5

0

10

NNW, 339

7.5

April 17, 2019 07:00

7.2

0

10

NNW, 339

3.9

April 17, 2019 08:00

7.1

0

10

NNW, 339

2

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 17, 2019 04:00

3.2

April 17, 2019 05:00

Wind
gust
(m/s)

Sea levelpressure
(hPa)

Cloud
cover
(%)

3.4.2. S–2: Natural dust started to disperse from the steppe zone, and there is no specific source ofdust (Figure 4).
Approximate coordinate: 46°27'0"N, 110°37'0"EMeteorology: The dust plume was transported by the north and northwesterly wind with a speedof 9-10 m/s, lasting from 00:00 to 01:00 UTC (Table 8). Therefore, a wind speed of 9-10 m/s may
be inferred as the threshold velocity in this case.
Table 8. Meteorological data nearby Galshar, Khentii.
Wind
speed
(m/s)

Wind
direction(angle)08NNW, 341

0.4

9.5

0

10

N, 351

39.7

April 17, 2019 01:00

11.5

0

10

N, 351

4.7

April 17, 2019 02:00

12.9

0

9

NNW, 348

0.5

April 17, 2019 03:00

13.9

0

9

NNW, 344

10.8

April 17, 2019 04:00

14.7

0

9

NNW, 339

30.1

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 16, 2019 23:00

6.9

April 17, 2019 00:00

Wind
gust
(m/s)

Sea levelpressure
(hPa)

Cloud
cover
(%)

April 17, 2019 05:00

15.2

0

8

NNW, 334

27.1

April 17, 2019 06:00

15.3

0

8

NNW, 331

45.7

3.4.3. S–3: There are some seasonal lakes and dry gullies in the south and southwest of BaruunUrt. The dry beds of multiple small lakes and the surrounding areas near them became the initialsource in this case (Figure 4).
Approximate coordinate: 46°23'0"N, 112°41'0"E
Meteorology: With a wind speed of 8-10 m/s, the dust plume was transported by the NNW, NE,
and N winds as indicated in Table 9.
Table 9. Meteorological data nearby Baruun-Urt, Sukhbaatar.
Wind
speed
(m/s)

Wind
direction(angle)8

NNW, 339

8

NE, 50010

N, 351

9.4

10.1

0

10

NNW, 348

3.1

April 17, 2019 03:00

6.1

0

12

NE, 50April 17, 2019 04:00

10.5

0

10

NNW, 344

24.5

April 17, 2019 05:00

10.4

0

10

NNW, 343

34.7

April 17, 2019 06:00

7.9

0

8

N, 360Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 16, 2019 23:00

3.9

0

April 17, 2019 00:00

3.9

0

April 17, 2019 01:00

8.8

April 17, 2019 02:00

Wind
gust
(m/s)
8

18

15

Sea levelpressure
(hPa)

Cloud
cover
(%)
10.2

997.6

1002.31006.280

50

60

Figure 4. Dust RGB extraction using Himawari-8 geostationary satellite on April 17, 2019.

3.5. April 19, 2019
3.5.1. S–1: Dust is dispersed from the Khangai mountain range. Indeed, it is very rare to see sucha dust storm over this area. The source area can be defined as forest-steppe. We presume thatnatural dust dispersed from the pasture because there are no mines, barren surfaces, or beds oflakes and rivers in the area (Figure 6).
Approximate coordinate: 49°21'0"N, 101°48'0"E
Meteorology: The wind gust reached 16-18 m/s, and the wind speed ranged between 9-14 m/s
during this event (Table 10). The dust momentum is caused by the west-northwesterly (WNW)
wind.
Table 10. Meteorological data nearby Tosontsengel, Khuvsgul .
Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

Wind
gust
(m/s)

Wind
speed
(m/s)

Wind
direction(angle)Sea levelpressure
(hPa)

Cloud
cover
(%)

April 19, 2019 00:00

4.5

0

17

9

WNW, 304

1010.847

April 19, 2019 01:00

1.5

0

12

WNW, 304

0.3

April 19, 2019 02:00

2.4

0

13

WNW,304

0

April 19, 2019 03:00

4

0

10

WNW, 304

April 19, 2019 04:00

3.1

0

14

WNW, 305

0April 19, 2019 05:00

3.4

0

13

WNW, 3060161014.520.9

April 19, 2019 06:00

3.3

0

18

12

NW, 3101018.95.2

3.5.2. S–2: A severe white dust outbreak occurred, although it's a bit difficult to distinguish it on
the large-scale map (Figure 6). This case was emphasized as a special case in Batbold’s PhD thesis
in 2022.
As shown in Figure 5a, white dust is dispersing from the tailings pond, while natural dust is comingfrom the northeast at 05:50 UTC. They subsequently mixed at 07:40 UTC (Figure 5b). Although
the dust RGB imagery illustrates both natural dust and white dust as magenta, the white dust plumeappears as a brighter red compared to the natural dust. We extracted the red color component fromthe dust RGB algorithm by adjusting the BTD(12.4–10.4 ȝm) range from –4 K to +2 K with a 0–
1 value in each dispersion map. Setting the minimum value of red color intensity as 0.85 at 07:40
UTC made the white dust plume distinguishable from the natural dust, with the white dust
exhibiting a higher red color contribution corresponding to dense dust clouds (Figure 5c).
Approximate coordinate: 47°15'0"N, 103°44'0"EMeteorology: The wind gust reached 16-18 m/s, and the wind speed ranged between 9-14 m/s
during this event (Table 10) and the dust momentum is driven by the west-northwesterly (WNW)
wind.

Figure 5. White dust outbreak on April 19, 2019. The Dust RGB imagery at 05:50 UTC (a), the dust RGB imagery at
07:40 UTC, and red component extraction at 07:40 UTC. The white triangle denotes the tailings pond.

Table 11. Meteorological data nearby Erdenet, Orkhon.
Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

Wind
gust
(m/s)

Wind
speed
(m/s)

Wind
direction(angle)Sea levelpressure
(hPa)

Cloud
cover
(%)

April 19, 2019 00:00

14.9

0

11

7

SSW, 210

996.4

14.9

April 19, 2019 01:00

7.6

0

13

NW, 311

7.6

April 19, 2019 02:00

7.2

0

13

NW, 311

7.2

April 19, 2019 03:00

10.7

0

13

NW, 320

April 19, 2019 04:00

8.2

0

13

NW, 310

8.2

April 19, 2019 05:00

8.1

0

14

NW, 311

8.1

April 19, 2019 06:00

8.6

0

11

WNW, 300

April 19, 2019 07:00

6.7

0

14

NW, 316

6.7

April 19, 2019 08:00

5.8

0

13

NW, 320

5.8

April 19, 2019 09:00

5.9

0

10

WNW, 300

April 19, 2019 10:00

3.2

0

11

NNW, 330

25

21

15

1004.21010.11014.3

10.7

8.6

5.9
3.2

3.5.3. S–3: Natural dust started to disperse from a grazing area and nearby some seasonal lakes at
02:00 UTC (Figure 6). From 02:00 to 07:00 UTC, the wind direction was from SSW and WSW.
It then changed to W and N at 08:00 UTC (Table 12 and Figure 6).
Approximate coordinate: 46°50'0"N, 109°30'0"E
Meteorology: No dust outbreak is observed when wind speed reached 10 m/s. Then, at 02:00
UTC, a wind speed of 11 m/s put the dust in motion. During the dust outbreak, wind speed
fluctuated between 11 and 13 m/s (Table 12 and Figure 6).
Table 12. Meteorological data nearby Bayanmunkh, Khentii.
Wind
speed
(m/s)

Wind
direction(angle)0

10

S, 195

52.7

12.6

0

11

SSW, 203

17.4

April 19, 2019 03:00

15.5

0

12

SSW, 209

10.1

April 19, 2019 04:00

18.2

0

12

SSW, 218

9

April 19, 2019 05:00

20.7

0

12

SW, 229

7

April 19, 2019 06:00

22.4

0

11

SW, 238

7.7

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 19, 2019 01:00

9.2

April 19, 2019 02:00

Wind
gust
(m/s)

Sea levelpressure
(hPa)

Cloud
cover
(%)

April 19, 2019 07:00

23.2

0

11

WSW, 252

11.2

April 19, 2019 08:00

22.8

0

11

W, 282

27.3

April 19, 2019 09:00

19.7

0

13

NW, 31127.9

April 19, 2019 10:00

15.2

0

13

NW, 323

65.7

Figure 6. Dust RGB extraction using Himawari-8 geostationary satellite on April 19, 2019.

3.6. April 22, 2019
3.6.1. S–1: Dust hotspot originated from the dry seasonal lake bed in the grazing area.
Approximate coordinate: 46°59'0"N, 106°11'0"E
Meteorology: Natural dust is propelled by a wind speed of 11 m/s at 05:00 UTC by the NNW
wind. Subsequently, a wind gust of 16 m/s increasingly magnified the dust plume at 06:00 (Table
13 and Figure 7).
Table 13. Meteorological data nearby Bayantsagaan, Tuv.
Wind
speed
(m/s)

Wind
direction(angle)012NNW, 333

0011NNW, 333

0.4

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 22, 2019 04:00

13.5

April 22, 2019 05:00

13.7

Wind
gust
(m/s)

Sea levelpressure
(hPa)

Cloud
cover
(%)

April 22, 2019 06:00

12.6

0

April 22, 2019 07:00

13.3

April 22, 2019 08:00

12.6

16

16

NNW, 330

1004

80

0

10

NNW, 333

10.6

0

9

NNW, 334

0.1

3.6.2. S–2: A gully created by floodwater cross through the center of Bayan soum (Aimags are
divided into soums). For S–2, the gully served as the dust hotspot.
Approximate coordinate: 47°16'0"N, 107°31'0"E
Meteorology: A wind gust of 16 m/s from the NNW direction propelled the dust plume to theleeward area (Table 14 and Figure 7).
Table 14. Meteorological data nearby Bayan, Tuv.
Wind
speed
(m/s)

Wind
direction(angle)11

NW, 325

16

NNW, 330

010NW, 325

0.1

11.5

0

10

NW, 326

0.3

10.9

0

14

N, 350Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 22, 2019 04:00

130

April 22, 2019 05:00

12.6

0

April 22, 2019 06:00

12.4

April 22, 2019 07:00
April 22, 2019 08:00

Wind
gust
(m/s)
16

18

Sea levelpressure
(hPa)

Cloud
cover
(%)
0.2

1004

1005.5Figure 7. Dust RGB extraction using Himawari-8 geostationary satellite on April 22, 2019.

8030

3.7. April 28, 2019
3.7.1. S – 1: Uvs is the largest lake in Mongolia in terms of coverage. The lake swash located at
the southwest of Uvs Lake has been identified as a hotspot.
Approximate coordinate: 50°14'0"N, 91°59'0"E
Meteorology: Dust plume is driven by a 10 m/s wind from WNW at 04:00 UTC. With decreasing
wind speed, the dust plume shifted towards the southeast (Table 15 and Figure 8).
Table 15. Meteorological data nearby Ulaangom, Uvs.
Wind
speed
(m/s)

Wind
direction(angle)0

10

WNW, 300

30.6

4.6

0

10

WNW, 302

17.9

April 28, 2019 05:00

13.6

0

7

NW, 310

April 28, 2019 06:00

6.2

0

8

NW, 310

6.3

April 28, 2019 07:00

6.5

0

8

NW, 314

1.6

April 28, 2019 08:00

13.9

0

4

SSE, 160

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 28, 2019 03:00

4

April 28, 2019 04:00

Wind
gust
(m/s)

19

17

Sea levelpressure(hPa)

1015.4

1016.6

Cloud
cover
(%)

30

80

3.7.2. S – 2: We identified the second source area from the so-called Great Lakes Valley, where
there are several permanent lakes and some sand dunes. The dry bed of Holboo Lake was the mostintense hotspot of the dust outbreak (Figure 8).
Approximate coordinate: 47°13'55.55"N, 92°42'0"EMeteorology: During the dust outbreaks shown in Figure 8, natural dust dispersion at 03:00 UTC
was driven by a 15 m/s wind from the west. Several dust sources then created a bigger dust storm.
Wind gusts were recorded at 19 m/s (05:00 UTC) and 17 m/s (08:00 UTC) (Table 16).
Table 16. Meteorological data nearby Mankhan, Khovd.
Wind
speed
(m/s)

Wind
direction(angle)0

15

W, 268

21.4

1.3

0

14

W, 271

8.3

April 28, 2019 05:00

12.2

0

8

W, 270April 28, 2019 06:00

2.4

0

11

W, 275

1.9

April 28, 2019 07:00

2.2

0

10

W, 276

3.7

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 28, 2019 03:00

0.5

April 28, 2019 04:00

Wind
gust
(m/s)

19

Sea levelpressure(hPa)

1016.9

Cloud
cover
(%)

30

April 28, 2019 08:00

13.2

0

17

9

WNW, 290

1016.630

3.7.3. S – 3: We identified the third source area near the so-called Lakes Valley (Figure 8).
Through the valleys between mountainous areas, soil degradation due to water erosion, forexample seasonal dry lakes and dry gullies, is common.
Approximate coordinate: 44°56'0"N, 100°7'0"EMeteorology: The wind speed during the event fluctuated between 9 and 13 m/s from the west(W) and west-northwest (WNW) directions (Table 17).
Table 17. Meteorological data nearby Bayan-Ovoo, Bayankhongor.
Wind
speed
(m/s)

Wind
direction(angle)09W, 282

0

14.6

0

11

W, 2850.2

April 28, 2019 05:00

15.1

0

12

W, 2883

April 28, 2019 06:00

15.3

0

12

WNW, 291

7.8

April 28, 2019 07:00

15.5

0

13

WNW, 293

6.3

April 28, 2019 08:00

15.4

0

13

WNW, 292

4.4

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 28, 2019 03:00

13.6

April 28, 2019 04:00

Wind
gust
(m/s)

Sea levelpressure
(hPa)

Cloud
cover
(%)

Figure 8. Dust RGB extraction using Himawari-8 geostationary satellite on April 28, 2019.

3.8. April 6, 2020
Two distinct and intense dust outbreaks were observed on the 6th of April 2020.
3.8.1. S – 1: Dust outbreak is initiated near the Khangai mountain range, which is a geographicallyforest-steppe. Annually, dust storm is a very rare event in this region.
Approximate coordinate: 47°13'0"N, 101°46'0"EMeteorology: It's noteworthy that the wind speed was between 1 and 5 m/s at the beginning of thedust dispersion from 01:00 to 03:00 UTC. Additionally, the wind gust reached only 4 m/s (Table
18). However, the plume direction conforms with the meteorological data given in Table 18 and
Figure 9.
Table 18. Meteorological data nearby Tsenher, Arkhangai.
Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 05, 2019 23:00

-4.1

0

Wind
gust
(m/s)

Wind
speed
(m/s)

Wind
direction(angle)3

S, 174

Sea levelpressure
(hPa)

Cloud
cover
(%)
0

April 06, 2020 00:00

-5.6

0

April 06, 2020 01:00

5.3

April 06, 2020 02:00

4

1

S, 1700

4

S, 195

0

8.8

0

5

SSW, 2090

April 06, 2020 03:00

0.4

0

4

ESE, 120

April 06, 2020 04:00

11.5

0

7

SSW, 216

0

April 06, 2020 05:00

12.1

0

8

SSW, 2190

April 06, 2020 06:00

5.2

0

5

ESE, 110

April 06, 2020 07:00

11.9

0

9

SW, 223

0

April 06, 2020 08:00

11.4

0

9

SW, 226

0

April 06, 2020 09:00

6.1

0

4

E, 80

4

5

6

1032.71025.91019.81018.1

60

0

0

50

3.8.2. S – 2: An intense dust storm initiated from the steppe zone, moving towards the west (W)and west-northwest (WNW). By 09:00 UTC, the dust cloud merged with the S–1 dust plume(Figure 9).
Approximate coordinate: 47°3'0"N, 106°59'0"E
Meteorology: It can be seen that dust storm started at 23:00 UTC on the 5th of April 2020, with 8
m/s wind from Easterly. As shown on the table, wind gusts ranged rfrom 11 to 20 m/s. From 00:00
to 03:00 UTC wind force reached 10-17 m/s (Table 19).
Table 19. Meteorological data nearby Bayantsagaan, Tuv.
Wind
speed
(m/s)

Wind
direction(angle)

8

E, 87

17

E, 100010

E, 104

88.4

6.1

0

10

ESE, 110

85.6

April 06, 2020 03:00

1.4

0

15

E, 100April 06, 2020 04:00

10

0

9

ESE, 12547.8

April 06, 2020 05:00

11.3

0

9

SE, 132

40

April 06, 2020 06:00

5.9

0

10

ESE, 120

April 06, 2020 07:00

12.3

0

8

SE, 140

17.7

April 06, 2020 08:00

11.9

0

8

SE, 139

3.1

April 06, 2020 09:00

6.2

0

11

ESE, 110

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 05, 2019 23:00

-2.6

0

April 06, 2020 00:00

-1.4

0

April 06, 2020 01:00

3.5

April 06, 2020 02:00

Wind
gust
(m/s)
17

20

20

11

Sea levelpressure
(hPa)

Cloud
cover
(%)
75.9

1030.41029.61025.81024.2

77.2

65.5

40

0

Figure 9. Dust RGB extraction using Himawari-8 geostationary satellite on April 28, 2019.

3.9. April 7, 2020
An intense and rare dust storm occurred in the northern part of Mongolia on the 7th of April 2020
(Figure 10). To provide more elaborate details on the meteorological conditions, we have included
data from the two stations.
Approximate coordinate: 49°5'0"N, 104°7'0"E, and 49°28'0"N, 105°56'0"EMeteorology: Similar to S–1 in April 6, 2020, the wind speed was not particularly high (Table 20
and 21). Therefore, these cases could be considered special events warranting detailed
investigation in meteorology.
Table 20. Meteorological data nearby Erdenet, Orkhon.
Wind
speed
(m/s)

Wind
direction(angle)4

WNW, 300

1

NNW, 330

03

NW, 319

0.8

5.1

0

3

NW, 322

1.9

April 07, 2020 03:00

6.7

0

2

SE, 130

April 07, 2020 04:00

7.6

0

3

NW, 310

2.9

April 07, 2020 05:00

8.5

0

3

WNW, 308

5.3

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 06, 2019 23:00

-2.9

0

April 07, 2020 00:00

0.7

0April 07, 2020 01:00

3.2

April 07, 2020 02:00

Wind
gust
(m/s)
4

3

Sea levelpressure
(hPa)

Cloud
cover (%)
4.4

1023.81021.340

1.8

April 07, 2020 06:00

9.4

0

April 07, 2020 07:00

9.1

April 07, 2020 08:00

5

4

WNW, 300

03NW, 318

11.8

8.8

0

3

NW, 325

35.7

April 07, 2020 09:00

8.6

0

2

NW, 320

April 07, 2020 10:00

6.8

0

3

N, 35433.1

April 07, 2020 11:00

2.9

0

3

N, 12

31.1

5

1018.61018.740

80

Table 21. Meteorological data nearby Darkhan, Darkhan-Uul.
Wind
speed
(m/s)

Wind
direction(angle)4

S, 1705

SE, 140

0

7

S, 180

87.3

5.3

0

8

S, 184

87.5

April 07, 2020 03:00

8.2

0

4

S, 170April 07, 2020 04:00

7.1

0

8

S, 18280.1

April 07, 2020 05:00

8

0

7

S, 17872.8

April 07, 2020 06:00

12.7

0

5

SSW, 210

April 07, 2020 07:00

10

0

6

SSE, 168

16.2

April 07, 2020 08:00

10.3

0

6

SSE, 165

1.5

April 07, 2020 09:00

14.4

0

4

S, 170April 07, 2020 10:00

7.2

0

3

SSE, 156

0.1

April 07, 2020 11:00

3.6

0

3

SE, 132

0.2

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

April 06, 2020 23:00

-0.2

0

April 07, 2020 00:00

6.4

0

April 07, 2020 01:00

3.7

April 07, 2020 02:00

Wind
gust
(m/s)
8

6

10

7

Sea levelpressure
(hPa)

Cloud
cover (%)
86.9

1022.81023.11019.91017.6

90

90

80

60

Figure 10. Dust RGB extraction using Himawari-8 geostationary satellite on April 7, 2020.

3.10. May 15, 2020
A regional-scale dust storm occurred on the 15th of May 2020. We aimed to illustrate the initialstage of the dust storm and identified two distinct locations (Figure 11).
3.10.1. S – 1: The dry gullies in the valley of the Khangai mountain range (southwestward) wereidentified as the initial source region.
Approximate coordinate: 46°55'0"N, 98°42'0"EMeteorology: Throughout the dust storm, wind speeds ranged from 10 to 21 m/s, with gusts
reaching 19-23 m/s between 00:00 and 10:00 UTC. The wind direction was primarily from WNW
and NW (Table 22 and Figure 11).

Table 22. Meteorological data nearby Bayanbulag, Bayankhongor.
Wind
speed
(m/s)

Wind
direction(angle)9

WNW, 301

14

NW, 320015NW, 313

0

13.6

0

16

NW, 3140.1

May 15, 2020 03:00

7.9

0

21

WNW, 300

May 15, 2020 04:00

14.9

0

17

NW, 3170

May 15, 2020 05:00

15.5

0

17

NW, 31922.2

May 15, 2020 06:00

10.4

0

19

WNW, 300

May 15, 2020 07:00

16.2

0

16

NW, 32284.6

May 15, 2020 08:00

16.2

0

15

NW, 323

22.5

May 15, 2020 09:00

11.4

0

10

NW, 320

May 15, 2020 10:00

15.5

0

13

NW, 323

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

May 15, 2020 23:00

8.2

0

May 15, 2020 00:00

4.6

0

May 15, 2020 01:00

12.4

May 15, 2020 02:00

Wind
gust
(m/s)
19

23

21

19

Sea levelpressure
(hPa)

Cloud
cover
(%)
0

1009

1007.61006.31005.4

0

0

56.1

60
29.9

3.10.2. S – 2: Like defined in S–1 of April 14, 2019, the dust outbreak is observed dispersing near
Elsen Tasarkhai (Figure 11).
Approximate coordinate: 47°15'0"N, 103°44'0"EMeteorology: Wind speeds ranged from 9 to 16 m/s (wind gusts reached 12-18 m/s), causing
such an intense dust storm. The wind direction was from the NW and NNW.
Table 23. Meteorological data nearby Rashaant, Bulgan.
Wind
speed
(m/s)

Wind
direction(angle)13

NW, 323

16

W, 270012NNW, 336

43.4

5.8

0

12

NNW, 344

57.3

May 15, 2020 03:00

3.9

0

12

N, 360

May 15, 2020 04:00

5.6

0

12

NNW, 348

49.6

May 15, 2020 05:00

5.5

0

11

NNW, 347

56.4

Date & Time (UTC)

Temp.,(°C)

Precip.
(mm)

May 15, 2020 23:00

6.9

0

May 15, 2020 00:00

10.2

0

May 15, 2020 01:00

6.2

May 15, 2020 02:00

Wind
gust
(m/s)
18

18

Sea levelpressure
(hPa)

Cloud
cover
(%)
0.5

999.1

1006.680

100

May 15, 2020 06:00

2.1

0

May 15, 2020 07:00

4.7

May 15, 2020 08:00

12

9N, 360011

NNW,347

55.2

4.2

0

10

NNW, 348

54.4

May 15, 2020 09:00

1.2

0

9

N, 360

May 15, 2020 10:00

2.9

0

10

N, 353121011.91014.8

100

100
45.9

Figure 11. Dust RGB extraction using Himawari-8 geostationary satellite on May 15, 2020.

Conclusion
To be continued…

Reference[1] Mongolian Academy of Science (2009) Mongolian National Atlas, vol II. MAS, Ulaanbaatar.
[2] Chultem Batbold, Keiya Yumimoto, Sonomdagva Chonokhuu, Batdelger Byambaa, Batdavaa
Avirmed, Shuukhaaz Ganbat, Naoki Kaneyasu, Yutaka Matsumi, Teppei J. Yasunari, Kenji
Taniguchi, Noriko Hasebe, Keisuke Fukushi, Atsushi Matsuki (2022). Spatiotemporal Dispersion
of Local-Scale Dust from the Erdenet Mine in Mongolia Detected by Himawari-8 Geostationary
Satellite. https://doi.org/10.2151/sola.2022-036

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Advanced tokamak physics and integrated transport modelling
Yong-Su NA, Gyungjin CHOI, Chweeho HEO, Huiwon CHUNG
Department of Nuclear Engineering, Seoul National University, Seoul, Republic of Korea

It is crucial to develop novel advanced operation scenarios to achieve commercial tokamak fusion reactor. In theadvanced tokamak operation scenarios, along with avoidance or mitigation of abrupt MHD activities, reduction,
control, and optimization of transport level has long been an essential issue. It is well-known that turbulence isthe main origin of transport of confined plasma in toroidal fusion machines. A thorough understanding of the
turbulence physics is thus needed to achieve high-performance advanced tokamak operation. However, even after
half-century research of turbulence in tokamak plasmas, still there are physics issues remaining. One of those is
the self-organized criticality induced by nonlinear self-organization of mesoscale structures from the turbulence.
Recently, there has been experimental findings of direct fast ion effect on core confinement enhancement fromASDEX-U and KSTAR. It is worth noting that the main auxiliary heating methods of the two cases are largely
different that it is ICRH for ASDEX-U while NBI for KSTAR. This implies the presence of a universal mechanism
working for the confinement enhancement. Indeed, previous extensive experimental studies of various transportbarrier formations have demonstrated that ExB flow shearing is the main mechanism of suppression of drift wave
turbulence and enhancement of tokamak plasma confinement. While the role of profile-induced equilibrium ExB
shear flow has first been highlighted due to its easier experimental measurements and estimations, theoretical andsimulation studies have revealed that mesoscale zonal ExB flow, nonlinearly self-generated from the drift wave
turbulence, is the major physical object triggering the transition to an enhanced confinement state. The equilibrium
ExB flow plays a role in the later part of the transition, altering the zonal flow. One of interesting features of the
turbulence-zonal flow interaction is the Dimits shift, a nonlinear upshift of the turbulence onset threshold fromlinear marginal stability to self-organized criticality (SOC) because of the quenching of turbulence after its initial
burst by flow self-generation. We would like to remark that the transient turbulence bunch near SOC could beconsidered as a seed of the intermittent transport event visible near marginality. Therefore, understanding the flow
self-organization from turbulence is essential to understand all the nontrivial transport properties near marginality,
more precisely near SOC, in high-performance advanced tokamak operations.
Accordingly, we have addressed theoretical and simulation studies of turbulence-zonal flow interaction in highperformance advanced tokamak plasmas. Linear and nonlinear gyrokinetic simulations have shown importanceof thermal ion dilution effect by the presence of fast ions. It significantly reduces linear growth rate of turbulence,and in nonlinear stage leads to a dramatic reduction in the transport flux. It is noticeable that zonal flow growthrate is even stronger in the presence of fast ions, even in the presence of much weaker turbulence prey. This result
indicates much efficient zonal flow growth from turbulence. This could be relevant to our analytic theoreticalextension of the Hasegawa-Mima equation to the case with fast ions. It is worth noting that the Hasegawa-Mima
equation is an adiabatic limit of the Hasegawa-Wakatani equation which is relevant to the PANTA plasma in
RIAM. It has also been widely accepted as a paradigm equation for the drift wave turbulence-zonal flow nonlinear
interaction in magnetized plasmas. By the 4-wave-coupling calculation we have shown that while the Reynolds
stress drive for the modulational growth of zonal flow is weakened by the dilution effect, the finite threshold of
the zonal flow growth by frequency mismatch among the pump drift wave and sidebands is much more strongly
reduced. As a result, we have an easier zonal flow growth near its threshold, that is, near SOC.
As a next step, we initiated PANTA experimental analyses for comparative study of flow self-organization fromturbulence. It is important that the Hasegawa-Wakatani equation is based on the straight magnetic field, similar
to PANTA plasma, which is still relevant to study nonlinear physics of tokamak plasmas. Moreover, its relevanceto the tokamak SOL is striking. Note that it is easier to find nonlinear self-generated streamers rather than zonal
flows in the PANTA plasmas. Recall that radial anomalous diffusion of transient heat flux in tokamak SOL is
crucial to reduce divertor heat load. Another remarkable point is that many fusion researchers have addressed
electromagnetic fluctuations and perturbed structures in tokamak SOL, while it has been known to be electrostaticin core confined region. Interestingly, it is also well-known that electromagnetic effect on the core turbulence andAlfvenic modes are influential in the core confinement in advanced tokamak operations. The two limits of hot andcold plasmas in the same device point to one signature of the electromagnetic perturbation. Therefore, throughthis international collaboration, we have trained to use diagnostics in PANTA device, in particular the Langmuirprobe and the ball-pen probe. Our final goal is a thorough understanding of nonlinear turbulence physics relevantto the advanced tokamak plasmas by comparative analysis of the electric potential fluctuations obtained by thetwo probes, and the magnetic field fluctuations obtained by the magnetic probe which will be installed in 2024.

Fig. 1. I-V curve obtained from Langmuir probe by voltage sweeping (left), and electron density profile obtained
from the 10-channels radial array of the Langmuir probes (right).
With the guidance of Prof. Chanho Moon and DiMatteo Donato, we have first trained to understand the Langmuirprobe system of PANTA. Fig. 1 shows a successful measurement of electron density profile using the Langmuirprobe array consisting of 10 radial channels. Clear distinction of the core and edge regions are visible.

FIG. 2. Fourier analysis (left) and bicoherence analysis (right) of potential perturbation in different radial locations.
Radially localized turbulence and nonlinear coupling have been observed.
Next, we have trained to obtain potential perturbation data using the Langmuir probes from PANTA experiments
and performed Fourier spectrum analysis and the bicoherence analysis. Fig. 2 shows the results of the fluctuation
analyses. The left figure shows that broadband turbulent fluctuation is robust only in the region connecting coreand edge, indicating importance of core-edge coupling which was unexpected before and cannot be fully describedby a core or edge-specialized modeling. That is, the result reveals the need of an integrated modeling for a proper
understanding of the turbulent transport in PANTA plasmas. The right figure is the result of bicoherence analysis
in different radial locations, also showing radial localization of nonlinear interactions. These interesting features
showing the symptom of core-edge coupling will be further investigated by extensive experimental measurements
and analyses coupled with an integrated modeling.
In summary, through an international collaboration with PANTA, we have performed analytic theoretical studies
and experimental measurements and analyses of nonlinear turbulence properties toward thorough understandingof advanced tokamak physics and integrated transport modeling. Fluctuation analyses of PATNA plasma haveshown unexpected highly radially localized turbulent fluctuations and nonlinear interactions, which is the opposite
nontrivial limit of turbulence physics in contrast to non-local transport events. This unexpected, interesting featurefound during the collaboration will be more extensively investigated using the magnetic probe and an integrated
modeling for its deeper understanding from the perspective of the advanced tokamak plasmas in the upcominginternational collaboration program.

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Plasma start-up and sustainment in spherical tokamak configuration by RF
TAKASE Yuichi(Tokamak Energy Ltd., United Kingdom)
An on-site/on-line hybrid workshop on “Plasma start-up and sustainment in sphericaltokamak configuration by RF” was held on 1st and 2nd February at Advance Fusion
Research Center in Research Institute for Applied Mechanics, Kyushu University. Lively
discussions were held following each presentation.

Agendast

1 February
9:20 Ǧ9:30
Yuichi Takase / Kazuaki Hanada
WS purpose and agenda
9:30 - 10:00
Yuichi Takase
Fusion Development at Tokamak Energy
10:00 - 10:40
Akira Ejiri
Study of current drive in the TST-2 spherical tokamak (Remote)10:40 - 11:20
Hitoshi Tanaka
Recent Result of EC Start-up Experiment on LATE (Remote)11:20 - 11:50
Yusuke Kosuga
Bootstrap current and flow in spherical tokamaks
11:50 - 12:50 Lunch
12:50- 13:30
Hiroshi Idei
Recent Progress and ECH Plans in QUEST
13:30 - 14:10
Takumi Onchi
Electron cyclotron current start-up using a retarding electric field in the
QUEST spherical tokamak

㻌㻌㻌㻌㻌㻌㻌㻌㻌14:10 - 14:50
Masayuki Ono
Efficient ECCD non-inductive start-up and ramp-up and transition to asustainment phase for an ST fusion reactor
14:50 – 15:30
Ryuya Ikezoe
Studies of fast electrons and corresponding kinetic modes on QUEST
15:30 – 15:40

Coffee Break

15:40 - 16:10
Makoto Hasegawa
Plasma control system of QUEST and fast plasma shape recognition with
Machine Learning
16:10 - 16:50
Luis Delgado-Aparicio
Non-Maxwellian LHCD anisotropic features in the edge and core measured
with a multi-energy HXR detector at WEST
16:50 - 17:30
Vladimir Shevchenko
ECRH Progress and Plans for ST40 (Remote)17:30 - 18:10
Bodhi Biswas
Fully-relativistic EBW current drive simulations in STEP (Remote)18:10 – Group Photo

2nd February
9:00 - 9:40
Roger Raman
Closed flux plasma startup using Transient CHI on QUEST
9:40 Ǧ 10:10
Shin Kubo

Toward the numerical estimation of the power flow of the electron Bernstein
wave (Remote)10:10 Ǧ 10:50
Atsushi Fukuyama
Kinetic full wave modeling of O-X-B mode conversion
10:50 ဨ 11:30
Nicola Bertelli
Initial study of the impact of the edge density fluctuations on the HHFW
propagation in NSTX/NSTX-U plasmas
11:30-12:10
Syunichi Shiraiwa
Implicit method for plasma conductivity and its application to electron
Bernstein wave mode conversion
12:10 - 13:10 Lunch
2nd February PM

Discussion of proposals for experiments, diagnosis, and analysis

Summary of Presentations
Yuichi Takase
Tokamak Energy is aiming for early commercialization of fusion energy by combining
the advantages of the low aspect ratio tokamak and high temperature superconducting(HTS) coils. In addition to achieving ion temperatures exceeding 100 million degrees K
needed for fusion burn, we are developing technologies needed for fusion reactors. In
HTS coil development, we have achieved a world record magnetic field of 24T at 20 K,
greatly improved quench resilience, and beginning tests of an HTS coil system in thespherical tokamak configuration (Demo4). We have established the Magnet Business
Unit to commercialize these technologies.
Akira Ejiri
 Preliminary experiments with the new antenna suggested the expected core powerdeposition. Orbit expansion of fast electrons (hitting the limiters) can be a significant loss
channel, and experiments using a movable target is underway. Sheath effect is the present
dominant source of copper and molybdenum impurities, but fast electron heating effecton the limiter can be important for a longer discharge duration. Ion heating occurs at thenear edge region, and the estimated heating power is much smaller than the LHW power.
Ion heating through parametric decay instabilities (ion-cyclotron quasi-mode and ionsound quasi-mode) is suggested as the mechanism, and it is consistent with theoreticaland experimental results.
Hitoshi Tanaka
Firstly, effects of the background magnetic field in the experiment room on theformation of closed flux surface (CFS) by ECH under steady Bv was investigated. A
toroidal plasma current flows when a weak vertical field is applied to the ECR plasma,so as to cancel the applied vertical filed. The plasma current does not flow when theapplied vertical field cancels the vertical component of the background magnetic field(Bz-background = 0.27 mT). After the formation of CFS, there are no significant effect on Ip
ramp-up at least up to 5 kA. Secondly, effects of the vertical vacuum vessel space wasinvestigated. A movable limiter was installed from the top port in the vacuum vessel tochange the vertical elongation of the plasma generating region (the vertical elongation
ratio țvv = 1.7 ~ 2.3). In the case of țvv =1.7, n-index or Pinj should be high enough toform CFS (n-index > 0.25 @ Pinj = 10 kW, n-index > 0.15 @ Pinj = 20 kW). In the case ofțvv =2.3, formation of CFS is achieved in the wide range of n-index and Pinj (n-index Ӎ
0.07 @ Pinj = 10 kW). For the same Pinj, the larger țvv allows lower n-index and brings
larger current-flowing area and larger Ip. In addition, formation of CFS is achieved at
higher Bv. Large țvv allows flexibility of current-flowing area and tokamak equilibrium.
Yusuke Kosuga
 It is shown that appreciable amount of current can be carried by the precession motionof trapped energetic electrons in QUEST. Relative importance of this current to bootstrap
current scales as H1/2/(1-H2)1/2, where H is the inverse aspect ratio. Thus precession driven
current can be more important for spherical tokamaks with H < 1. For typical plasma
parameters in QUEST, the precession driven current can reach up to O(10) kA. Inductive
field may decrease this current due to conservation of toroidal canonical momentum.

Hiroshi Idei
Recent progresses in QUEST were briefly explained as introduction of several talks tofollow. In addition, ECH plans are shown. The toroidal magnetic field will be doubled to
0.5 T. The second harmonic and fundamental resonance layers will be at center of thedevice and inboard side, respectively. Heating scenarios at 0.5 T are considered throughone pass absorption analysis using the TASK/WR code. The 60-keV energetic electronsof several percentage populations are considered as well as the bulk electrons of 500 eV.
The incident 28-GHz waves are strongly damped at the fundamental and second harmonicresonances in low- and high-density plasmas, respectively. The strong damping at thesecond harmonic layer is considered through a resonant ellipse analysis in the momentum
space. EBWHCD scenarios based on the multiple ray-tracing analysis by using theGaussian optics are explained.
Takumi Onchi
 The latest plasma current start-up experiment conducted through electron cyclotron
heating in the QUEST spherical tokamak is introduced. By applying toroidal electric fieldin the anti-direction to plasma current, the growth of energetic electrons is suppressed.
Efficient bulk electron heating has been observed with such retarding electric field.
Masayuki Ono
The elimination of the need for an Ohmic heating solenoid may be the most impactfuldesign driver for the realization of economical compact fusion tokamak reactor systems.
However, this would require fully non-inductive start-up and current ramp-up from zero
plasma current and low electron temperature of sub-keV to the full plasma current of ~10 - 15 MA at 20 - 30 keV electron temperature. To address this challenge, an efficientsolenoid-free start-up and ramp-up scenario utilizing a low-field-side-launched
extraordinary mode at the fundamental electron cyclotron harmonic frequency (X-I) is
proposed, which has more than two orders of magnitude higher electron cyclotron current
drive (ECCD) efficiency than the conventional ECCD for the sub-keV start-up regime. A
time dependent model was developed to simulate the start-up scenarios. For the Spherical
Tokamak Advanced Reactor (STAR), it was found that to fully non-inductively ramp-up
to 15 MA, it would take about 25 MW of EC power at 170 GHz. Because of the relatively
large plasma volume of STAR, radiation losses must be considered. It is important tomake sure that high Z impurities are kept sufficiently low during the early current startup phase where the temperature is sub-keV range. Since the initial current ramp up takes
place at a factor of ten lower density compared to the sustained regimes, it is important
to transition into a higher bootstrap fraction discharge at lower density to minimize the
ECCD power requirement during the densification. For the sustainment phase an array ofeight gyrotron launchers with a total of about 60 MW of fundamental O-mode was foundto be sufficient to provide the required axis-peaked external current drive. Highefficiencies between 19 – 57 kA/MW were found with optimal aiming, and these wereresilient to small changes in aiming angles and density and temperature profiles.
Ryuya Ikezoe
Energetic particle probe (EPP) developed on QUEST for the studies of fast electrons
gave (1) radial profile of fast electron flux, showing the wide existing range exceedingthe local limiter, (2) its pitch-angle profile, and (3) its fluctuation with excited kinetic
modes. A rotation drive system has been attached to the EPP, enabling fine pitch-angle
distribution measurement. As a result, strong correlation between the pitch-angle and
the energy spectrum of fast electrons of > keV was found to emerge at far SOL on
QUEST, suggesting a narrow velocity distribution in this region.
Makoto Hasegawa
 Using Deep Neural Network (DNN), plasma shapes can be predicted quickly and withhigh accuracy. It is necessary to consider new methods that handle not only plasma shape
but also plasma pressure, beta value, etc. For practical applications, it is necessary toincorporate the effect of local toroidal current distributed in the z direction.
Luis Delgado-Aparicio
Multi-energy soft and hard x-ray (SXR & HXR) pinhole cameras have been designed,
built and deployed at Alcator C-Mod, MST and WEST to aid the study of particle andthermal transport, heating and RF current drive as well as MHD stability physics. This
novel imaging diagnostic technique employs a pixelated xray detector in which the lower
energy threshold for photon detection can be adjusted independently on each pixel. The
2D detector of choice is a PILATUS3 100K configuration fielded with a 0.45 mm thicksilicon and 1.0 mm thick CdTe sensors and ~100 kpixels sensitive to photon energies
between 1.6 to 30 keV and 20-200 keV, respectively. Careful trimming of the lower
energy threshold for photon detection allowed our team to circumvent the contribution
from radiative recombination steps and line-emission from medium to high-Z impurities
like Al, Mo and W. Central values of Te can be obtained by modeling the slope of thecontinuum radiation from ratios of the inverted radial emissivity profiles over multiple
energy ranges with no a-priori assumptions of plasma profiles, magnetic fieldreconstruction constraints, high-density limitations, or need of shot-to-shot
reproducibility. The latest of our results include measuring the temporal evolution ofcentral electron temperature at 100 Hz in 70 s steady-state L-mode at WEST at CEA. A
novel application has recently been tested tokamak plasmas for early detection, 1D
imaging and study of the birth, exponential growth and saturation of runaway electrons
at energies comparable to 100 × Te,0. We have also used the high-efficiency of the CdTe
sensor at high energies to probe non-Maxwellian tails and the resultant emissionanisotropies at the edge and core of WEST’s LHCD plasmas.
Vladimir Shevchenko
A multi-frequency electron cyclotron resonance heating (ECRH) and current drive(CD) system is currently under construction on the ST40 spherical tokamak at Tokamak
Energy Ltd. The system employs 1 Kyoto Fusioneering gyrotron with a maximum output
power of 1 MW and a pulse length of 2s. The gyrotron can be tuned to operate either at
104 GHz or 137 GHz. The system is designed to study non-inductive plasma start-up,
current ramp-up and sustainment. At present ST40 has the highest for STs toroidal
magnetic field up to 3T which allows testing of reactor relevant radio frequency (RF)based methods of plasma start-up, current ramp-up and sustainment with commerciallyavailable MW range RF power sources. Well-established conventional ECRH and CD
schemes are planned to be tested in ST40 plasma using a poloidally and toroidally
steerable launcher installed at low field side (LFS) of the tokamak. In addition toconventional ECRH, plasma start-up and CD scenarios using electron Bernstein waves(EBW) are planned to be tested on ST40. Efficient EBW excitation in the plasma requires
RF power to be launched as a slow extra-ordinary (X) mode from the high field side
(HFS) of the machine. To achieve that, the O-mode polarized RF beam is launched from
LFS towards mirror-polariser (MP) installed on the central post of ST40. At MP the RF
power is mode-converted into the X mode and reflected towards the fundamental EC
resonance layer. The slow X mode experiences a subsequent mode conversion into the
EBW mode at the upper hybrid resonance (UHR) and then EBW propagates back to theEC resonance. This scheme allows experimental studies of non-inductive plasma start-up,
current ramp-up and sustainment. The present status of the ECRH system development
and plans for the first experimental campaign will be presented and discussed.
Bodhi Biswas Electron Bernstein waves (EBWs) are theorised to efficiently drive current in reactorgrade spherical tokamaks, e.g. STEP. At high temperatures (Te > 5 keV), relativistic
effects can significantly impact wave propagation (and surely impacts wave damping).
This work presents relativistic calculations of EBW wave propagation, damping, andcurrent drive (CD) in a conceptual STEP plasma. Kramers-Kronig relations are exploited
to efficiently evaluate the fully-relativistic dispersion relation for arbitrary wave-vectors,
leading to a ~ 50x speed-up compared to previous efforts. A recently verified linear
adjoint model is used to estimate CD efficiency. Thus, for the first time, large parametricscans of fully-relativistic EBW CD simulations are performed through ray-tracing. In
STEP, three main classes of rays are identified. The first class propogate deep into thecore (rho < 0.5), but only exist if relativistic effects are accounted for. They damp strongly
at the 1st harmonic on nearly-thermal electrons and thus drive little current. A secondclass of rays propagate to intermediate depths (rho = 0.3 - 0.7) before damping at the 2nd
harmonic. Their CD efficiencies are significantly altered due to relativistic changes to
trajectory and polarisation. The third class of rays damp strongly far off-axis (rho > 0.7),
predominantly at the first harmonic. These ray trajectories are sufficiently short and"cold" such that relativistic effects are unimportant. Presently, the EBW antennas for
STEP are being optimised around this third class of rays due to their large CD efficiencies.
This suggests that non-relativistic simulations are adequate for this particular operating
point.
Roger Raman
Results from QUEST show that Transient CHI start-up is compatible with a floatingbiased electrode (FSB) configuration. The FSB configuration is much more suitable fora fusion reactor as large vacuum insulators are not needed. Transient CHI discharges havebeen generated over a very wide parameter range, and the discharges can be easily started.
About 100 kA closed flux current has been generated. This is consistent with earlier
current startup projections for QUEST. Near term plans are to reduce the electron density
so that the discharges coupled to induction can be heated, initially using ECH & later
using EBW.
Shin Kubo Project of direct detection of EBW in QUEST using HCN laser scattering is briefly
introduced. The estimation of the power flux of EBW is essential for the heating/current

drive and scattering consideration. It is indicated that optical vortex might excite EBW
directly from low field side by mode conversion. For the precise estimation and power
flux and EBW excitation by optical vortex, a new Quasi-optical beam tracing code thattakes diffraction into account (EQUASI) is under development.
Atsushi Fukuyama
Kinetic full wave analysis using the integral form of dielectric tensor has beenformulated and applied to the analysis of the O-X-B mode conversion of electron
cyclotron waves in QUEST. Two-dimensional analysis on midplane in tokamak
configuration (slab model) has shown the spatial structure of O-mode, X-mode, andelectron Bernstein wave (EBW). It was confirmed that O-mode is efficiently converted
to EBW near the optimum injection angle and a small amount of collision near the upperhybrid layer causes strong damping of the wave. Analysis on a poloidal cross section
requires the formulation including inhomogeneity of magnetic field strength along thefield line, and the implementation in 2D FEM analysis is under way.
Nicola Bertelli
An analytical edge density fluctuation model was implemented in Petra-M toinvestigate its impact on the HHFW propagation. 2D Petra-M simulations with a cold
plasma model clearly show a significant perturbation of the HHFW propagation to thecore plasma when density fluctuations with large amplitudes (A > 30%) exist. Similar
results in terms of HHFW propagation are found when a local hot plasma approximation
is employed. With the local hot plasma model, we can also make some observations on
the effects on the edge perturbations on the ion and electron absorption. For amplitude ofthe edge density perturbations larger than 10% and for the plasma/wave parameters usedin these simulations, the density fluctuations seem to have a strong impact on both theelectron and ion absorption. The deuterium/hydrogen power deposition area tends tospread vertically and scatter into multiple sub-regions. 3D Petra-M simulations were
performed assuming a 3D axisymmetric edge density perturbation for a cold plasma
model for three antenna phasing values: 30, 90, and 150 degrees. Overall reduction of theelectric field amplitude in the core plasma for large A was found. A strong modificationof the vertical wave field mainly on the poloidal cross-section as similarly found in the
2D runs for a cold plasma. Finally, initial attempts to implement an edge 3D filament
geometry along the magnetic field line in the NSTX-U geometry used in Petra-M wasalso shown and discussed. This subject though is still in progress.
Syun’ichi Shiraiwa
It is well known that the dielectric response to the RF fields in hot plasma is non-local,
and the Maxwell wave problem is an integro-differential equation. A differential form of
dielectric operator, based on the small kԋȡ expansion, typically includes up-to the second
order terms, and thus the use of such an operator is limited to the waves that satisfy kԋȡ< 1. We propose an alternative approach to construct a dielectric operator, which includes
all-order finite Larmor radius effects without explicitly containing higher orderderivatives. We use a rational approximation of the plasma dielectric tensor in the wave
number space, in order to yield a differential operator acting on the dielectric current (J).
Then, we solve the resultant partial differential equation for J simultaneously with theMaxwell equation. To demonstrate this approach, we use the Petra-M framework andsolve the 1D O-X-B mode-conversion of the electron Bernstein wave in the nonrelativistic Maxwellian plasma. An agreement with analytic calculation and theconservation of wave energy carried by the Poynting flux and electron thermal motion(“sloshing”) is found. An approach to extend the operator in a 2D poloidal cross-section
setting was also discussed.

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Date: March 7

Visiting scientists: (name)Xiang Gao

(position)

Professor

2023(university / institute) Institute of Plasma Physics,
Chinese Academy of Sciences

Host scientist: (name)

Kazuaki Hanada(position)

Professor(university / institute)

KyushuResearch period: (from) March 12 2023

(to)University
March 16 2024

Research subject: Joint study of long pulse high beta discharges andrelated edge turbulence transport in steady state operation (SSO) plasmas
on QUEST and EAST㸦ᵝᘧ 11࣭ᣐⅬ㸧

Introduction
Steady state operation (SSO) of tokamak plasma is one of the basic requirements for future fusion
reactors. Long pulse high beta operation is one of important missions for ITER. Joint study long pulse
high beta discharges in SSO plasma research field on QUEST and EAST is strongly supporting ITER
experiment from both experience and theory. In 2023, the collaboration research continue focused on the
power balance in SSO high performance discharge and coupling of injected energy and plasma during
discharge, which is benefit for the SSO high beta discharges of EAST and QUEST. A steady-state
plasma with a world-record pulse length of 403 s H mode plasma was obtained, where the density andthe divertor peak heat flux were well controlled, with no core impurity accumulation.
With this visit, I will also give an annual summary presentation of “Hybrid plasma and tungsten
transport on EAST tokamak”, which introduced the recent results hybrid plasma physics study on EAST
and to discuss with our QUEST collaborators.

New results in 2023-2024
EAST-Highlights: 403-second Reproducible H-mode
Record Duration of 403-second Reproducible H-mode Plasma Achieved with Tungsten Divertor on
EAST, as shown in figure 1. To access this steady state long-duration H-mode plasmas, experiments
have been performed in using LHCD at 1.6MW and ECRH at 1.7MW. H98y2 >1.3, fGr~0.7, zero injected
torque ȕP~2.5, ȕN ~1.5, fBS>50%, Small ELM (fELM >2.5kHz) with negligible transient heat load.
Robust iso-flux control with SP to W-divertor. It is a new milestone in Fusion community.

The operation regime was extended in last year. Enable investigation on key physics (coreturbulence, MHD, stability…) in ITER-like condition, as shown in figure 2.

Fig. 1. Waveform of the 403s reproducible H-mode discharge #122254 and #122296

㸦ᵝᘧ 11࣭ᣐⅬ㸧

Fig. 2. The operation regime was extended
Fig. 3 represents Tungsten transport and its Effect on the Pedestal in EAST Hybrid Plasmas. The
poloidal asymmetry of tungsten impurity due to larger toroidal rotation velocity can enhance theneoclassical pinch of heavy impurities, then leading the central heavy impurities accumulation between
2.6 s and 3.4 s. The W emission decreases gradually when counter-NBI injected at 3.5s and the toroidal
rotation velocity decrease gradually.
Fig. 4 represents From 4.3 s to 4.7 s, the core density increase with almost the same edge electron
density, where the toroidal rotation velocity is only 50 km/s. The W content starts to increase slowly
from 4.35 s. The increase of the Mo31+ and Fe22+ emission lines diagnosed by EUV can be observed
during the period of increased central electron density (4.3–4.7 s), which does not appear before 4.3 s.
The light impurity C (carbon) also starts to accumulate even earlier than the Fe22+. These results showthat the peaking of electron density and improved particles confinement maybe play an important role inboth the heavy and light impurities accumulation. The simulation reproduces the experimental
observations of W accumulation and identifies that neoclassical inward pinch by the toroidal rotation andturbulence suppression by the large density peaking of the bulk plasma are the main reasons for the W
accumulation respectively. Pedestal density increased during tungsten accumulation from 3.2s to 3.4s
No change at ELM frequency during tungsten accumulation.

㸦ᵝᘧ 11࣭ᣐⅬ㸧

Fig. 3. The poloidal asymmetry of tungsten impurity due to larger toroidal rotation velocity canenhance the neoclassical pinch of heavy impurities

Fig. 4. Tungsten transport in EAST hybrid discharge

Summary
Partly support with this joint research, record Duration of 403-second Reproducible
H-mode Plasma Achieved with Tungsten Divertor on EAST, the operation regime was
extended on EAST in last year and tungsten transport in EAST hybrid discharge was㸦ᵝᘧ 11࣭ᣐⅬ㸧

studied in detail.

Experiments of hybrid operational scenario have been carried out on EAST

tokamak with ITER-like tungsten (W) divertors recently. In the hybrid H-mode plasma, the internaltransport barrier (ITB) has been obtained with central flat q prfile and it is found that the fishbonemode(m/n=1/1) can be beneficial to sustain the central flat q(0˅=1 profile with a stable ITB. The
behavior of W in the core of hybrid plasma scenario on EAST with ITER-like divertor is studied. W
accumulation

is

often

observed

andseriously

degradestheplasmaperformance.

It is found that the toroidal rotation and density peaking of the bulk plasma are usually large in thecentral region, which is particularly prone to the W accumulation. The simulation reproduces theexperimental observations of W accumulation and identifies the neoclassical inward convection/pinch
velocity of W due to the large density peaking of the bulk plasma and toroidal rotation in the central
region as one of the main reasons for the W accumulation. These results will be compared with QUEST
results and made further analysis during my stay.

Acknowledgement and comments:
Work supported by the international joint research at the Joint Usage of Research Centers for Applied
Mechanics for 2023. I would like to thank our host, Professor K. Hanada. We hope that the international
joint research at the Joint Usage of Research Centers for Applied Mechanics could continue to enhance
China-Japan cooperation on fusion plasma research in the future.

My Co-Publications in 2023-2024:[1] Yunfei Wang, Kazuaki Hanada, Haiqing Liu, Xiang Gao et al., " Hot spots induced by RF-accelerated
electrons in the scrape-off layer on Experimental Advanced Superconducting Tokamak ", Nuclear Fusion(2023). DOI 10.1088/1741-4326/acb726[2] Yunfei Wang, Kazuaki Hanada, ……, Xiang Gao, et al., “Phase jump detection and correction
based

on

the

supportvectormachine”,

Plasmaphys.

Controlfusion,2023,

https://doi.org/10.1088/1361-6587/accaa2.
[3] X. Gao*, 瀖瀖, H.Q. Liu澿瀖瀖澿澳K. Hanada and the EAST team., " Tungsten transport and its Effect on
the Pedestal in EAST Hybrid Plasmas ", 41st ITPA meeting of PEP Group, April 24-28, 2023
[2] X. Gao*, 瀖瀖, H.Q. Liu澿澳 K. Hanada, 瀖瀖澿澳 and the EAST team., " Tungsten transport in hybrid
discharges on EAST tokamak ", 10th Asia Pacific-Transport Working Group Meeting, June 13-16, 2023
Hanyang University, Seoul, Korea.

(Signature)(Name in print) Xiang Gao        ᅜ㝿໬᥎㐍ඹྠ◊✲ᴫせ
1R10

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RIAM JOINT RESEARCH REPORT SUMMARY (English Form)
1. Research ID: No.10 _23NU-6
2. Research Title: The research on the confinement and loss mechanism of alpha particle through the research ofenergetic electron on QUEST
3. Category:International

4. Applicant
Affiliation: Institute of Plasma Physics, Chinese Academy of Sciences
Name: Yinxian Jie
5. RIAM Attendant:

K. Hanada

6. Summary (150~200 words in Japanese or 100~150 words in English):After COVID-19 pandemicˈthis year we worked on QUEST in site from March 1
2023 to March 8 2023. Though the Research Title wasĀthe research on the confinement
and loss mechanism of alpha particle through the research of energetic electron on
QUEST” , but the real work was : discussing the paper “Hot spots induced by
RF-accelerated electrons in the scrape-off layer on Experimental Advanced
Superconducting Tokamak” by Mr. Yunfei Wang.
Preventing impurity emission from hot spots on plasma-facing materials is a criticalissue in the maintenance of high-performance plasma on the Experimental Advanced
Superconducting Tokamak (EAST). In this study, experimental and theoretical analyses
were performed to investigate the mechanism of hot spot formation.

*) Submit either one of Japanese or English forms.

Research subject: The research on the confinement and loss mechanism of alphaparticle through the research of energetic electron on QUEST
I discussed the paper in details with Mr.Yunfei Wang. And the paper “Hot spots induced by
RF-accelerated electrons in the scrape-off layer on Experimental Advanced Superconducting
Tokamak” by Mr. Yunfei Wang has published in Nucl.Fusion.
Preventing impurity emission from hot spots on plasma-facing materials is a critical issue inthe maintenance of high-performance plasma on the Experimental Advanced Superconducting
Tokamak (EAST). In this study, experimental and theoretical analyses were performed to investigate
the mechanism of hot spot formation.

Experiments on plasma configuration control indicated thatthe reduction in the gap between the lower (secondary) separatrix and lower hybrid antenna iseffective in preventing hot spot formation on the lower divertor, which frequently emits impurities inlong-duration discharges.
This effectiveness was quantitatively confirmed by magnetic field lines tracking simulation andcalorimetric measurement of divertors in the experiment. Two-frequency power modulation of thelower hybrid wave (LHW) was conducted to evaluate power deposition on the scrape-off layer (SOL)
during propagation from the LHW antenna to the main plasma. This experiment clarified that
LHW-accelerated electrons in the SOL via collision damping deliver their energies to hot spots along
the magnetic field line. These findings help alleviate or even liminate the formation of hot spots andmaintain the performance of plasma.
Hot spots are caused by the excessive localized heat load on the PFCs. Although hot spot
formation must be avoided, hot spots often appear on the divertors, main limiter, and LHW guarding
limiter during discharges in the EAST. In this study, we investigated the mechanisms underlying the
hot spot formation on the lower divertor during the EAST 2017 campaign and found that two factors,
namely the magnetic configuration in the SOL and the energy deposition of the LHW in the SOL,
played an important role in hot spot formation. By slightly changing the SOL plasma configuration,
the hot spot on the lower divertor was effectively alleviated. This helped achieve a record ofsteady-state H-mode plasma in the EAST for 101.2 s. Experiment analyses and GENRAY/CQL3D
simulations showed that the two LHWs had different plasma heating and current driving efficiencies
in the main plasma owing to their different frequencies; the LHW at 2.45 GHz likely deposits moreenergy than the LHW at 4.6 GHz in the SOL through collision damping, which leads to hot spot
formation in the LHW modulation experiment.
The findings of this study provide two primary insights. First, reduce the auxiliary heating
power (such as LHW) deposition in the SOL. This part of the energy directly contrib焁utes to the heatload of related PFCs that are magnetically connected from the SOL. Therefore, efforts to increase theauxiliary heating power deposition in the core plasma for heating and current driving are needed.
This will improve the confinement performance of the plasma and reduce the cost-of-energy of thefusion device. Second, the heat load between different PFCs can be redistributed by slightly
adjusting the magnetic configuration in SOL. This can be used to alleviate excessive heat load on aparticular PFC, thus avoiding problems, such as impurity emission and subsequent plasma
degradation. In the near future, the EAST aims to realize a higher performance plasma operation withhigher power injection; there焁fore, it is important to achieve full FoV detection for PFCs on the
EAST to monitor the condition of PFCs, including hot spots. Besides, the mechanism of association
between the LHW and plasma should be further investigated to improve the efficiency of plasma
heating and current driving through the LHW to achieve lengthier H-mode operations andnoninductive current driving. These results have potential applications in exploring advanced
operating modes on CFETR in China and ITER.

(Signature)(Name in print)

Y. JieYinxian Jieᅜ㝿໬᥎㐍ඹྠ◊✲ᴫせ㻌
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Date: March 7

Visiting scientists: (name)2024

Haiqing LIU(position)

Professor(university / institute) Institute of Plasma Physics,
Chinese Academy of Sciences

Host scientist: (name)

Kazuaki Hanada(position)(university / institute)

Professor
KyushuResearch period: (from) March 12 2024

University(to)March 16 2024

Research subject: Joint study of calorimetric measurement of heat loadand power balance estimation and measurement and simulation ofenergetic electrons loss in steady state operation (SSO) plasmas on
QUEST and EAST㸦ᵝᘧ 11࣭ᣐⅬ㸧

Introduction
Maintaining long-pulse steady-state operation of plasma is one of the crucial prerequisites for achieving
commercial fusion energy in the near future. Both the QUEST and EAST tokamaks possess thecapability to sustain plasma long-pulse steady-state operation, serving as excellent experimental
platforms for relevant research. One of the main focuses of collaborative research this year is to explore
the causes of hot spot formation. Through experimental data and simulation analysis, two results havebeen obtained: firstly, changes of the magnetic configuration in the scrape-off layer (SOL) have asignificant impact on the hot spot formation, and the appearance of hot spots is accompanied by a greatchange of heat load distribution between different plasma-facing components (PFCs). Secondly, the
LHW can deposit energy to electron in the SOL through the collision damping, these electrons movealong the magnetic field lines then attack the PFCs, cause the hot spot formation.
The enhancement of plasma confinement is highly important for sustaining long-pulse steady-state
plasma operation and improving the economic viability of fusion power generation. A new study of ‘Ne
injection with improved confinement’ has been performed on EAST. Ne injection with a finite rate canchange the equilibrium with reversed magnetic shear of the plasma and promote improvement of theconfinement.
With the continuous development of artificial intelligence algorithms and the rapid advancement ofcomputing power, the field of AI has experienced rapid growth in recent years, as exemplified by
ChatGPT, and is increasingly being applied in scientific research. Magnetic confinement fusion researchinherently possesses massive datasets, making it highly suitable for integration with machine learning(ML). Another collaborative research endeavor this year is ‘phase jump detection and correction basedon the support vector machine’, representing an attempt to integrate machine learning with fusion
research. The POINT system on EAST has measured a large amount of chord-integrated electron density
data, which can be categorized into two types: normal data and anomalous data caused by fringe jumps.
By identifying classification features, ML algorithms automatically determine feature boundaries,
thereby detecting the fringe jump data from the database. This approach has yielded promising results.
During this visit, I will also give an annual summary presentation which introduced the recent results
and progress of the steady state operation and physics research on EAST and to discuss with our QUEST
collaborators.
.

Recent results in 2023-2024
Preventing the emission of impurities from hot spots on PFCs represents a crucial challenge inmaintaining high-performance plasma on the EAST. This study conducted experimental and theoreticalanalyses to investigate the mechanism underlying hot spot formation. Experimental investigations into
plasma configuration control revealed that reducing the gap between the secondary separatrix and the
LHW antenna effectively mitigates hot spot formation on the divertor. This effectiveness wasquantitatively confirmed through magnetic field lines tracking simulations and calorimetricmeasurements of divertors in the experiment. Figure 1 shows the hot spot gradually formed on the lower
divertor, on the 101.2 s long-pulse H-mode discharge, #73 999, in the 2017 campaign. The zero drift ofthe magnetic measurement system resulted in small, persistent changes of the plasma configuration㸦ᵝᘧ 11࣭ᣐⅬ㸧during discharges, which cause the hot spot formation.
Additionally, two-frequency power modulation of the LHW was implemented to assess power
deposition on the SOL during propagation from the LHW antenna to the main plasma. This
experimentation elucidated that LHW-accelerated electrons in the SOL, via collision damping, transfer
their energies to hot spots along the magnetic field line. These findings contribute to the mitigation or
potential elimination of hot spot formation, thereby supporting the maintenance of plasma performance.

Figure 1. Photographs of the EAST discharge #73 999 at 50 s, 55 s, 60 s, and 65 s obtained using avisible-light camera. The hot spot gradually formed.
The effect of Ne injection on improved plasma confinement is investigated in the EAST. A series of Ne
injection experiments were conducted, wherein the safety factor q profile and electron-scale turbulence
were examined using the POINT system and a CO2 laser collective scattering system. It was found that
Ne injection at an appropriate rate can induce negative magnetic shear in the plasma core, thereby
suppressing electron-scale turbulence. Moreover, continuous Ne injection under reversed shear
conditions further decreases the intensity of electron-scale turbulence, leading to an increase in coreelectron temperature and improvement in confinement. The QuaLiKiz model is employed to simulate theimpact of impurity and reversed q on turbulence. The combined effects of negative magnetic shear and
Ne injection on turbulence suppression surpass the inherent effect of the impurity alone, which
potentially elucidates the observed increase in electron temperature and turbulence suppression.
Furthermore, the relationship between pedestal structure induced by Ne injection and LHW-driven
current deposition is discussed. These findings offer a novel perspective for enhancing confinement
through Ne injection, suggesting the adjustment of Ne injection to modify the ideal plasma equilibrium.
Figure 3 shows the evolution of turbulence with Ne injection in step 2. In step 2, all electron-scale
turbulence in the interval is further suppressed, the maximum reduction of integrated turbulence power ishalf. And the average reduction ratio is about 30%, which is higher than that outside the interval.
Turbulence suppression in step 1 and step 2 may be the reason of Te increase in step 2.

㸦ᵝᘧ 11࣭ᣐⅬ㸧

Figure 2. Relation of Ne content change rate to relative variation of turbulence amplitude with kș = 12
cmí1 at step 1. Here, ¨S = S1íS0, where S1 and S0 are the amplitude of turbulence measured by CO2
system at the end and beginning of step 1.

Figure 3. Relation of Ne content change rate to relative variation of turbulence amplitude with kș = 12
cmí1 at step 2. Here, ¨S = S1íS0, where S1 and S0 are the amplitude of turbulence measured by CO2
system at the end and beginning of step 2.
Interferometers are commonly utilized for electron density measurements in magnetically confinedplasma. These measurements entail comparisons of phase shift variations between the probe andreference laser beams. The plasma electron density ideally exhibits continuous variation during
discharge, the fringe jump is a step-like change of the apparent electron density caused by a sudden jumpof the measured phase shift. Such fringe jumps can significantly compromise the accuracy ofinterferometric measurements. This study addresses the fringe jump issue in the POINT system of the
EAST by introducing a support vector machine model for electron density fringe jump correction. The
proposed model effectively distinguishes fringe jump data from raw measurement data, demonstrating
robustness against noise and interference, and subsequently rectifies the jump. This model markedly
enhances the efficiency and precision of electron density data correction derived from the POINT system
in EAST. Integration of this model into the plasma control system is anticipated to enable more accurate
real-time electron density feedback control. One example to demonstrate the performance of fringe jumpdetection and correction by the support vector machine model is shown in figure 4. In this figure, all 23
fringe jumps in chord 8 were detected and corrected. With the advantage of multi-chord measurement of
the POINT system, the accuracy of the corrected line-integrated electron density can be confirmed by㸦ᵝᘧ 11࣭ᣐⅬ㸧using the measurement data of two adjacent chords in space. Further, the electron density profile can becalculated by using the corrected electron density data.

Figure 4. Apparent line-integrated electron density measured by the chord 7 (green), 8 (black), and 9(blue) of the POINT system for discharge 80142, and the corrected electron density for the chord 8 (red).

Discussions
The collaborative research this year continues to focus on the plasma long-pulse steady-state operation
and achieve good results, which include two parts, avoiding excessive local heat loads on the PFCs andimproving plasma confinement through neon seeding. Both two topics conducive to achieving plasma
long-pulse steady-state operation. The study of avoiding excessive local heat loads on the PFCs is
conducted by Dr. Wang Yunfei, Prof. Hanada’s doctor student, with whom I have engaged in many
fruitful discussions. The findings of this study yield two principal insights. Firstly, mitigating theauxiliary heating power deposition in the SOL is crucial. A substantial portion of this energy directly
contributes to the heat load on the PFCs. Hence, endeavors to enhance the deposition of auxiliary heating
power within the core plasma for both heating and current drive purposes are warranted. This approach
will enhance plasma confinement performance and reduce the cost-of-energy associated with fusion
devices. Secondly, redistribution of heat load among different PFCs can be achieved by making slightadjustments to the magnetic configuration within the SOL. This strategy can effectively alleviate
excessive heat loads on specific PFCs, thereby forestalling issues such as impurity emission andsubsequent plasma degradation.
The research on ‘electron-scale turbulence suppression under weak magnetic shear with neon seeding’ isperformed by Dr. Chu Yuqi, my doctor student. In this study, a new perspective on impurity
injection-induced confinement improvement is presented. For the ITER-like RF heating tokamak,equilibrium reestablishment by impurity injection should be considered. Maximizing the beneficial
effect of impurity injection and allowing it to be dominant in front of the deleterious effects of impurity
injection could help us to promote better plasma confinement. To promote rather a positive impact of
impurities on fusion power, it is necessary to further study the influence of impurity injection on thepedestal and the influence of impurity injection on turbulence suppression. Exploring suitable impurity
injection methods is important for future fusion devices.

㸦ᵝᘧ 11࣭ᣐⅬ㸧

Building upon this foundation, we have also explored the integration of machine learning into the fieldof fusion, yielding promising results. This part of research is completed by Dr. Wang Yunfei, utilizing
measurement data from POINT provided by EAST. This study introduces a novel ML-based method forelectron density fringe jump correction for the POINT system of the EAST tokamak. This method
automatically identifies and rectifies fringe jump data from the digital phase demodulator output,
offering high accuracy and robust noise tolerance, thereby notably enhancing the efficiency of
post-processing data from the POINT system. Furthermore, this method extends beyond specificdischarge devices and interferometer diagnostics, rendering it applicable to interferometer systems indiverse fusion devices. Consequently, this algorithm holds considerable promise for fusion dataprocessing applications. This model can be further enhanced and incorporated into the real-time electron
density feedback control algorithm of the Plasma Control System.
During this stay, I was also discussed with Prof. Hanada and Prof. Ido under this international joint
research frame. And we will make new co-proposals in the next EAST experimental campaign. We willcontinue to study the power balance (particle balance) estimation in steady state operation (SSO)
plasmas on QUEST and EAST.

Acknowledgement and comments:
Work supported by the international joint research at the Joint Usage of Research Centers for Applied
Mechanics for 2023. I would like to thank our host, Professor K. Hanada. We hope that the international
joint research at the Joint Usage of Research Centers for Applied Mechanics could continue to enhance
China-Japan cooperation on fusion plasma research in the future.

Co-publication list of the joint usage / research in 2023-2024:[1] Wang Y, Hanada K, Liu H, et al. Hot spots induced by RF-accelerated electrons in the scrape-off
layer on Experimental Advanced Superconducting Tokamak[J]. Nuclear Fusion, 2023, 63: 056001.
[2] Chu Y Q, Zhang S, Li P, et al. Observation of electron-scale turbulence suppression under weakmagnetic shear with neon seeding in EAST plasma[J]. Nuclear Fusion, 2023, 63: 086021.
[3] Wang Y, Hanada K, Sakurai D, et al. Phase jump detection and correction based on the support vector
machine[J]. Plasma Physics and Controlled Fusion, 2023, 65: 065001.
[4] X. Gao*, 瀖瀖, H.Q. Liu澿瀖瀖澿澳K. Hanada and the EAST team., " Tungsten transport and its Effect on
the Pedestal in EAST Hybrid Plasmas ", 41st ITPA meeting of PEP Group, April 24-28, 2023
[5] X. Gao*, 瀖瀖, H.Q. Liu澿澳 K. Hanada, 瀖瀖澿澳 and the EAST team., " Tungsten transport in hybrid
discharges on EAST tokamak ", 10th Asia Pacific-Transport Working Group Meeting, June 13-16, 2023
Hanyang University, Seoul, Korea.

(Signature)(Name in print) Haiqing Liu                     

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
                  !"!#$% 
&$          '     ( )     *& (    $ (    ( (      ( *       '         *      
(  +( (                *&         ( *,    (    (        '      (   $ (           *-          (   (             *&           
( !.      '           (   (      (      * 
-             (   *&    '          /    /  $      $0  )   *&        '   )  (        (               *&     & ,1         $    2 3*-   (      '   2!3 (( (    ((      *4         (         ( )     &*& 5  (    &2#3         #. '       5 *&                                  ,1*  & & '       67$,,,     ' 8( 89    :     (     ; (    <8   (   (* * '         * .* =  1                      ,1  (  * &     (   (     (        >  *  1 (    
 (   ?@#A$ 9A  &      ) *  '                  (    (   @A*!<BA*<<     ( @A*!B9/4  (
 5     9B A  10)*       $            '       (     (/   *4       (      283          
293*&      (       (           *4                   (   9=$          ($     *,   <8$  ; (   2<3  )             *              !  !
  

                  *,              (        (   2:3       (    *  '           (                     (*!*4    '        (           ( (     C       &      /       ( *           '                   (        !      ( *- (   (            '                         (         '   *-    ( (       (        (  (   (       (*#*&      (        <A
:A&          &*" # $%&$%%& !
%'    % ("()
*    ! %     +     *
! %     %      *!

,    !-          % ("()* .% %  !   %   !// *!

  &        5                    ) *  ,  (        (                //*  ,             (    ( * 4                    5                *&     (      ) *-(8             ,  D *6       (    $((*0        (     (       '    //    '      * & ( ,  D      (    '    *0   1 !%*  2345(((5(6 
7    %   5  8 3("()2345(((5(6 9 ? (       !.   (*9* -  (              8 *(*   3A     )                    *0    )      (             /(*&              $((       E F                 (   8        4   (   (                *&  / &   5 $       (  +     *  &  5 $            ($(*&       )  $    *  &              ( (       (      5 $       ( *  6             /                  
    *  &                                       *  4     (       ( (               *) ": 9*!2 !/    /  .   *%*    

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Ae=SWJN^THBInvestigation of ﬂow patterns in a linear magnetized plasma experiment(13 23NU-9)
N. Fahrenkamp
Institute of Physics, University of Greifswald,
Felix-Hausdorﬀ-Str.6, 17489 Greifswald, Germany

I.

AIM

Turbulence in a linear plasma device are driven by gradients. resulting from diﬀerent kinds instabilities,
like drift-waves or Kelvin-Helmholtz instabilities. Both can appear together as discussed in detail within
the concept of cross-ferroic turbulence [1] impacting the overall ﬂow pattern. Inside the source region, an
axial ﬂow from the source to the target is observed. Outside the source, we expect a return-ﬂow from thetarget towards the source occurred. Further investigations of the ﬂow pattern were done by [2] suggesting
behavior with changing plasma parameters. We aim to deepen the understanding of the ﬂow patterninside a linear magnetized plasma such as in PANTA. The unique tomography system at PANTA [3] oﬀers
the chance to compare 3D ﬂow data with conventional probe techniques. Three-dimensional tomographic
scans of the ﬂow paatern inside a linear magnetized plasma at diﬀerent axial positions can be measured.
To investigate the return-ﬂow in plasmas in a linear devices higher pressures at varying magnetic ﬁelds
can be investigated due to expected unrecorded ﬂows beyond the source radius. Preliminary studies do
not cover high pressures and/or high magnetic ﬁelds, additionally no data is present beyond the source
radius. Thus a wider radial area can be investigated. Ideally this tomographic data will give further
insight into the particle ﬂux of linear plasmas, because the return-ﬂow might mainly consist of neutral
particles. A related study was aimed by Dr. Stefan Knauer with the electrical 2D-probe system and
Mach-probes will gain information also about charged particles along the whole vacuum chamber. The
comparison of both approaches can be used to gain detailed information of the ﬂux inside the entire
chamber, although the tomography system only covers a region close to the source. This was the plan
we had in mind. Since it was not possible at sight to measure with the electrical 2D-probe system
and Mach-probes due to unforeseen diﬃculties on the ﬁrst day of our stay, we were forced to change
our measurement plan and aim of our research. First of all measurements from the year before wererepeated to increase the quality of these measurements for the use of publication. Furthermore the highionization rates of helicon discharges and their heating mechanism are not understood to this day. A key
piece to this understanding is the dispersion relation of the propagating wave. Eﬀects of the dispersion
relation also relate to a rarely studied parameter of the wave, its frequency. The inﬂuence of the heating
frequency on the phase transitions of the discharge modes was investigated in this research. The existenceof a critical magnetic ﬁeld Bc as postulated by Kwak et al. [4] was the research topic of Stefan Knauer.
Going beyond the work of Kwak we furthermore look for a dependency of Bc on the heating frequency
frf . PANTA allows us to study the inﬂuence of the frf on a helicon discharge, which is and will not be
possible for us in our helicon plasma device VINETA in Greifswald. In addition to the dependence of
Bc on frf , another topic of open research is the question in which way phase transitions of the discharge
modes (E-H-W modes, explained in the next section in more detial) dependent on frf , too. To increase
the insight of the scientiﬁc community into these topics we measured plasma discharges at PANTA withvarying magnetic ﬁelds, pressures, heating powers and heating frequencies to derive a dependency for themode transitions.
II.

SCIENTIFIC CREDENTIALS, THE E-H-W MODE TRANSITIONS

It is now well known that helicon discharges exhibit three modes of operation: a capacitive mode(known as the E mode), which is a low-density mode an inductive mode (known as the H mode) withhigher densities and a helicon-wave sustained mode (known as the W mode) with very high densities.
In [5] critical densities are proposed, observed with a double loop antenna (m = 0). The transition
between E and H-modes should occur when the skin depth δ is equal to the half radius of the Pyrex
tube [6]. Similarly a minimum density depending on the magnetic ﬁeld strength is necessary to observe
the ﬁrst longitudinal helicon-wave mode. At higher magnetic ﬁeld strength the critical density for the
H-W transition is higher and at higher frf the critical density for the H-W transition is lower [7]. This
relation is linear in theory, but somewhat less pronounced in experiments. In [6, 8], both with m = 1

antennas, a direct transition from E-mode to W-mode is observed. This is in contrast to a minimum
density responsible for the transition. The density in E-mode is simply to low to reach the critical density.
III.

EXPERIMENTAL SETUP

Experiments have been carried out in the linear magnetized plasma experiment PANTA [9] at RIAM
(Kyushu University). The experiments were led by Prof. Dr. Chanho Moon, he was also our ﬁrst contact.
We would like to thank him again for the experiments. PANTA exhibits a length of 4.05 m and a diameterof 45 cm. A homogeneous axial magnetic ﬁeld up to 150 mT is generated by a set of Helmholtz coils.
The plasma is heated by a double loop helicon source (m = 0) with a diameter of 10 cm at one endof the device. The typical cylindrical plasma radius is 5 cm. At the other end the plasma terminates
at a stainless steel iris diaphragm. The density has been measured as a function of power ne (P ) with
Langmuir probes. Each pin of the existing 5-pin probe was used as an independent Langmuir probe. A
combination of Langmuir measurements at diﬀerent radial positions of the 5 pin probe was used to geta radial density proﬁle. This proﬁle was subsequently ﬁtted with a Gaussian to get the center plasma
density ne . In a log(ne ) vs. log(P ) diagram, the behavior at lower (E-mode) ne ∼ P αE and higher
densities (W-mode) ne ∼ P αW and the H-W mode intersection ne,trans (Ptrans ) can now be ﬁtted.
IV.

RESULTS

These power scans have been conducted for diﬀerent heating frequencies frf , magnetic ﬁelds B0 and
neutral pressures p0 . The results are shown in ﬁgure 1 and ﬁgure 2. The central plasma density overabsorbed RF power at labeled p0 and B0 at diﬀerent heating frequencies are shown in logarithmic scaled
graphs. The three diﬀerent discharge modes are clearly distinguishable and color coded. The modes E(grey), H (red) and W (blue) are ﬁtted as described above and the intersection of the H-W modes is calculated. The results of the ﬁts P αE and P αW , and the calculated H-W mode intersection ne,trans (Ptrans )from the ﬁts are shown in table I.

FIG. 1: Plasma density over absorbed RF power at labeled p0 and B0 at frf = 6 MHz. The three
diﬀerent discharge modes are clearly visible. The modes E (grey), H (red) and W (blue) are ﬁtted andthe intersection of H-W is calculated.

2

FIG. 2: Plasma density over absorbed RF power at labeled p0 and B0 at frf = 10 MHz. The three
diﬀerent discharge modes are clearly visible. The modes E (grey), H (red) and W (blue) are ﬁtted andthe intersection of H-W is calculated.

TABLE I: Parameters of discharges, ﬁtted and calculated results for the graphs in ﬁgures 1 and 2.
frf /MHzp0 /sccm

B0 /mT

αE

αW

ne,trans /1018 m−3

6
6
6
6
10
10
10
10
10
10

20
20
60
60
20
20
20
60
60
60

50
100
50
100
50
100
150
50
100
150

1.49
1.80
1.35
0.84
0.75
0.63
1.41
1.05
0.83
0.93

0.36
0.46
0.13
0.18
1.09
0.18
0.40
0.72
0.42
0.49

3.65
4.40
3.95
3.77
0.35
4.71
3.84
1.54
2.01
1.27

3

Examine the values of ne,trans for the same heating frequency and neutral gas pressure, four pairs withmagnetic ﬁelds of 50 mT and 100 mT are found. Comparing the densities of the H-W transition for thesepairs, it is shown that at higher magnetic ﬁeld strength B the critical density for the H-W transition isrising. However, at higher magnetic ﬁeld strength of 150 mT at a heating frequency of frf = 10 MHz
this directly proportional dependency is not valid anymore. It seems that the magnetic ﬁeld strength
dependency of the critical density for the W-mode is not linear and shows a non-monotonic behaviour.
Taking a closer look at discharges with the same neutral gas pressure and magnetic ﬁeld strength but
varying frf , it is in accordance with [7] that at higher frf the critical density for the H-W transitions
is lower. Finally, with higher neutral gas pressure at constant frf and B0 the critical density of the
H-W transition is lower. Regarding the exponents αE and αW from the ﬁts ne ∼ P αE (E-mode) andne ∼ P αW (W-mode), an inverted correlation to the critical plasma density behavior in dependence ofthe discharge parameters frf , p0 and B0 is observable. Meaning, the higher the critical density is, theless dependent the plasma density is from higher Pabs , reducing the slope of the regression line, indicatinga plasma density limit for the W-mode. In E-mode the absorbed power should decrease with increasing
heating frequency at low collisionality, and this observed here at low pressure. At high collisionality theeﬀect is weaker and this is the case for higher pressure.
V.

CONCLUSION

Measurements in PANTA at diﬀerent discharge parameters have been performed to investigate thediﬀerent discharge modes and their corresponding critical densities. The results are very promising.
In comparison with the data regarding the existence of a critical magnetic ﬁeld in helicon discharges
underscore the ﬁndings discussed here. Currently both results together are prepared to be published.
However, the behavior shown here is not monotonic and we need a larger database to regress the functional
dependencies. We will tackle this in future measurement campaigns. The next steps to increase the insightof the scientiﬁc community into these topics are: a) turbulence characteristics at the position of the 5channel probe used to gain the proﬁles of the discharge. We assume that the upper limit of the density
originates from turbulence. And b) more data points with varying magnetic ﬁelds, pressures, heating
powers and heating frequencies to derive a clear functional dependency for the mode transitions. For (a)we would need to include 64Ch array measurements to the magnetic ﬁeld scans or other means to measure
the turbulence and for (b) we need more detailed multi dimensional scans of the pressure, magnetic ﬁeld
and power. Elaborating on these would underscore the importance of smaller laboratory experiments as
PANTA.

[1] S. Inagaki, T. Kobayashi, Y. Kosuga, S.-I. Itoh, T. Mitsuzono, Y. Nagashima, H. Arakawa, T. Yamada,Y. Miwa, N. Kasuya, et al., Scientiﬁc Reports 6 (2016).
[2] R. Hong, J. C. Li, R. Hajjar, S. Chakraborty Thakur, P. H. Diamond, and G. R. Tynan, Physics of Plasmas
25 (2018), ISSN 1089-7674, URL http://dx.doi.org/10.1063/1.5017884.
[3] C. Moon, K. Yamasaki, Y. Nagashima, S. Inagaki, T. Ido, T. Yamada, Y. Kasuya, N. Kosuga, M. Sasaki,
Y. Kawachi, D. Nishimura, et al., Scientiﬁc Reports 11, 3720 (2021).
[4] J. G. Kwak, H. D. Choi, H. I. Bak, S. Cho, J. G. Bak, and S. K. Kim, Physics of Plasmas 4, 1463 (1997).
[5] V. Kaeppelin, M. Carrère, and J. B. Faure, Review of Scientiﬁc Instruments 72, 4377 (2001), ISSN 00346748, https://pubs.aip.org/aip/rsi/article-pdf/72/12/4377/19295379/4377 1 online.pdf, URL https://doi.
org/10.1063/1.1419228.
[6] C. M. Franck, O. Grulke, and T. Klinger, Physics of Plasmas 10, 323 (2003).
[7] K. P. Shamrai, Plasma Sources Science and Technology 7, 499 (1998), URL https://dx.doi.org/10.1088/
0963-0252/7/4/008.
[8] S. C. Thakur, C. Brandt, L. Cui, J. J. Gosselin, A. D. Light, and G. R. Tynan, Plasma Sources Science andTechnology 23, 044006 (2014).
[9] T. Yamada, S.-I. Itoh, T. Maruta, N. Kasuya, S. Shinohara, Y. Nagashima, M. Yagi, K. Terasawa, S. Inagaki,
Y. Kawai, et al., Plasma and Fusion Research 3, 044 (2008).

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Development of Core-SOL-Divertor Model for Simulating
Tokamak with Impurities
Apiwat Wisitsorasak
Department of Physics, Faculty of Science,
King Mongkut’s University of Technology Thonburi,
Bangkok, Thailand

1

Introduction

Impurities in tokamak plasma introduce several deleterious eﬀects on the overall performance of the devices. A large amount of impurities can dilute the fuel and reduce the rateof fusion reactions. Furthermore, one of the most immediate eﬀects is the loss of radiatedpower, which leads to lower plasma temperatures. For example, impurity ions such as
oxygen and carbon, originating from the tokamak vessel, strongly cool the plasma near
the edge. However, excessive edge cooling destabilizes the plasma and leads to plasma
disruption, which can severely damage the wall and other structures [1]. On the other
hand, metal ions from the plasma-facing components, such as tungsten, can travel farther
from the edge and cause signiﬁcant radiation in the core. This prevents the plasma fromreaching a high enough temperature for ignition. Hence, the concentration of impurities
should be minimized. For a tokamak with a divertor conﬁguration, the impurities should1

be pumped away near the divertor; otherwise, they will accumulate in the vessel. Despite
the downside eﬀects of impurities, the radiation of plasma impurities nevertheless has somehelpful consequences. Injection of noble gases such as argon or neon is intentionally used
to increase radiation in the edge region of the plasma. A well-controlled amount of theseseeded impurities helps to disperse the plasma power exhaust over wider surface areas andreduce the temperature in front of the plasma-facing components.
In order to dynamically model the SOL and divertor plasma, one may reduce thecomplexity of the problem by only considering the transport along a magnetic ﬁeld line. The
ﬁve-point dynamics model further simpliﬁes the transport and is developed to investigate
the response of the plasma in the SOL and divertor regions at ﬁve points [2]: the stagnation
point (0), upstream throats of divertors (uA , uB ), and divertor plates (sA , sB ), as shownin ﬁgure 1.

Figure 1: Schematic diagram showing the geometry of the ﬁve-point model which considers
the transport along the magnetic ﬁeld.

2Model Equations
Through integrating the ﬂuid equations along the magnetic ﬂux tube in each region, one
obtains the dynamical equations of the density (n), ion particle ﬂux (Γ), electron (Te ), andion (Ti ) temperatures at each point along the open ﬁeld lines as follows [2]:

LSOL

dn0
dt

dnsA,BdtdΓuA,Bmi(la,b + (RA,B + 1) Ldiv )
2
dt
Ldiv

= −ΓuB − ΓuA + S0 LSOL ,(1)= −ΓuA,B − ΓsA,B + SA,B LSOL ,(2)= n0 (Te0 + Ti0 )−nSA,B (2TesA,B + (1 + g)TisA,B )1.5LSOLd (n0 Tj0 )dt= −QjuB − QjuA − δj J (φuB − φuA )+ (Wj0 + Wjeq0 + Wrad ) LSOL ,1.5Ldiv

d (nsA,B TjsA,B )
dt

(3)

(4)

= −QjuA,B − QjsA,B − δj σA,B J (φuA,B − φsA,B )+ (WjA,B + WjeqA,B + Wrad ) Ldiv ,(5)

where the subscript j refers to particle species (i for ions and e for electron) with δe = 1,
δi = 0, σA = −1 and σB = 1. S0 and W0 are the particle and energy source in the radial
direction. The neutral particle source and the ionization energy due to these neutrals are
given by SA,B and WjA,B , respectively. Wrad is the radiated energy due to impurity. Γand Q are the particle and heat ﬂux from the core. Detailed calculation of each term isprovided in reference [3, 2].

3

Modelling of Impurity Production and Transport
The dynamic ﬁve-point model can be extended to explicitly describe impurity production
and transport in the tokamak edge region. This task can be achieved by considering
the multi-ﬂuid equations of impurity species. Upon considering an impurity species withatomic number Zmax , the continuity equation of the jth charge state, j = 1, ..., Zmax , canbe written as [4, 1]:
dnj
dt

= −

dΓ⊥
dnj vjj−+ nj−1 αj−1 − nj (αj + βj ) + nj+1 βj+1 ,
dz
dx

(6)

and the momentum equation:d(mZ nj vj )dt

= −d(mZ nj vj2 ) d(mZ nj vj uj ) dpj−−− mZ n j
dz
dx
dz



vH − vj
τj= +mZ [nj1 vj−1 αj−1 − nj vj (αj + βj ) − nj+1 vj+1 βj+1 ] ,(7)where mZ is the impurity mass, nj is the impurity density of the jth charge state, vj is
the parallel component of velocity, uj is the perpendicular component, αj and βj are theionization and recombination rate coeﬃcients, respectively, vH is the velocity of hydrogenspecies, and τj is the impurity-hydrogen collision time. Note that z is the direction along
the ﬁeld line, and x is the perpendicular (radial) direction. Γ⊥
j is the impurity ﬂux from thecore. For simplicity, we may take the impurity temperature to be equal to the hydrogentemperature, i.e. TZ = Ti = TH , and the pressure pj = nj TH .
For the typical plasma edge, the temperature is less than 100 eV, and the density
is between 1018 and 1021 m−3 . The recombination of the impurity ions can be ignored.
Neglecting the perpendicular ﬂuxes and integrating equation 6 in the SOL region (z = −la4

to z = lb ) yields:
LSOL

dnj,0
= −Γj,uB − Γj,uA + LSOL (nj−1,0 αj−1,0 − nj,0 αj,0 + Sj,0 ) ,dt(8)where Sj,0 is the impurity source rate from the core. One can also integrate equation 6 inthe divertor regions (z = uA,B to z = sA,B ):dnj,sAdt
dnj,sB
Ldiv
dt

Ldiv

= Γj,uA − Γj,sA + Ldiv (nj−1,sA αj−1,sA − nj,sA αj,sA + Sj,sA ) ,(9)= Γj,uB − Γj,sB + Ldiv (nj−1,sB αj−1,sB − nj,sB αj,sB + Sj,sB ) .

(10)

Integrate equation 7 from z = 0 to the divertor plate of each side, one obtains:dΓj,uBmZ(lb + (Rj + 1)Ldiv )2
dt= nj,0 TH,0 − 2nj,SB TH,SB


mZ 1
1
mZ
+
nj,0 vH,0 + nj,sB vH,sB +(lb + (Rj + 1)Ldiv ) Γj,uB
τj 2
22+mz (lb + (Rj + 1)Ldiv ) (αj−1,uB Γj−1,uB − αj,uB Γj,uB ) ,where mZ nj vj2 is approximately less than nj TH . The impurity-ﬂux ampliﬁcation factor
is deﬁned as Rj ≡ Γj,sB /Γj,uB . The other equation on the other side can be obtained bychanging subscript uB to uA. In this analysis, the parallel velocity of the main ion vH is
unknowns, but it can be obtained by an appropriate model for the main-ion dynamics [1].
In principle, the impurity density (nj ) and particle ﬂux (Γj ) of each charge state at eachlocation along the SOL and divertor (equations 8 - 11) can be numerically determined byusing standard numerical techniques such as the Runge-Kutta method.
In the present work, we have developed a computer code based on Python programmingfor solving the dynamical equations for the densities and temperatures in the core, thescrape-oﬀ layer, and the divertor regions, which we described previously. The code is also

5

(11)

Figure 2: The ﬁgures show the time evolution of the plasma densities (n0 , nsA , nsB ),temperatures (Te0 , Ti0 , Te,sA , Te,sB , Ti,sA , Ti,sB ), particle and heat ﬂuxes (ΓuA , ΓuB , ΓsA ,ΓsB ), current density (J), particle and energy sources (S, W ), and impurity densities ofdiﬀerent charge states (nj ) at diﬀerent locations.
able to solve for the impurity densities of each charge state. Figure 2 illustrates an exampleof the time evolution of the plasma densities (n0 , nsA , nsB ), temperatures (Te0 , Ti0 , Te,sA ,Te,sB , Ti,sA , Ti,sB ), particle and heat ﬂuxes (ΓuA , ΓuB , ΓsA , ΓsB ), current density (J),particle and energy sources (S, W ), and impurity densities of diﬀerent charge states (nj )at diﬀerent locations. Note that the locations of 0, uA , uB , sA , and sB are referred to in
Figure 1. In future work, we will implement the code in Fortran and incorporate it into
the TASK code for simulating tokamak plasmas with more accurate models.

6

References[1] P. C. Stangeby et al., The plasma boundary of magnetic fusion devices, vol. 224. Institute of Physics Publishing Bristol, 2000.
[2] N. Hayashi, T. Takizuka, and M. Hosokawa, “Modeling of dynamic response of soldivertor plasmas to an elm crash,” Journal of nuclear materials, vol. 363, pp. 1044–
1049, 2007.
[3] N. Hayashi, T. Takizuka, A. Hatayama, and M. Ogasawara, “Onset condition of thermoelectric instability in divertor tokamaks,” Nuclear fusion, vol. 38, no. 11, p. 1695,
1998.
[4] R. Zagorski and F. Romanelli, “Modelling of impurity production and transport in the
scrape-oﬀ layer of a high density limiter tokamak,” Nuclear fusion, vol. 36, no. 7, p. 853,
1996.

7

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Three-dimensional electromagnetic particle-in-cell simulation for the instabilities
in the magnetized plasmas
Haejune Lee, Hanshin Cheong
Department of Electrical Engineering, Pusan National University, Busan 609-735, Korea
Understanding plasma instability and turbulence is essential for the advancement of nuclear fusion technology.
Therefore, direct measurements using probes have been used to study physical characteristics and energy
transport in various linear magnetized plasma devices. However, as fusion devices have become larger and more
complex in recent years, direct measurements have been challenged by plasma instabilities. To overcome these
difficulties, there is a growing need for research through simulation. This research presents to the complexityof magnetized-plasma behavior and energy transport through electrons. Focusing on phenomena that are
difficult in experimental measurement such as real-time changes in electron temperature, azimuthal changes inthe electric field within the plasma. So, comparison three-dimensional particle-in-cell (PIC) simulations usinga code called plexSIM with real experimental draw comprehensive conclusions. In addition, this research will
be carried out using a magnetized linear plasma device known as Plasma Assembled Nonlinear Turbulence
Analysis (PANTA). It is an ideal device for investigating the tokamak plasmas physics, as it is particularly
effective for studying nonlinear plasma turbulence. Under different power, pressure and magnetic field
conditions, comparing simulation with experimental data improves our understanding of plasma dynamics. It is
expected to contribute to the study of plasma stability and turbulence, paving the way for more sustainable andeffective fusion technologies.
Accordingly, we have conducted several experiments and studies in laboratory. One of collaborative research is a
PIC-simulation for plasma nonlinear instability. We are also trying to conduct plasma PIC simulations with the resultsof the PANTA experiment conducted by the RIAM, Kyushu university. We want to simulate changes in electric andmagnetic fields and wave propagation under the same conditions as PANTA. Through PIC simulation, we willcalculate the variation of electron temperature and potential energy and study energy transfer and plasma instability.

Fig.1 Schematic of PANTA (Plasma Assembly for Nonlinear Turbulence Analysis) GHYLFHWe needed real plasma data from the PANTA device to make the PIC simulation converge faster and give accurate
results. So, with Prof. Chanho Moon, we have first trained to understand the probe analysis system of PANTA and
Ball-pen probe. Fig. 1 shows Schematic of PANTA device.

Fig.2 Result of plasma floating potential by Ball-pen probe(left) and curve fitting by Langmuir probe(right).
We tried to find a usable point (a point that works well) for the ballpoint probe in the PANTA device, which is a
plasma-assembled nonlinear turbulence analysis device. Finally, We found a point where the ballpoint probe activates
well under certain conditions. Figure. 2 is the result of the PANTA experiment, which shows that under certain
conditions, the floating potential of the ballpoint probe closely matches the floating potential of the plasma. Also,being able to measure the potential of the plasma without applying voltage to the probe, i.e. without interference withthe plasma, is a powerful measure for studying the stability of the plasma.

Fig.3 The electron density (left), temperature (middle), and neutral density (right) contours in the drift plane at asnapshot in time.

Figure. 3 shows the neutral and plasma density in the drift plane at a single point in time through simulation [1]. We
will check the spatial distribution of variables such as density, electron temperature and ion temperature over time
and their shift in the theta direction. In addition, as Figure. 4, PIC simulations can be used to calculate real-timechanges of the induced magnetic fields and induced electric fields inside the plasma that are difficult to verify
experimentally.

Fig.4 The induced magnetic field and induced electric field snapshot at r-z plane inside the PANTA plasma.
In conclusion, in an international collaboration with RIAM, Kyushu University, using the PANTA device, we areattempting to simulate the nonlinear turbulence characteristics of helicon plasma and the heating mechanism ofhelicon plasma. Therefore, the final goal of this research is to understand the physical properties and generation
process of strongly magnetized helicon plasma. In addition, in future research, we will compare the frequency of thedominant wave inside the strongly magnetized helicon plasma with the simulation results using plasma floating
potential data values measured by the Langmuir probe. The wave frequency of the plasma is related to the energy
absorption or heating of electrons or ions. In future work, we will perform simulations in different regions, such asnear the source, in the middle, and at the end of a linear device. Finally, we will study the temperature evolution ofelectrons in the radial direction of the plasma and the energy transport in the plasma through simulations using
experimental values.

References.
[1] J. Leddy, B. Dudson, H. Willett, Simulation of the interaction between plasma turbulence and neutrals in linear
devices, Nucl. Mater. Energy 12 (2017) 994–998



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)*$,+1 &%".#1' /0) * ( -1+,LQ><:;=:jmclO5&FW4(N2/P6'Y)EKAW?hrn\^ef]hjpri (Fourier cutoff probe)9 Q>871.#PHSO6'DXHTPL@V>-V3EjmclOBAKDUOY'ERF?<:;=:jmclP8

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23NU-13
Development of a Fourier cutoff probe to fast measure
the plasma density profiles in PANTA
NA, Byungkeun(Korea Institute of Fusion Energy, Daejeon, Korea)

Turbulence is one of the most important transport phenomena in magnetically confinedplasmas, and PANTA provides an optimized experimental environment with linear cylindricalgeometry of magnetized plasma and multiple diagnostics to study the structure of the plasma turbulence.
For example, plasma structures such as ITG and ETG are generated in PANTA, and the plasma
diagnostics such as Langmuir probe array and the set of tomography is already developed. [1, 2] Theseexperimental studies provide a unique and important data set of spatiotemporal profile of the plasma
density and temperature where the plasma turbulence occurs. Further challenging to this study would
be independent measurements of electron density and temperature because the previous diagnostics
utilized the method where both parameters simultaneously affect the measurement results. For example,
constant electron temperature is assumed in the previous studies but it could be differ by location andtime because it is measured at the border of two different plasma characteristics. Even though theassumption is reasonable in the previous studies, the more direct diagnostics with less assumption isrequired to study in more various experimental conditions, such as ETG environment.
The diagnostics which provide an independent measurement of plasma density andtemperature is needed to provide more degree of freedom in experimental conditions. The ball-pen
probe and the cutoff probe are suggested to independently measure the electron temperature and density
respectively. Such diagnostics provide solid analysis even under steep gradient of electron density andtemperature without ambiguity. In this study, only the cutoff probe is focused because the ball-pen
probe is already developed in PANTA.
The cutoff probe is a diagnostics to find a plasma frequency which is converted to electron
density. From the transmission spectrum, the resonance peak is found and its frequency is a function ofଶ
only electron density as ݊௘ ሾͳͲଵ଺ ݉ିଷ ሿ ൌ ͳǤʹͶ ൈ ݂௖௨௧௢௙௙
ሾ‫ݖܪܩ‬ሿ. The Q-factor of the resonance isrelated to the electron temperature, but the peak frequency is dependent only on the electron density,
not the electron temperature. One another advantage of this method is that the measurement is
independent of the probe geometry. The conventional apparatus of the cutoff probe is two coaxial cables
whose end tips are exposed to plasma and a network analyzer. Moreover, boxcar technique is used toprovide a high time resolution for repetitive plasmas. [3] The boxcar method provides a high time
resolution but it requires at least several thousands times of repetitions for frequency sweeping,
therefore it is quite challenging to apply this method to PANTA since it is operated with near 1 Hz
repetition rate. Moreover, the electron density in PANTA is in the range of ͳͲଵ଻ െ ͳͲଵ଼ ݉ିଷ , it is noteasy to approach this frequency of several tens of GHz with a commercial equipment.
In this study, an advanced technique to approach PANTA plasma is introduced. Fourier cutoff
probe is developed for high time resolution measurements, [4] and it is even more powerful in repetitive
plasma: it requires only about ten times of repetition to enhance the quality of the signal. Fourier cutoff
probe requires three apparatus: a probe, a short impulse generator (usually SRS DG645 is used) and ahigh bandwidth oscilloscope. Regarding PANTA plasma parameters, a short impulse generator of <100 ps and an oscilloscope with bandwidth of > 50 GHz are required to approach high frequency
spectrum, which are not convenient as well. Therefore, a handmade short impulse generator and themethod to detect the signal are needed.
Several methods for short pulse generation are well known. For example, RC pulse generator
with passive components such as capacitors and resistors are used so that a charged capacitor releases
the energy in a short time. A more sophisticated method utilizes the fast reaction of a transistor. Since
faster reaction chips are being developed as the technology is improved, it is quite convenient utilizingthese chips. A method of glitch is one of those techniques. [5] In this method, two separate pulses witha small delays are merged through a logic gate, such as XOR gate. Finally, an impulse of the widthcompared to the delay time is generated. Since arbitrary short delay time can be generated easily, forexample transmission line length difference or repeated inversion provide delayed pulse, the pulse width
can be created as short. The quality of the pulse, such as rising time, depends only on the reaction timeof the logic gate. One example scheme is shown in Figure 1. A single pulse is merged with a delayed
pulse signal by a logic gate to create a short glitch signal. In this method, very short impulse < 100 ps
can be generated.

Figure 1. Schematic of Glitch generation [5]The detection of such a short pulse is not convenient because detection of 100 ps of pulse
signal requires an oscilloscope with bandwidth of much higher than 10 GHz. However, RF mixer
convert the high frequency signal to low frequency signal. The scheme is shown in Figure 2. The
original impulse signal and the transmitted impulse signal are down converted by mixers to be detectedby a low bandwidth oscilloscope. Most of the frequency dependent characteristics of a individual mixer
could be neglected during the analysis because the final transmission spectrum is acquired bycomparison of the input signal and the transmitted signal. The spectrum in the region of interest isconverted to a low frequency spectrum by the LO signal of the RF mixer.

Figure 2. (a) schematic of cutoff probe and mixer configuration, (b) plasma transmission spectrum (top) and spectra of ashort impulse and its down conversion.

The above methods will be expand the utilization of Fourier cutoff probe to a high frequency
spectrum with low cost. More detailed engineering circuit design for both the impulse generator andlow frequency conversion will be performed in the next joint research program.

References.
[1] Y. Nagashima et al., J. Phys. Soc. Jpn, 89, 093501 (2020).
[2] C. Moon et al., Sci. Reports, 11, 3720 (2021).
[3] J.-H. Kum et al., J. Kor. Phys. Soc. 51, 963 (2007).
[4] B.-K Na et al., J. Instrum. 7, C04022 (2012).
[5] M. Slimani and P. Matherat, Faible Tension Faible Consommation (2011).

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ࢆࠊࣇ࢛ࢵ࣮࢝ࣉࣛࣥࢡゎᯒࢆ⏝࠸࡚ホ౯ࡍࡿࡇ࡜࡟ඛ❧ࡕࠊ┦ᑐㄽⓗࢻࢵࣉ࣮ࣛࢩࣇࢺඹ㬆᮲௳ࢆ㏿ᗘ✵㛫ୖ࡛⪃ᐹࡋࠊࣂࣝࢡ㟁Ꮚ࠿ࡽ㧗㏿㟁Ꮚࡲ࡛ࡢᖜᗈ࠸࢚ࢿࣝࢠ࣮⠊ᅖ࡛ඹ㬆྾཰ࡍࡿࡇ࡜ࢆ♧ࡋࡓࠋECRH/ECCD modeling for QUEST by use of ray-tracing and
Fokker-Planck codes䚷
BERTELLI Nicola䚷 (Princeton University, U.S.A)
Extra-ordinary mode second (2nd ) harmonic heating scenario has been considered forthe 0.5 T ECHCD experiment, based on the ray tracing analysis. Figure 1 shows ray
trajectories at top view and transmitted power evolution along ray propagation withparallel refractive indexes at the antenna, N//a = 0.15, 0.25 and 0.35, in the relatively
high-density plasma. Bulk (of 0.5 keV at the center) and highly energetic (of 60 keV atthe center) electron components of few percentages for the bulk density are assumed.
These analyses were done in the 2021 collaboration. The rays cannot penetrate to thehigh-field side due to the cutoff, then they start to bend near the 2nd harmonic resonancelayer. The strong dumping would be expected in the case of N//a = 0.25 because the ray
trajectory is along the resonance layer. In addition, the dumping in the case of N//a = 0.15
is rather stronger than that in the case of N//a = 0.25 even when the ray is not along theresonance layer. To begin the Fokker-Planck analysis, the resonant condition in the
momentum space is considered.
The relativistic Doppler-shifted n-th harmonic resonance condition is expressed as anellipse equation in the momentum space (Ծ̰, Ծѱ) as follows,(1 ࡠ Լ )Ծ ࡠ 2Լ
2

2

̰

̰

ՖՎՋՍ
̰

Վ

2

Ծ̰ + 1 + Ծѱ ࡠՖՎՋՍ 2( ) = 0.
ՎHere, Ծ̰ and Ծѱ are the relativistic normalized momentums in parallel andperpendicular to the magnetic field. Լ̰ and fce are the refractive index in parallel to thefield and electron cyclotron frequency, respectively, which are functions of the major
radius R. The resonant ellipses are formed in the momentum space, depending on R.
Figure 2 shows the resonant ellipses for various Rs around the 2nd harmonic resonance222

layer of R = 0.64 m. The semi-circles with the radii Ծ̰ + Ծѱ of ƞ ࡠ 1 are also shownfor various energies (0.5, 10, 20 keV and so on) in the figure. The (Ծ̰, Ծѱ) of theintersections of the resonant ellipses and the semi-circles satisfy the resonant condition
for their energies. The resonant
ellipse for the major radiusaround R = 0.64 m has many
intersections
forvarioussemi-circles (wide range of theenergies) in the up-shifted
resonance condition of Ծ̰ > 0,
expecting significant absorption
by bulk and energetic electrons,
and efficient current drive. The
effects of electron cyclotron
resonance heating (ECRH) andcurrent drive (ECCD) are
expressed with a diffusion termof quasi-liner operator in the
momentum
spaceon
Fokker-Planck analysis. To understand strong dumping around the 2nd harmonicresonance layer of R = 0.64 m will be analyzed with the ray tracing and Fokker-Plank
codes under this momentum space consideration.
An analytical edge density fluctuation model was implemented in Petra-M [1, 2, 3] toinvestigate its impact on the hhfw propagation propagation [4]. 2D Petra-M simulations
with a cold plasma model clearly show a significant perturbation of the HHFW
propagation to the core plasma when large density fluctuations amplitudes (A > 30%).
Similar results in terms of HHFW propagation are found when a local hot plasma
approximation is employed. With the local hot plasma model, we can also make someobservations on the effects on the edge perturbations on the ion and electron absorption.
For amplitude of the edge density perturbations larger than 10% and for theplasma/wave parameters used in these simulations, the density fluctuations seem tohave a strong impact on both the electron and ion absorption. The deuterium/hydrogen
power deposition area tends to spread vertically and scatter into multiple sub-regions.
3D Petra-M simulations were performed assuming a 3D axisymmetric edge density
perturbation for a cold plasma model for three antenna phasing values: 30, 90, and 150
degrees. Overall reduction of the electric field amplitude in the core plasma for large A
was found. A strong modification of the vertical wave field mainly on the poloidal

cross-section as similarly found in the 2D runs for a cold plasma.
Finally, initial attempts to implement an edge 3D filament geometry along the magnetic
field line in the NSTX-U geometry used in Petra-M was also shown and discussed. Thissubject though is still in progress.
This subject was presented at a workshop entitled “Plasma start-up and sustainment in
spherical tokamak configuration by RF” which was held under a different international
RIAM collaboration framework.
[1] S. Shiraiwa and et al, EPJ Web of Conference 157, 03048 (2017).
[2] S. Shiraiwa and et al, 28th IAEA Int. Conf. on Fusion Energy (Virtual Event)(2021). [3] N. Bertelli and S. Shiraiwa, 29th IAEA Int. Conf. on Fusion Energy (2023).
[4] N. Bertelli, S. Shiraiwa, and M. Ono, Nucl. Fusion 62, 126046 (2022).

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໬ࡋࠊⰋዲ࡞ඹ᣺ჾືసࢆ☜ㄆࡋࡓࠋ
Report of international collaboration 2023NU-15 between RIAM
and IGVP in FY2023: High power mm wave transmission line
technology for advanced fusion devices
Mr. Dr. Carsten Lechte
Introduction: The MQIV diplexer developed at IGVP is a fast switch, power combiner, and mode
filter for megawatt power 170 GHz millimeter waves using a Fabry-Perot resonator in a compact box
design that is vacuum capable and can be directly interfaced with the 63.5 mm ITER ECRH
waveguides which are available at QST. The device has 2 input and 2 output ports, which areconnected as shown in Fig. 1. Our technical partners at TNO in the Netherlands have designed andbuilt a fast mechanical tuning control unit for the device that is also vacuum-compatible.

DN

DR
IN
Diplexer

Fig 1: Diplexer integration into the gyrotron test stand at QST. DN and DR are the dummy loads at
the non-resonant and the resonant channel, respectively, and IN is the input waveguide.
The highpower tests have demonstrated the switching capability of the device, but also highlighted
problems with arcing and stray radiation. Both are believed to have been fully addressed in 2023.
Since no high power tests at QST were possible in 2023, the work was assembly of the newcomponents and characterisation at low power.
Arc mitigation: The mirror surfaces were put into a “known-good” state with a galvanicallydeposited copper layer on the 4 surfaces of the main resonator, which were then re-machined back to
the design shape.
Furthermore, 4 new observation ports are now available for 3 new cameras to watch most mirror
surfaces for arcing.
Stray radiation mitigation: Six absorber plates covering the six internal surfaces of the device were
designed and are being fabricated at the IGVP workshop and at our collaborating partner IFKB at
Stuttgart University. The absorber consists of 8 mm aluminium plates with coutouts for all the mirrors,
waveguide ports, and observation ports that will be press-fit into the diplexer box (see Fig. 2). The
absorbing coating of aluminium and titanium oxide is applied by an atmorpheric plasma spraying
process to a thickness of approximately 100 wm. It has a high (>70%) single pass absorption at 170

GHz from all but the shallowest angles. Cooling is achieved by radiation and contact with the box
structure. Since only a fraction of the input power should end up as stray radiation, the absorbers
should be able to cool down between shots if a duty cycle of 1:20 of power on to power off is adhered
to. This duty cycle is also the maximum for the main mirrors.
Low power characterisation: Measurements were undertaken to certify the frequency dependent
switching behaviour of the device. Low power was injected into the input port, and the powerusually is measured at the output ports.
At high power use, the input and output powers are monitored via grating couplers on the matching
mirrors, which divert -40dB toward small diagnostic horn antennas. The polarisation of theseantennas was optimised. Because of the low coupling, the signal is very weak at low power.
It is expected that the introduction of the absorber decreases the stray radiation in the resonatorvolume, so that mostly the desired monitor signal hits the antennas. At nominal high power of 1
MW, the monitor signal would be 100 W. Qualitatively, the monitor signal has now a better signal
to noise ratio, but the ultimate test will be operation at high power in FY2024.

Fig. 2: Assembled absorber plates (dark) inserted into diplexer housing. Also visible are the 4 new
windows in the back.
The final low power characterisation was performed with two mirror positions, at the equilibrium of
the mounting hardware, and at the innermost position. The cleanest signal was obtained bymeasuring the monitor antenna signal, not the direct output signal. The plots are shown in Fig. 3.

Fig. 3: Top resonant (orange) and non-resonant (blue) power over frequency (a.u.). Bottom bothresonant outputs at both mirror positions.
The figure shows the expected resonance curve with at free spectral range of 278 MHz with good
switching contrast. The bottom figure shows the resonant output at two mirror positions, with aslight shift of the peaks due to the changed length of the resonator. The power changes withfrequency because of the way the monitor signal is extracted. The monitor antennas look at thediffreacted beam from a grating on the coupling mirrors (aluminium in Fig. 2), and the grating is
optimized for a single frequency.
In summary, the device was re-assembled and its operation was confirmed.

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Exploration of conditions for synthesizing heat-resistant materials using
supercritical technology
Department of Environmental and Energy, The University of Suwon
Assistant Prof. SEONG Gimyeong
1. Background and Purpose
Supercritical fluids, known for their innovative reaction environments, have attracted significant interest
and research due to their ability to promote unique chemical reactions. Combining them with a flow-type
reactor in a non-equilibrium reaction environment, characterized by high-density and highly diffusive
supercritical fluids, enables the development of high-performance nanomaterials. Particularly, composite
materials like tungsten alloys capable of withstanding extreme temperatures are gaining attention, especiallyin nuclear fusion and aerospace applications.
This collaborative research, supported by the advanced plasma physics capabilities of the ResearchInstitute for Applied Mechanics at Kyushu University, aims to advance the development of new highperformance nanomaterials. In this study, CeO2 was chosen as a model substance to understand the easily
occurring redox reactions at high temperatures. The impact of oxygen defects within the crystal structure on
the melting point variation was investigated using molecular dynamics simulations.
2. Methods
Molecular dynamics simulations were conducted using Fujitsu's SCIGRESS (v3.4) MD-ME. Initially, apristine CeO2 structure without oxygen defects in the 4+ oxidation state was generated. The system was thensubjected to high temperatures to induce amorphization, followed by a gradual cooling process to crystallize
the structure. Subsequently, a CeO2–x structure with oxygen defects in the 3+ oxidation state was created bygenerating 3+ ceria structures at concentrations of 23%, 50%, 75%, and fully reduced Ce2O3. The oxygen
was removed proportionally to the cationic charge during the crystallization process using the same method.
3. Results and Discussion
Molecular dynamics simulations (MD) provide
insights into the crystallization process of CeO2,
revealing the correlation between the degree of oxygen
defects (Ce3+) and the stability of CeO2 nanoparticles.
As depicted in Figure 1, initially, for CeO2 without
oxygen defects, the energy gradually decreases in theamorphous state at 6000 K, sharply dropping around3800 K, interpreted as the onset of crystallization.
While this temperature is approximately 40% higher
than the actual melting point (2673 K), it is sufficient Figure 1 The crystallization process of CeO2 withvarying degrees of oxidation and the morphologies
to understand the overall trend.
at 298K after crystallization: (yellow) Ce4+; (gray)
As oxygen defects increase, particles expand, with Ce3+; (red) O2–.
Ce3+ at 75% exhibiting a highly swollen morphology.
Additionally, an observed decrease in the melting point and a reduction in potential energy near the melting
point with increasing Ce3+ levels suggest a trend where phase transitions become easier. This implies that asthe ceria undergoes a 3+ oxidation state, the transition to a different state becomes more facile.
4. Summary and Conclusion
This study employed molecular dynamics (MD) to investigate the structural properties of nanoparticles.
The stability assessment based on oxygen vacancies not only provided crucial insights into the cerium
oxidation states but also offered a comprehensive understanding of nano-materials prone to oxygen defects.
The crystallization and calculated properties aligned well with reference data, confirming the effectivenessof the theoretical approach. The results of this study open the path for further investigations into materials,
including the introduction of various metal species, particularly in the development of heat-resistant alloymaterials.

国際化推進共同研究概要
No.21
23RE-1
タ イ ト ル： Investigation of III-nitride semiconductor surface properties
using coupled ab initio simulations and machine learningalgorithms.

研究代表者： KEMPISTY Pawel

所内世話人： 草場彰

研 究 概 要： 半導体表面の被覆構造の詳細な理解は、結晶成長過程の制御に不可欠です。本研究では、GaN 表面の Ga および H 混合被覆構造について、ベイズ
最適化を活用して第一原理計算データを効率的に収集し、Ising 模型の学習を行いました。その結果、460 万以上の候補構造の中から最安定構造の特定に成功しました。これは、従来の網羅的計算によるアプローチ
では達成できなかった成果です。

Investigation of III-nitride semiconductor surface properties using coupled ab initio simulations
and machine learning algorithms
Pawel KEMPISTY,
Institute of High Pressure Physics PAS, Sokolowska 29/37, 01-142 Warsaw, Poland
Introduction
The project primarily aimed to enhance the theoretical model for characterizing the surfaces of nitride
semiconductors. Understanding the surface phenomena is crucial for gaining better control over the
crystallization process, which, in turn, could address technological challenges in growing nitride
crystals, layers, structures, and devices. Dr. Kempisty's recent work at IWC PAN focused on dynamic
surface properties, incorporating first-principles phonon calculations into the thermodynamic
description of nitride semiconductor surface stability. Concurrently, Dr. Kusaba at RIAM has been
actively developing models using machine learning, particularly exploring large-scale periodic
structures through surface reconstruction informatics. By combining their computational expertise, bothresearchers synergized their efforts. The incorporation of machine learning models enabled them tosurpass typical approximations employed in ab initio calculations.
MethodMuch of the research involved a thermodynamic analysis based on data derived from first-principles
calculations. The RSDFT and SIESTA codes, utilizing Density Functional Theory (DFT) within the
General Gradient Approximation, was employed to calculate the energies of the systems and phononband structures. We incorporated contributions from the vibrational motion of the crystal and its
surface, obtained through phonon calculations. Subsequently, using thermodynamic relations derived
from phonon spectra, various thermal properties such as constant volume heat capacity, vibrational
entropy, and Helmholtz free energy were determined.
Results
The study employs DFT calculations to systematically investigate the adsorption of gallium atoms on
GaN polar surfaces. The analysis begins with the clean surface and progresses to the metallic
multilayer. Changes in the chemical potential of gallium adatoms were determined as a function oftemperature and surface coverage, as illustrated in Fig. 1. These findings contribute to a more accurate
thermodynamic description of the surface state under conditions typical for Molecular Beam Epitaxy(MBE), offering an interpretation of the observed growth window.
&ŝŐƵƌĞϭ͘dĞŵƉĞƌĂƚƵƌĞĚĞƉĞŶĚĞŶĐŝĞƐŽĨƚŚĞĐŚĞŵŝĐĂůƉŽƚĞŶƚŝĂůŽĨ'ĂĂĚƐŽƌďĂƚĞŽŶƚŚĞ'ĂE;ϬϬϬϭͿƐƵƌĨĂĐĞ͘&ŝŐƵƌĞϮ͘ĚƐŽƌƉƚŝŽŶĨƌĞĞĞŶĞƌŐǇŽĨƚŚĞ'ĞĂƚŽŵŽŶƚŚĞ'ĂE;ϬϬϬϭͿƐƵƌĨĂĐĞǁŝƚŚĚŝĨĨĞƌĞŶƚƐƵƌĨĂĐĞŵĞƚĂůůĂǇĞƌƐĂƚŚŝŐŚƚĞŵƉĞƌĂƚƵƌĞ͘Furthermore, we explored the role of gallium and indium adlayers in the context of InGaN crystal
growth. The indium surfactant layer exhibits better regularity and a closer lattice match to GaN, while
the gallium layer appears denser and more amorphous in nature. Additionally, we investigated theadsorption free energy difference of germanium (Ge) and silicon (Si) atoms on Ga and In layers as
a function of temperature. Our findings indicate that the free energy of Ge adatoms on a Ga-covered
GaN(0001) surface can exceed the chemical potential of bulk Ge (see Fig. 2), potentially leading tosegregation of Ge crystallites on the surface. These results agree well with observations made during
the growth of InGaN and GaN by MBE.
The next stage of the research involved considering
mixed surface reconstructions with the presence ofgallium and hydrogen. The analysis was performed ona slab model with a size of 6×6 surface cells.
Calculating the energy of all node occupancy
combinations explicitly through ab initio methods was
not feasible. Therefore, we have identified surface
structures by the DFT calculations combined withmachine learning technique Bayesian optimization. We
successfully identified the most stable structure among
4,686,825 candidate structures with various adsorbate
configurations by incorporating a data-driven Isingmodel and augmenting the well-known electron&ŝŐƵƌĞϯ͘ŽŵƉĂƌŝƐŽŶŽĨŵŝǆŝŶŐĞŶƚŚĂůƉŝĞƐŽĨŐĂůůŝƵŵ counting rule. Our interpretable trained model revealedĂŶĚŚǇĚƌŽŐĞŶĐŽǀĞƌĂŐĞĞƐƚŝŵĂƚĞĚďǇ/ƐŝŶŐŵŽĚĞůĂŶĚ a stabilization mechanism, enabling the evaluation ofĐĂůĐƵůĂƚĞĚďǇ&d͘
the entire set of candidates.
Conclusion
The project demonstrated the effectiveness of integrating density functional theory (DFT) calculations
with machine learning, resulting in a powerful tool for predicting material properties. We investigated
the thermodynamic properties of GaN surfaces under gallium-rich conditions and mixed galliumhydrogen coverages. The proposed approach utilized Bayesian optimization to explore the parameter
space and identify surface site occupations. Additionally, the Ising model was employed to predict themost promising cases, streamlining the research process for subsequent DFT calculations.
Measurable effects of participation in the programme
As part of the project, Dr. Kempisty undertook a short research visit at RIAM Kyushu University from
November 12 to December 2, 2023. During this period, he actively participated in the14th International
Conference on Nitride Semiconductors (ICNS-14) held in Fukuoka from November 12 to 17, 2023.
A poster presentation entitled “Ab initio thermodynamic study of the metallic surface wetting layer
during MBE (In)GaN growth and its consequences for dopants incorporation” was presented by
P. Kempisty, K. Kawka, A. Kusaba, and Y. Kangawa. A significant portion of the project's results has
been published in an article entitled “Polar GaN Surfaces under Gallium Rich Conditions: Revised
Thermodynamic Insights from Ab Initio Calculations” by P. Kempisty, K. Kawka, A. Kusaba,
Y. Kangawa in Materials, 16(17), 5982, 2023 (doi: https://doi.org/10.3390/ma16175982). Additionally,another manuscript entitled “Augmentation of the Electron Counting Rule with Ising Model” by
K. Kawka, P. Kempisty, K. Sakowski, S. Krukowski, M. Bockowski, D. Bowler, and A. Kusaba has
been submitted to the Journal of Applied Physics. It is based on the results previously presented by
Dr. Kusaba in an oral presentation entitled “Ising model-based analysis of the GaN(0001) surface
reconstructed structures sampled from Bayesian optimization” at the 20th International Conference on
Crystal Growth and Epitaxy (ICCGE-20) held in Naples from July 30 to August 4, 2023.

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Report for 2023 RIAM International Joint Research Project[23RE-3]AI-based Interactive Integrated Design, a novel method for Floating
Offshore Wind Turbines Design and Optimization
Zhiqiang Hu
Marine, Offshore and Subsea Technology, School of Engineering, Newcastle University, UK

This collaborative research between RIAM Kyushu University and Marine Offshore andSubsea Technology group, Newcastle University was planned in the year 2022, aiming topropose an AI-based interactive Integrated Design and Optimization method for thedevelopment of floating offshore wind turbines. This project continued in year 2023 by thesame research groups.
This method was initially proposed based on the novel concept SADA, which was brought out
by Zhiqiang Hu and Peng Chen on a journal Ocean Engineering publication in year 2020. The
fundamentals of SADA were introduced on RIAM symposium in year 2021 and an engineering
practice case-of-study was also presented on RIAM symposium in year 2022.
From year 2023, Zhiqiang Hu led his research team at Newcastle University, devoting into theresearch developing SADA and integrating the AI technology in a further step with monitoringand maintenance of FOWT, to solve the challenges for lowing O&M cost and achieve digital
twins for offshore wind industry. During the year of 2023, the collaborative research outcomesare listed as below.
1) The 2nd International Symposium on Marine Renewable Energy System Dynamics washeld at RIAM Kyushu University in Jan 2024. Zhiqiang Hu made a presentation on the
topic of ‘Offshore Wind and Artificial Intelligence: Steps to real-time monitoring andDigital Twins for offshore wind turbines’. In this presentation, Zhiqiang firstly presented astrategy to realize digital twin system for monitoring and prediction of offshore windturbines, via the AI technology, SADA method and Inverse SADA method. This
presentation attracted many attentions from the audience and a fruitful discussion withother attendants was made during the symposium.
2) During year 2023, the collaborative research has been carried out to extend the AI-basedInteractive Integrated Design method into the digital twins’ application field. During thisinvestigation, the proposed method was updated to digital twin level. With the SADA
concept which is an AI-based method, the Inverse SADA method is currently underinvestigation. When the updated Inverse SADA method is completed, it can work together
with SADA to realize the digital twin for offshore wind turbines. The first engineering
practice case will be put on the monitoring of scour development of fixed-bottom offshore
foundation.
3) Based on the research in year 2023, a collaborative conference paper entitled ‘Time-domain

Integrated Analysis of Multi-segment Mooring System for Floating Offshore Wind
Turbines’ was written, and the abstract was submitted to EAWE Conference 2024.
Unfortunately, due to the first author’s personal healthy circumstance, the full paper was
not submitted successfully. But the research team has a plan to resubmit the paper to someother conference in year 2024.
4) Another collaboration outcome is PhD exchanging between Kyushu University and
Newcastle University. Mr Chaozhi Qiu, a PhD in RIAM, started an academic visit at
Newcastle University on Nov 2023 and would stay at NU for four months. During his visit
at Newcastle University, he followed lectures, attended academic events, and discussedwith Zhiqiang Hu, all of which benefiting his PhD research on multi-rotor FOWT.
In year 2024, the collaborative research between Newcastle University and Kyushu University
will be conducted to a further step. The focus will be put on the digital twins system application
on O&M for offshore wind. The development of Inverse SADA method is the key challenge,
but it is promising to benefit offshore wind industry. In addition, the symposium at RIAM will
also be upgraded to a conference. It is expected to make further improvement of thecollaborative project within year 2024 and present the research outcomes in the new conference.

ᅜ㝿໬᥎㐍ඹྠ◊✲ᴫせ㻌
1R24

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ࡓ᪂ࡋ࠸ᘬᙇಀ␃⥘ࣔࢹࣝ࡜ᚑ᮶ࡢ◳┤ಀ␃⥘ࢆ⏝࠸ࡓィ⟬⤖ᯝࢆࠊᇶ♏
ࡢືⓗᛂ⟅࡜ಀ␃⥘ࡢᙇຊ࡟ࡘ࠸࡚ẚ㍑ࡋࡓࠋᥦ᱌ࡉࢀࡓᘬᙇಀ␃⥘ࣔࢹࣝࡣࠊᾋయᘧἼຊⓎ㟁⿦⨨ࡢୖୗ㐠ື࠾ࡼࡧ๓ᚋ㐠ືࠊ୕ᮏࡢᙇຊᆺಀ␃
⥘ࡢࣇ࢙࢔࣮ࣜࢻ࡟࠿࠿ࡿᙇຊࡢண

⢭ᗘࢆྥୖࡉࡏࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ

ᅜ㝿໬᥎㐍ඹྠ◊✲ሗ࿌᭩No.
23RE-4䝍 䜲 䝖 䝹䠖Mooring design and coupled dynamic analysis of wave energy converter and its mooring
system under typical sea states◊✲௦⾲⪅䠖XIANG, Gongᡤෆୡヰே䠖

๽㻌 ┆⁄Introduction
In the past decades, an increasing number of floating marine systems have been designed, produced and operated in
the sea to adhere to the demand of exploring the ocean energy resources deeper and further away from the land [1-5]. The
typical floating systems for harvesting ocean resources include traditional oil and gas platforms [2,6,7], as well as
renewable energy devices, such as wind turbines, tidal/current turbines, wave energy converters and their associatedoperational systems [4,8,9,10].
There are three main types of mooring design for floating wave energy converters: the catenary mooring system,semi-taut mooring system, and taut mooring system. Most of the mooring systems under operations are catenary or semitaut. Several catenary mooring configurations were proposed that could be accomplished with single or multi-connections[1]. Astariz and Iglesias [11] found the most appropriate mooring was CALM (catenary anchor leg mooring), which has
the advantages of easy installation, lower cost, and fewer effects of corrosion. However, the use of catenaries may sufferfrom wear and fatigue damage and affect the structure safety due to vortex-induced vibration. Gao and Moan [12] also
pointed out that a catenary line system usually consisting of chain links relies on the weight of links or clump weights toprovide horizontal restoring force. If no clump weight is used, a long mooring line of chain links must be considered toobtain adequate flexibility. Furthermore, catenary line systems will bring large, vertically downward loads to the floating
structures. This could limit the allowable deck loads for floating wave energy converters. Therefore, this concept might
not be suitable in shallow waters.
As shown in Fig.1, with synthetic fibers becoming very promising mooring materials, the taut mooring system canalso be treated as a good alternative to a mooring system for floating wave energy converters. New materials, such as AI
foam, might also be used for the composition of the mooring lines after enhancement of the structural strength. The diametersizes of those synthetic fiber ropes used for commercial purposes vary within the range of 16 mm to 240 mm [13] and are
typically made of nylon (polyamide), polyester (polyethylene terephthalate), aramid (para-aramid), or HMPE (highmodulus polyethylene). Synthetic fiber ropes are significantly lighter than other materials and, therefore, can be used in
the water column of a taut mooring system. Casaubieilh [14] found that the new generation of mooring system, tautconfiguration using tether mooring lines, can significantly reduce the loads on mooring lines, floating structure, and anchors,and it can also reduce the device excursions when compared to the conventional catenary moorings. The elastic propertiesof fiber ropes are also of interest to damp mooring loads, and they avoid snap loads [13].

Fig. 1 Synthetic fibers applied into the taut mooring system of floating device
In this study, a time domain modelling method is proposed to study the dynamics of a point absorber-type wave
energy converter moored by the synthetic fiber mooring lines under regular waves. The simulations of motion
response and the tension force on the mooring lines at the fairlead of the foundation with a three-point (T3) tautmooring system under regular waves are studied using traditional stiff and proposed tensile mooring line model.
The dynamics of a spar-type floating wave energy converter foundation moored by synthetic fiber mooring linesof different lengths and pretensions have been simulated. Comparative performance analysis of two-point (T2)and three-point (T3) taut mooring systems are also conducted.
Methodology
Dynamics of a tensile mooring line
The mooring line is generally treated as a slender rod when studying its dynamics. In a 3-D Cartesian coordinate
system, the rod is expressed as a function of time t and the arc length s along the rod, namely a position vector,r(s, t) as shown in Fig.2. In Fig.2, the unit vectors in tangential, normal and binormal directions are expressedby t, n and b, respectively. The rod tensile is usually assumed to allow for large axial elongation, that is, theoriginal arc length is s while the deformed arc length is V as shown in Fig.2.

Fig.2.The rod in original and deformed stateFor a slender rod, the equations of motion are developed based on general conservation of linear momentum
and moment of momentum and can be expressed as, c  rc u F  m 0
M
Fc  q(1)

U r( s, t )(2)

Where, q is the external load acting on the rod per unit length, U and m is the mass and the external moment perunit length, respectively. The symbol of prime indicates the space derivative with respect to s, while the symbol~of superposed dot represents time derivative. Correspondingly, F is the total force acting at a point while M isthe total moment acting at the centerline of the rod.
~

Based on the Bernoulli-Euler theory, the related total moment M can be expressed by rc u ( Brcc)  Hrc
M(3)

By merging Eqs.2~3, the equations of motion of slender rod are represented by

rc u ( Brcc)c  H crc  Hrcc  rc u F  m 0(4)

For a tensile mooring line such as the studied synthetic fiber rope here, it is regarded as a long slender tensile
rod with negligible moments and shear forces which can also experience large elongations. As a result, thebending stiffness B, the torsional stiffness H, and the shear deformations can be all neglected in the above
equations. Therefore, the only remaining internal force is caused by the cable tension tangential to the local
direction. Finally, the governing equation is simplified as(Orc)c  q

U r

(5)

where O is the Lagrange multiplier. The total external forces applied on a submerged slender rod per unit lengthareq q F  K  q I  q D  q B  qG

(6)

where the first three terms represent the hydrodynamic forces including Froude-Krylov force, ‫ࡷିࡲܙ‬, added massforce, ‫ ࡵܙ‬, and drag force, ‫ ;ࡰܙ‬Here ‫ ࡰܙ‬stands for the damp forces which is dependent on the velocities of themooring line. It is noted that the fourth term, ‫ ࡮ܙ‬is hydrostatic force; the last term, ‫ ࡳܙ‬is the Gravity force. The

total force ‫ ܙ‬can be also expressed in detail asq

1
2

U A I  CMn N  CMt T a  U DCDn N v  r N v  r
U A  Ut At ge y1
 U DCDt T v  r T v  r 
2
1䞉

(7)

where T=r’Tr’ and N=I-T, ‫୑ܥ‬୬ , ‫ ୲୑ܥ‬, ‫ܥ‬ୈ୬ , and ‫ܥ‬ୈ୲ are added mass coefficients in normal and tangential
direction, drag coefficients in normal and tangential direction, respectively while ‫ܣ‬௧ , A and D denote the areaof geometric cross section of the rod, the area of outer cross section of the rod and the diameter of the outercross section of the rod. In the fluid domain, ‫ ܞ‬and ‫ ܉‬represent velocity and acceleration of the ambient fluid.
where the subscripts f, i and t denote the sea water, the fluid inside the tube and the tube itself.
At the same time, the dynamics of n tensile mooring line can be calculated in rectangular Cartesian coordinates.
The governing equation and constraint equation for a tensile mooring line can be also expressed as.

w (T t )
q
ws

U r

(8)

where T is the local tension, s is original length between one end to a waypoint along the rod, ܵҧ is deformed
length, t is the unit vector tangential to the deformed length expressed by ‫= ܜ‬૒‫ܚ‬. The relation between deformed૒௦

length and original length can be described as:

ds(1  H )ds

(9)

H

T
EA

(10)

where EA is the axial stiffness of the slender rod.
Therefore,

rc

wr
ws

wr
(1  H ) t (1  H )
ws

(11)

rc
t
1 H

(12)

Substitute Eq. (12) into Eq.(8),Trc)c  q
(
1 H

U r

By comparing Eq.(13) and Eq.(5), the Lagrange multiplier O is defined as

(13)

T
1 H

O

(14)

Substitute Eq.(14) into Eq.(10),

H

O

O

T
EA

EA

EA-O

H

1-

O

H
1-H

EA

(15)

O
EA

(16)

Additionally, r must satisfy a stretching constrain equation:rc  rc (1  H ) 2(17)

rc  rc(1  H ) 2 1(18)

By substituting Eq.(15) into Eq.(17),Finite Element Simulation Approach
A global-coordinate-based nonlinear finite element method is used for the simplicity of numerical computation.
The Galerkin's method was used to discretize the dynamic equations in space, resulting into a set of nonlinear
2nd-order ordinary differential equations in the time domain. Finally, a Newmark-ȕmethod was employed fortime-domain integration of the discretized equations. For each element, the mooring line dynamic equation at
the Kth time step becomes:

J ikm M njmukj  Eikm Omukn

Pim qmn  fin(19)

The coefficients in Eq.(19) are obtained through integration over the length of the element :

Eikm

1 1
aic([ )akc ([ ) pm ([ )d [
L³0

J ikm

L ³ ai ([ )ak ([ ) pm ([ )d [

Pim

1

0

1

L ³ ai ([ ) pm ([ )d [Similarly, the constrain equation is discretized as

0

(20)

Eikmuinukn  Kiklm (2H l  H l2 )uinukn  W m

0

(21)

The coefficients in Eq.(21) are obtained through integration over the length of the element :

Wm
Kiklm

1

L ³ pm ([ )d [0

1 1
aic([ )akc ([ ) pl (m) pm ([ )d [
L ³0

(22)

where, a(s) is the Hermite cubic shape function, and p(s) is the quadratic shape function, [ is a nondimensional
position expressed as [=s/L, L is the original length of the element.
During simulations, the tensile mooring line is discretized into 100 line elements each of which should be solved
as per the relation expressions in Eq.(19) and (21) using Newmark-ȕ method. The boundary conditions for thefinite element simulations of the mooring lines include that the first element is attached to the fairlead of thefloating point absorber while the 100th element gets connected to the seabed. Therefore, the first element willtransfer the pretension force to the point absorber and in turn will move following the motion of the point
absorber. For the last element, it is treated to be fixed at the seabed. To begin with the dynamic analysis of themooring lines, static analysis is conducted to achieve the static equilibrium position, namely, the initial condition
for mooring dynamic analysis. The time step is set as 0.05s to achieve the independence while the wholesimulation time lasts 30 wave excitation time cycles. After the simulation is finished, totally 15 unknowns
relating to u and Ȝcan be obtained.
Coupling dynamics of floating point absorber with taut mooring system
To accomplish the coupling dynamic analysis of a floating point absorber foundation with taut mooring system
as shown in Fig.1, the equations of motion for the foundation shown in Eqs.(23)-(24) and mooring lines shownin Eq.(5) and Eq.(18) are solved simultaneously using Newmark-ȕmethod. The six degree-of-freedom (6-DOF)
nonlinear motion equations of a rigid body were derived as follows:¨ u rg  mTt Ȧ u Ȧ u rg
m [  mTt Ȧ¨  Ȧ u IȦ  mrg u §¨ T [ ·¸ M
IȦ
©
¹

F

(23)

(24)

The translational motion and the rotational motion of a rigid body are expressed in the spaced-fixed coordinate
system OXYZ with origin at O and the body-fixed coordinate system oxyz with origin at o, respectively. Where,ߦ is the translational displacement of the body at point o in OXYZ, ૑ is the rotational velocity in OXYZ, rg=(xg,yg, zg)t, is the point vector of mass center of the body in OXYZ, I is the moment of inertia of the body withrespect to point o in OXYZ, T is a transfer matrix between the oxyz and OXYZ ; The total external forces ۴෨acting on the body in OXYZ and the total external moments with respect to o, M can be unified by F as shown
inFª F º
« »
¬M ¼

(25)

Correspondingly, the 6 DOF motion equations for the floating foundation can be derived as¨>M b  M a @ X t  CX t

FeFH  FMorison  FM  FHtt°­mT (Ȧ u (Ȧ u rg ))  mT (Į q u rg ) °½®
¾°¯Ȧ u I oȦ  I oĮ q
°¿

(26)

(27)

Where ‫ۻ‬௕ and ‫ۻ‬௔ are the mass and added mass of the foundation respectively, C is the hydrostatic stiffness
matrix, ۴ு represent nonlinear hydrostatic restoring forces, ۴ெ௢௥௜௦௢௡ denotes Morison forces, and ۴ெ refers tomooring line forces. The generalized form of Eq.(26) can be expressed as¨

A X t  CX t

F t  FM t(28)

where, ۴ெ (‫ )ݐ‬denote mooring line forces and ۴(‫ )ݐ‬denote the rest of forces. At the Kth time step, the motion
equation can be re-written in the following form¨

AK X tK

C K X KF K  FM K

(29)

Correspondingly, a numerical modelling code, which is composed of a main program and a subroutine programis developed. The subroutine program namely a mooring dynamics program developed accordingly is called by
the main program at each time step to calculate the motions of the foundation. It should be noted that the valuesof fin in Eq.(19) are transmitted to ۴ெ (௄) in Eq.(29) through the hinged boundary conditions.
Results
The floating point absorber foundation coupled with a T3 mooring system is simulated according to the
proposed methodology. Fig.4 shows the comparison of surge and heave motions using the traditional stiff
mooring line model and tensile mooring line model proposed in this paper respectively. Through thecomparisons, it is found that the surge and heave motions of the foundation using the traditional stiff mooringline model will underestimate the range of the motion responses of the foundation. In a real situation, theelongation of the mooring line cannot be ignored since the elongation of the mooring line will make the whole
floating point absorber system less stiff and more elastic. Fig.3 shows the comparison of corresponding tension

forces at the fairlead of three mooring lines. It can be found that tensions at Line 1 and Line 2 calculated by stiff
mooring line model are much larger than stiff mooring line model. This is because the surge motion of thefoundation is larger in the tensile mooring line model than in stiff mooring line mode; much larger tension forcesat the fairlead of mooring lines 1 and 2, whose configurations are more aligned with surge direction are required
to limit the surge responses of the foundation. Also, it is noted that the mooring line is made of Polyester, which,in reality, can hardly be compressed. But in Fig.3, it is observed that if using the traditional mooring line model,
the calculated minimum mooring tension force of line 3 is much smaller than zero, which means the mooringline can be compressed a lot during wave-induced dynamic motions. By ignoring the bending stiffness of themooring line, the proposed tensile mooring line model can overcome the inaccuracy of predicting thecompressions of the elastic mooring line, such as polyester, using the traditional stiff mooring line model.
(c)

(d)

Line 1
60

Line 260
Extensible Mooring Line

Extensible Mooring Line

Inextensible Mooring Line
Inextensible Mooring Line

50

40

40

30

30

Tension(KN)

Tension(KN)

50

20

20

10

10

0

0
90

100

110

120

130

140

150

160

90

100

110

120

Time(s)

130

140

150

160

Time(s)Line 3(e)70
Extensible Mooring Line
Inextensible Mooring Line

60

50

40

Tension(KN)

30

20

10

0

-10

-20
90

100

110

120

130

140

150

160

Time(s)Fig.3. Comparison of time series of surge and heave motion time series, mooring tension at the fairlead using
traditional stiff line model and proposed tensile mooring line model,(a) Surge (b) Heave (c) Line 1 (d)Line 2(e) Line 3
References
1.

Fitzgerald, J., and Lars, B., 2008. Including Moorings in the Assessment of a Generic Offshore Wave Energy Converter: A
Frequency Domain Approach. Marine Structures 21 (1): 23–46. doi:10.1016/j.marstruc.2007.09.004.

2.

Kim, J.D., Jiang, B.S., 2016. Application of multi-objective optimization for TLP considering hull-form and tendon system. Ocean
Engineering, 116: 142-156.

3.

Xiang, X.B., Yu, C.Y., Zhang, Q., 2017. On intelligent risk analysis and critical decision of underwater robotic vehicles. Ocean
Engineering, 140: 453-465.

4.

Sergiienko, N.Y., Rafiee, A., Cazzolato, B.S., Ding, B., and Arjomandi, M. 2018. A feasibility study of the three-tether
axisymmetric wave energy converter. Ocean Engineering, 150:221-233

5.

Wang, Z., Yang, S.L., Xiang, X.B., Vasilijevic´, A., Miškovic´, N, Nad, Ðula., 2021. Cloud-based mission control of USV fleet:architecture, implementation and experiments. Control Engineering Practice, 106: 104657

6.

Kang, H.S., Kim, M.H., Aramanadka, S.B., 2020. Numerical Analysis on Mathieu Instability of a Top-Tensioned Riser in a DryTree Semisubmersible. Journal of Offshore Mechanics and Arctic Engineering 142 (2).

7.

Subbulakshmiab, A., Sundaravadivelub, R. 2021. Effects of damping plate position on heave and pitch responses of spar platform
with single and double damping plates under regular waves. Ocean Engineering, 224:108719.

8.

Liu, Y., Yoshida, S., Hu, C., Sueyoshi, M., Sun, L., Gao, J., Cong, P., He, G., 2018. A reliable open-source package for
performance evaluation of floating renewable energy systems in coastal and offshore regions. Energy Conversion and Management
174:516-536

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Zhang, Q., Zhang, J.L., Chemori, A., Xiang, X.B., 2018. Virtual Submerged Floating Operational System for Robotic Manipulation.
Complexity, 1–18. DOI: 10.1155/2018/9528313.

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Bachynskia E., Thysb M., Delhayec. V., 2019. Dynamic response of a monopile wind turbine in waves: Experimental uncertainty
analysis for validation of numerical tools. Applied Ocean Research, 89:96-114

11.

Astariz, S., and G. Iglesias., 2015. The Economics of Wave Energy: A Review. Renewable and Sustainable Energy Reviews 45:
397–408.

12.

Gao, Z., and Moan, T., 2009. Mooring system analysis of multiple wave energy converters in a farm configuration. Proceedingsof the 8th European Wave and Tidal Energy Conference, Uppsala, Sweden.

13.

Harnois, V. Analysis of Highly Dynamic Mooring Systems: Peak Mooring Loads in Realistic Sea Conditions. Ph.D. Thesis,
University of Exeter, Exeter, UK, 2014.

14.

Casaubieilh, P., Thiebaut, F., Sheng, W., Retzler, C., Shaw, M., and Letertre, Y., 2015. “Performance Improvements of Mooring
Systems for Wave Energy Converters.” Renewable Energies Offshore – Guedes Soares (Ed.) ©, no. Wang 2013: 897–903.

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ࢫࢺࣛࣜ࢔ࡢ  ࡘࡢ₯ᅾⓗ࡞ሙᡤ࡛ἼຊⓎ㟁᪋タࡢ᭱㐺࡞タ⨨ሙᡤࢆศᯒ
ࡋࡓࠋ⏕ᡂ㟁ຊࡢᮇᚅ್ࡣከ㔜ᩓ஘⌮ㄽཬ䜃ከ᪉ྥ୙つ๎Ἴ⌮ㄽ࡟ᇶ࡙࠸
࡚ᩘ್ⓗ࡟ண ࡉࢀࠊ᭱Ⰻࡢሙᡤࡣ௚ࡢ  ࡘࡢሙᡤࡼࡾࡶ⣙  ಸ࠿ࡽ ಸ࡯࡝㧗࠸ᛶ⬟ࢆ♧ࡋࡓࠋIntroduction
Ocean waves can supply a significant source of clean and renewable energy due to the vast ocean area on theearth [1]. These converters work collectively to generate electricity from the kinetic energy of ocean waves.
Wave farms are situated either near the coast or offshore and typically comprise various devices, including
floating buoys, oscillating water columns, or other wave energy converters, all interconnected to the electricalgrid.
In this study, we aim to analyse the best location for wave farm deployment in a set of candidate sites. Figure
1 shows several potential sea sites in south-east Australia [2] to deploy wave energy devices, in which “CB”
stands for Cape Bridgewater, “WP” stands for Wilson’s Promontory, and “LE” stands for Lakes Entrance. We
are going to predict the power expectation generated by a 2ൈ3 small-scale wave farm to be deployed at thesethree sites, based on the multiple-scattering wave interaction theory.

Figure 1. Potential sea sites in south-east Australia [2].
Multiple-scattering theory for wave energy arrays
Let us consider a train of regular incident waves that propagates to the positive x-direction with a small amplitude A, a heading angle E measured from the positive x-axis, and a wave number k, in water of a finite depthh. The ambient wave potential incident to body j can be written as୧௚஺ ୡ୭ୱ୦ ௞൫௭ೕ ା௛൯ ୧௞ൣ൫௫ೕ ା௫ҧ ೕ ൯ ୡ୭ୱ ఉା൫௬ೕ ା௬തೕ ൯ ୱ୧୬ ఉ൧݁,ୡ୭ୱ୦ ௞௛߶௝஺ ൫‫ݔ‬௝ ǡ ‫ݕ‬௝ ǡ ‫ݖ‬௝ ൯ ൌ െ ఠ(1)where ൫‫ݔ‬ҧ௝ ǡ ‫ݕ‬ത௝ ǡ Ͳ൯ refers to the origin of the local coordinate system of body j in terms of the global Cartesian
coordinates and ൫‫ݔ‬௝ ǡ ‫ݕ‬௝ ǡ ‫ݖ‬௝ ൯ refers to an arbitrary spatial point in terms of the local Cartesian coordinates. By
converting the local Cartesian coordinates to the polar coordinates ൫‫ݎ‬௝ ǡ ߠ௝ ǡ ‫ݖ‬௝ ൯, Eq. (1) can be expanded as asummation of partial cylindrical waves incident to the body j in the form of matrices்߶௝஺ ൫‫ݔ‬௝ ǡ ‫ݕ‬௝ ǡ ‫ݖ‬௝ ൯ ൌ ൛ܽ௝ூ ൟ ൛߰௝ூ ൟ,(2)where ൛ܽ௝ூ ൟ is a scalar vector of expansion coefficients, and ൛߰௝ூ ൟ is a scalar vector of the basis function that is
also named as the incident partial wave component.
In arrays of floating bodies, each individual body experiences not only the ambient incident plane wave but
also the outgoing waves that are scattered from all the other neighboring bodies in the arrays. Based on Graf’s
addition theorem, the scattered waves from body i can be expressed as incident waves to body j as the following equation்߶௜ௌ ሺ‫ݎ‬௜ ǡ ߠ௜ ǡ ‫ݖ‬௜ ሻ ൌ ൛‫ܣ‬௜ௌ ൟ ൣܶ௜௝ ൧൛߰௝ூ ൟ,(3)

where ൛‫ܣ‬௜ௌ ൟ is a scalar vector of the scattering coefficients, and the T-transfer matrix yields
௠௤ൣܶ௜௝ ൧௡௡ ൌ ቊ‫ܪ‬௠ି௤ ൫݇‫ܮ‬௜௝ ൯݁ ୧ఈ೔ೕሺ௠ି௤ሻ ǡ ݊ ൌ Ͳǡ‫ܭ‬௠ି௤ ൫݇௡ ‫ܮ‬௜௝ ൯݁ ୧ఈ೔ೕሺ௠ି௤ሻ ሺെͳሻ௤ ǡ ݊ ൒ ͳǤ

(4)Using a so-called diffraction transfer matrix ൣ‫ܦ‬௝ ൧ as the form that is defined in Liu et al. [3] based on the hybrid dipole-source formulation, the scattered wave from body j and all the incident waves to the same bodycan be connected based on the following relation்ேಳ൛‫ܣ‬௝ௌ ൟ ൌ ൣ‫ܦ‬௝ ൧ ቀ൛ܽ௝ூ ൟ ൅ σ௜ୀଵǡ௜ஷ௝ൣܶ௜௝ ൧ ൛‫ܣ‬௜ௌ ൟቁ ǡ ሺ݆ ൌ ͳǡʹǡ ǥ ܰ஻ ሻ,(5)where ܰ஻ is the number of wave energy converters. From Eq. (5), scattering coefficients and the wave potentials can be solved numerically. Wave excitation forces, etc., can be calculated via pressure integration overeach body using matrix operations.
Wave farm performance in multi-directional irregular waves
According to Evans [4] and Falnes [5], in regular waves, the maximum absorbed power of a wave farm can beevaluated in terms of the wave excitation force and the radiation damping matrices:ଵேಳܲ௝ ሺ߱ǡ ߚሻ൯௠௔௫ ൌ ଼ ሼ‫ ܨ‬ா ሽ‫ כ‬ሾ‫ܤ‬௥௔ௗ ሿିଵ ሼ‫ ܨ‬ா ሽ,
൫σ௜ୀଵ

(6)

where ܲ௝ ሺ߱ǡ ߚሻ is the maximum absorbed power of each device, and the superscript * denotes complex conjugate transpose. In real seas, the overall generation power of the wave farm can be evaluated as
గ

ஶ

ே

ಳ
ܲ ൌ ‫ି׬‬గ ‫׬‬଴ ൫σ௜ୀଵܲ௝ ሺ߱ǡ ߚሻ൯௠௔௫ ܵሺ߱ሻ‫ܩ‬ሺ߱ǡ ߚሻ߱ߚ,(7)

where ܵሺ߱ሻ is the localised wave frequency spectrum and ‫ܩ‬ሺ߱ǡ ߚሻ is the directional spectrum (also named as
directional spreading function). In case of JONSWAP spectra, the frequency spectrum reads [6]S (Z )

5
4

E J H s2Tp4 f 5 exp[ (Tp f )4 ]Jexp[  ( f / f p 1)2 /2V 2 ],(8)where Hs is the significant wave height, Tp is the peak spectral period, fp is the peak spectral period, J is thepeak shape parameter of a given irregular sea state and V is a scaling factor. The directional spectrum yields
ఉିఉ೘
ቁ,
ଶ

‫ܩ‬ሺ߱ǡ ߚሻ ൌ ‫ܥ‬ሺ݊ሻ  ଶ௡ ቀ

(9)where n = Hs/2㻌and㻌ߚ௠ 㻌is the mean㻌wave direction. The factorial function in Eq. (9) reads‫ܥ‬ሺ݊ሻ ൌଵ ୻ሺ௡ାଵሻ.
ξగ ୻ሺ௡ାଵΤଶሻ

(10)

Results
We consider designing a wave farm composed of 2ൈ3 point absorbers (see Figure 2) at three sites in SouthEast Australia (see Figure 1). The wave energy device has a CorPower-like geometry (see Figure 3). The localised sea site information is listed in Table 1, sourced from Liu et al. [2]. By using the aforementioned
methodology and considering the localised sea conditions (such as peak wave height, peak wave period mean
wave direction, etc.), we numerically predicted the expected power generated by the potential wave farm. It isfound that the Cape Bridgewater is best suitable to deploy the wave farm, which generates an overall wave
power of 2.63 times that of Wilson’s Promontory, and 6.04 times that of Lakes Entrance.

r

s

s㻌

O6

Incident wave

O5

O4

s

s

O2

O3

E
O1

Figure 2. Array layout of the wave farm.

Figure 3. Surface mesh and geometrical dimensions of the point absorber device.
Table 1. Sea site information and the predicted wave power expectation.
Location
Cape Bridgewater
Wilson’s
Promontory
Lakes EntranceLongitude(°E)

Latitude
(°S)

Depth
(m)

Peak wave
height (m)Peak wave
period (s)Mean wave direction (°)

Expected
power (kw)

141.27

38.36

66.88

2.52

12.5

225

15.144146.47

39.54

75.98

1.74

7.65

240

5.756

148.41

38.05

53.08

1.05

6.25

200

2.506

References[1] Isaacs, J. D., and Schmitt, W. R. (1980). Ocean energy: Forms and prospects. Science 207, 265–273.
[2] Liu, J., Meucci, A., Liu, Q., Babanin, A. V., Ierodiaconou, D., & Young, I. R. (2022). The wave climate of Bass Strait and southeast Australia. Ocean Modelling, 172, 101980.
[3] Liu, Y., Liang, H., Kashiwagi, M., & Cong, P. (2021). Alternative approaches of evaluating diffraction transfer matrix and radiation
characteristics using the hybrid source-dipole formulation. Applied Ocean Research, 114, 102769.
[4] Evans, D. (1979). Some theoretical aspects of three-dimensional wave-energy absorbers. Proceedings of the 1st Symposium on
Wave Energy Utilization, Gothenburg, Sweden, pp.78–112.
[5] Falnes, J. (1980). Radiation impedance matrix and optimum power absorption for interacting oscillators in surface waves. Applied
ocean research, 2(2), 75-80.
[6] Goda, Y. (1999). A comparative review on the functional forms of directional wave spectrum. Coastal Engineering Journal, 41(1),1-20.

ᅜ㝿໬᥎㐍ඹྠ◊✲ᴫせ㻌
1R26

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WLFVVWXG\RIDQLQWHJUDWHGV\VWHPFRQVLVWLQJRIDIORDWLQJRIIVKRUHZLQGWXUELQHDQGRVFLOODWLQJERG\ZDYHHQHUJ\FRQYHUWHUV◊ ✲ ௦ ⾲ ⪅㸸=+28%LQ]KHQᡤෆୡヰே㸸๽ ┆⁄◊✲ᴫせ㸸 ᾋయᘧὒୖ㢼ຊⓎ㟁ᶵ䛸ἼຊⓎ㟁⿦⨨䠄WECs䠅䛛䜙ᡂ䜛䝝䜲䝤䝸䝑䝗䝅䝇䝔䝮
䛿䚸」ᩘ䛾ᾏὒ෌⏕ྍ⬟䜶䝛䝹䜼䞊䜢ᢳฟ䛩䜛᭷ᮃ䛺ᡭẁ䛷䛩䛜䚸ᗈ⠊䛺㐠⏝ᾏᇦ䛻䛚䛡䜛㐃ᡂືⓗ≉ᛶ䛿䚸タィ䛻䛚䛔䛶㔜せ䛺ཧ⪃᝟ሗ䛷䛒䜛䛻䜒䛛䛛䜟䜙䛪䚸䜎䛰༑ศ䛻⌮ゎ䛥䜜䛶䛔䛺䛔䚹䛣䛾◊✲䛷䛿䚸AeroDyn䠄NREL䠅䛸⊂⮬㛤Ⓨ䛾ィ⟬䝁䞊䝗䜢⤌䜏ྜ䜟䛫䚸㢼ຊ-Ἴຊ-ไᚚ-ಀ␃䛾㐃ᡂᩘ್䝒䞊䝹
䜢㛤Ⓨ䛧䛯䚹DeepCWind-Wave Stars 䛚䜘䜃 Hywind-annular WEC 䛾ືⓗ≉ᛶ䚸ಀ␃ᙇຊ䚸䜶䝛䝹䜼䞊ኚ᥮ᛶ⬟䜢ศᯒ䛧䛯䚹䛭䛾⤖ᯝ䚸WECs 䛾Ꮡᅾ䛜㐠⏝䝃䜲䝖䛾䝢䞊䜽Ἴ࿘ᮇ࿘㎶䛷ᾋయ䛾Ᏻᐃᛶ䜢ྥୖ䛥䛫䜛䛣䛸䛜♧䛧䛯䚹ಀ␃ᙇຊኚື䜢ῶᑡ䛥䛫䛴䛴䚸ᖹᆒ್䜢䜟䛪䛛䛻ቑຍ䛥䛫䜛䚹⏕ᡂ䛥䜜䛯Ἴຊ䛿䚸≉䛻㢼㏿䛜ᑠ䛥䛔ሙྜ䛻䛿㢼ຊ䛻㐺䛧䛯⿵᏶䛸䛺䜛ࠋ㞧ㄅㄽᩥ㸸 [1] Zhou, B., Zheng, Z., Hu, J., Lin, C., Jin, P., Wang, L., Liu, Y. (2023) Annual performance and dynamic
characteristics of a hybrid wind-wave floating energy system at a localized site in the North Sea.
Ocean Engineering, 280: 114872.
[2] Jin, P., Zheng, Z., Zhou, Z., Zhou, B., Wang, L., Yang, Y., Liu, Y. (2023) Optimization and evaluationof a semi-submersible wind turbine and oscillating body wave energy converters hybrid system. Energy, 282: 128889.
[3] Zhou, B., Wang, J., Ding, K., Wang, L., Liu, Y. (2023). Prediction of the Occurrence Probability ofFreak Waves in Unidirectional Sea State Using Deep Learning. Journal of Marine Science and Engineering, 2023, 11(12): 2296.

Introduction
To fully use the abundant renewable energy resources in the ocean, co-located energy extraction by
combining different kinds of ocean renewable energy equipment becomes a research frontier.㻌Hybrid systems
consisting of offshore wind turbines and wave energy converters (WECs) provide a promising scenario of
sufficient use of the strong sea wind and high waves, offering an excellent synergetic application since thehigh winds and waves often coexist[1]. Such combinations also show several merits of mutual benefits inaddition to more sufficient use of the local energy resource[2]. For example, wave energy is less developed
than offshore wind energy and is still an industry in its early age, facing the problem of high cost [3]. By
integrating WECs on an offshore wind turbine, the turbine can share infrastructure such as moorings,
supporting structures, power grids, and maintenance with the WECs, helping reduce the cost of the WECs[4][6]. In turn, the power generated by the WECs can compensate for the shortage of power output of the windturbine during its downtime, improving the stability of power generation[7]-[8].㻌 Till now, many concepts ofwind-wave hybrid systems have been proposed inspired by government or industrial support throughinnovative projects such as the EU EP7 MA-RINA[9].㻌Although many concepts of wind-wave hybrid systems
have been proposed and extensively studied, none have been constructed and applied in the real world. Few ofthem are in the sea trail stage. The development speed of hybrid systems depends on the technologicalmaturity of wind and wave energy equipment and their compatibility.

(a) Hybrid system (b) Configuration of hybrid system (c) DeepCWind(d) Wave Star

Fig. 1 Sketch and configuration of the DeepCWind-Wave Stars hybrid system and its components(a) 3D effect(b) Sketch of the hybrid system

(c) Underwater part of the spar(d) Sketch of the annular WEC

Fig. 2 Layout of the Hywind-annular WEC hybrid system
In this study, two kinds of hybrid system are proposed as shown in Fig. 1 and Fig. 2. The dynamic responseof the platform and both the wind and wave power performance of the hybrid system is investigated throughthe full aero-hydro-servo couplings numerical model, emphasizing on the influence of the addition of the
WECs.

Methodology
Motion equations
Based on Cummins' equation, the matrix form multi-body motion equation of the DeepCWind-Wave Stars
hybrid system ist>M  Af @ X(t )  ȀX(t )  ³ R(t  W )X(W )dW

Fex (t )  Fc (t )(1)0

ሶ , and X(t)ሷ are the vectors of displacement, velocity, and acceleration, respectively. M is thewhere X(t), X(t)matrix of mass. A is the matrix of added mass at infinite wave frequency. The inertia and hydrodynamic
coefficients (added mass, radiation damping, and wave excitation force) of the floats are calculated using the
WAFDUT code based on the potential flow theory of linear waves. K is the matrix of the hydrostatic
restoration coefficient. R is the matrix of radiation impulse response function (RIRF). t and Ĳ are time terms.
Fc(t) is the constraint force, which can be dealt with using the augment method based on the Lagrange
multiplier. Fex(t) is the sum of external forces:

Fex t

Fwave t  FPTO t  Fwind X, t  Fmoor X, t  Fvis t(2)where Fwave(t), FPTO(t), Fwind(t), Fmoor(t), and Fvis(t) are the wave excitation force, power take-off force,
aerodynamic force, mooring force, and fluid viscous force, respectively.
Power take-off modelLinear power take-off damping bPTO is assumed and it is also assumed that the amount of stiffness kPTO is
zero. As for the flap-type WEC, the power take-off force on the hinge and the wave power generated by a
Wave Star are:bPTOT (t )(3)

FPTOT (t ) bPTOT 2 (t )

(4)

FPTO
P

where ș and ߠሶ are the angular displacement and velocity relative to the hinge, respectively, withT

( L2 JW  L2 JP  L2 WP )arccos
2 u LJW u LJP(5)

where LJW, LJP and LWP are the characteristic lengths illustrated in Fig. 3.

Fig. 3 Profile of the Wave Stars in the hybrid system
As for heave-type WEC, the instant wave power generated through the relative heave motion of theplatform and the WEC is:

Pwave t2
1
bPTO zPlatformt  zWEC t
l f
2

(6)

The aero-hydro-servo couplings framework
The full aero-hydro-servo couplings in the hybrid system are included in the present model, and its
framework is shown in 㻲㼕㼓㻚㻌 㻠. The wind turbine is simulated by the aero-servo module of OpenFAST. The
coupled frequency-domain hydrodynamic coefficients of the floats, including added mass, radiation damping,
and wave excitation force, are calculated by the WAFDUT code developed by the Dalian University ofTechnology based on a Higher Order Boundary Element Method (HOBEM). The mooring loads are calculated
based on the catenary theory. All three tools are compiled by Fortran language. An in-house code also
compiled by Fortran is developed to create interfaces to bridge the three. The in-house code also simulates themulti-body constraint dynamics, performs the frequency-to-time domain transformation of the multi-body
motion equation, and calculates the wave power. The wind power is calculated by OpenFAST. The

aerodynamic loads on the blades, nacelle, and tower are calculated by OpenFAST according to the wind speed
and position of the turbine and are delivered by the in-house code to calculate the motion of the platform. The
displacement and velocity of the platform are in turn delivered by the in-house code to the turbine. The
mooring loads are calculated according to the motion of the platform and delivered by the in-house code to theplatform.
Motion Equation in time domain
Incident wave
Diffraction
Force

Froude-Krylov
Force

Radiation
Force

External
Force
Mooring
Load
PTO
Force

Hybrid System

WEC
Responses

Platform
Responses

Mooring
Dynamics

Aerodynamics (in Open FAST)
Drivetrain
Responses

Wind Turbine
ProfileRotor
Responses

Constraint

NacelleResponses

Viscous
Force

Tower
Responses

Tower-base loads & Turbine mass

Control
SystemAirfoil Loads

Airfoil
Performance

Steady Wind

Coupling

Platform position, velocity and acceleration

㻌Fig. 4 Coupling framework of the present numerical model
Results
DeepCWind-Wave Stars hybrid system
The influence of the arm projection Lh on wave power generation is investigated. The tendency of wave
power and wave amplitude along the direction of the arm are also compared. The contained angle is set as
ĳ=0. Fig. 5 shows the wave power P and wave amplitude of the Wave Stars layout location A for a range ofarm projection lengths under the incident wave of Tp=5.3 s. Fig. 5a shows that the tendency of the wave powerof WEC #2 is similar to that of the wave amplitude but with a slight drift to larger Lh. This deviation caused by
the addition of the WEC has a small disturbance on the local wave amplitude by diffraction and radiation. Fig.
5b shows that while the distance between WEC #1 or WEC #3 and the corresponding side column is far, thetendency of wave power is coherent with that of the wave amplitude. The radiation and diffraction of the
WEC also cause a little deviation. Both Fig. 5a and Fig. 5b show that while a WEC is close to the sidecolumn, its power generation dramatically increases. This is due to the complex radiation and diffraction as
the device is placed close to the column. In this mode, water resonates in the narrow gap between the Wave
Star and the side column, inducing a very high wave force that promotes the motion of the Wave Star to obtaina large power output. Fig. 5c shows the tendency of the total power generation, which is similar to that of
WEC #2. The maximum wave power can be obtained at Lh=25.13 m, while the maximum wave amplitude
occurs at Lh=22.87 m. Although the maximum power cannot be obtained when the Wave Stars are precisely
placed where the highest wave amplitude exists due to the disturbance of the platform, the difference (2.26 m)
is not significant compared with the radius of the Wave Star, and the power output only decreases by 7.06%.

Therefore, for rapid design of the layout of the Wave Stars, the location of the highest wave amplitude can beused as a criterion. Lh=22.87 m is thereafter used as the optimal arm projection.
The optimal contained angle ĳ is then determined. Fig. 6 shows the total wave power under contained
angles ĳ = 0, 15°, 22°, 30°, 37°, and 45° while the arm projection remains Lh=22.87 m. The total power firstincreases and then decreases as the contained angle grows, peaking at M=30°. From the perspective of power
output maximization, the arm projection Lh=22.87 m and included angles M=30° are regarded as thepreliminary optimized layout of the Wave Stars, which will be used in the rest of the analysis.
2.0

2.0

200

200

150

1.0

100

0.5

50

0

5

10

15

20

25

30

35

150

1.0

100

0.5

0

0

5

10

Arm projection Lh (m)

15

25

30

50

35

Arm projection Lh (m)(a) WEC #2(b) WEC #1 or #3
500

5.0

Wave amplitude A
Power generation P

4.5

Wave amplitude A (m)

20

450

4.0

400

3.5

350

3.0

300

250

2.5

Lh=22.87 m
2.0Power generation P (kW)

0.0

1.5

Power generation P (kW)

1.5

Wave amplitude A (m)WEC #1& #3 Wave amplitude A
WEC #1& #3 Power generation P

Power generation P (kW)Wave amplitude A (m)WEC #2 Wave amplitude A
WEC #2 Power generation P

0

5

10

15

20

Lh=25.13 m
25

30

35

200

Arm projection Lh (m)(c) Total power
Fig. 5 The power generation and amplitude for different arm projections (T=5.3 s, M=0°)

Power generation P (kW)

550
500
450
400
350
300

0

10
20
30
Contained angle M °40

50

Fig. 6 The power generation for different included angles (T=5.3 s, Lh=22.87 m)

Fig. 7 shows the total power generation (sum of wind and wave power) of the hybrid system and the
proportions of wind power and wave power. The regular incident wave is Tp=5.3 s. The wind speed is U=0, 8m/s, 11.4 m/s, and 14 m/s. The integration of the Wave Stars will not reduce the power generated by windturbine. Also, under each wind condition, the Wave Stars can provide power over 500 kW, which can bevaluable to the whole while the wind turbine is experiencing downtime. As wind speed increases, theproportion of wave power becomes smaller. As the wind speed reaches the critical speed of U=11.4 m/s, theproportion of the wave power keeps about 10%. Considering that in most situations, the average wind speed in
the South China Sea is smaller than 10.7 m/s and the average wave height is larger than 2 m, the percentage ofwave power in the total power generation can be larger than that in the U= 8 m/s (23.8%), which could be aneffective supplement.
7000
Wave power
Wind power

Total power (kW)

6000

4980

5000

5565

5542

(4980+585)(4990+552)

10.5%

4990

10.0%

4000
2333

3000
1777

2000
1000
0

90.0%

89.5%

(1777+556)

23.8%
76.2%

525
0
SingleHybrid

U=0 m/sSingleHybrid

U=8 m/sSingleHybrid

U=11.4 m/s

SingleHybrid

U=14 m/s

Fig. 7 Power generation of the hybrid system at different wind speeds (Tp=5.3 s, A=1 m)
Hywind-annular WEC hybrid system
The motion response of the Hywind platforms in the hybrid system, in isolation, and the difference between
the two in the surge, heave, and pitch directions are shown in Fig. 8-Fig. 10, respectively. In each DoF, thechanging trends of motion response of the Hywind in the hybrid system and isolation are nearly the same, but
those in the surge and pitch directions are slightly different from that in the heave direction. The heave motion
response almost changes little for different wind speeds, increasing as the wave period increases. The
fundamental pattern can be divided into two parts in the surge and pitch directions, separated by the rated
wind speed. In either part with wind speed smaller or larger than the rated wind speed, the motion responsechanges quite slightly against wind speed, which increases as the wave period increases. A sudden drop in
motion response occurs around the rated wind speed, and this phenomenon is more evident in long waves.
As shown in Fig. 8c~Fig. 10c, the difference in the motion response is quite evenly distributed against thewind speed but changes largely against the wave period, indicating that the sudden drop is not caused by theannular WEC. The sudden declines in the surge and pitch motion response are caused by the servo system. As
wind speed grows beyond the rated value, a switch of mode in the servo system changes the dynamic featureof Hywind, which triggers the sudden drop. The working principle of the servo system is to adjust the position

of the wind turbine to make the rotor directly face the input wind. The servo system is sensitive to the surgeand pitch motions of the platform as they affect the relative speed between the rotor and the input wind but is
not sensitive to the heave motion. As the waves become longer, the wave forces increase and excite a larger
motion, which exerts a greater influence on the servo system and intensifies the sudden drop.
The difference between the Hywinds in the hybrid system and isolation shows that the motion in any of thethree DoFs will be increased by installing an annular WEC. The mechanism is quite simple in the surge andpitch directions. The annular WEC brings additional wave force, damping, and hydrostatic restoration
stiffness in any of the three DoFs. A rigid connection passes the wave forces on the annular WEC to the windplatform. The increase in wave force will increase the motion response of the Hywind, whereas the increases
in damping and hydrostatic restoration stiffness will reduce the motion response. The results indicate that theincrease in wave force exceeds the increases in damping and hydrostatic restoration stiffness, and the motion
response is consistently increased. As the surge motion of the hybrid system has a limited effect on the wave
power generation using the relative heave motion, an extended active tuned mass damper or tuned massdamper-nonlinear energy sink can be employed to mitigate the WEC-induced increase in the surge motion
response. In the heave direction, the mechanism is a bit more complex as the presence of the PTO force
constitutes an additional source of the force that intensifies the motion response of Hywind. The difference inthe motion response between the Hywind in the hybrid system and isolation is also dominated by wave
conditions. Above all, the dynamic stability of the Hywind depends on wave conditions and is reduced by theannular WEC. The reduction in the heave direction is greater than in the surge and pitch directions.
Fig. 11 shows differences between the Hywinds in the hybrid system and isolation in the maximum
displacements in the surge, heave, and pitch directions. Generally, the annular WEC reduces the maximum
displacements of the Hywind in the surge and pitch direction and increases that in the heave direction. It
improves the stability of the Hywind in the pitch direction, particularly around the rated wind speed. On theother hand, a compromise between the generation of wave power and the increase in the heave motion has tobe made according to specific situations.

Wind speed Uwind (m/s)

0.1
20

1.225

0.2

0.7

1.050

0.8

0.3
15

0.6

0.4

0.875

0.9

0.700

1.0

0.525

10

0.5

1.1

0.350

1.2
5

1.3
3

(b) Platform surge amplitude (m)
25

1.400

6
9
12
Wave period (s)(a) Hybrid

15

0.175
0.000

0.1
20

0.750

0.6

0.625
15

0.3

0.500
0.5

10

0.375
0.7

5

0.250
0.125

0.8
3

6
9
12
Wave period (s)(b) Hywind(c) Difference of platform surge amplitude (m)
25
1.00

0.875

0.4
0.2

1.000

15

0.000

Wind speed Uwind (m/s)(a) Platform surge amplitude (m)Wind speed Uwind (m/s)

25

0.80

20

0.60
15

0

0.40
0.20

10
0

-0.00
5
3

6

9

12

15

Wave period (s)(c) Difference (HybridíHywind)

Fig. 8 Motion amplitudes of Hywind in surge direction

-0.20

20

1.05

1.0

0.90

0.3

0.75

0.5

15

0.60

0.7

0.45

10

0.9
0.30

20

3

6
9
12
Wave period (s)

15

0.19
0.10

15

0.16
0.15

0.13
0.09

10

0.15

5

0.20

3

(a) Hybrid

0.06(c) Difference of platform heave amplitude (m)
25
1.00
0.20

6
9
12
Wave period (s)

15

0.80

20
0.40

0.60

15
0.60

0.40

10
0.20

0.80

0.03

5

0.00

0.25
0.22

0.05
Wind speed Uwind (m/s)

Wind speed Uwind (m/s)

0.1(b) Platform heave amplitude (m)
25

1.20

Wind speed Uwind (m/s)(a) Platform heave amplitude (m)
25

5

0.00

3

6

9

12

15

0.00

Wave period (s)(c) Difference (HybridíHywind)(b) Hywind

Fig. 9 Motion amplitudes of Hywind in heave direction

0.75

20
0.5

0.1
15

0.60
0.45

0.6

0.2

0.30

10
0.3

0.7
0.8

5
3

6
9
12
Wave period (s)15(b) Platform pitch amplitude (°)
25

0.50

20

0.40

0.30

0.2

15

0.3

0.1

0.20

10
0.4

0.15

(c) Difference of platform pitch amplitude (°)
25
0.80Wind speed Uwind (m/s)

0.90Wind speed Uwind (m/s)

Wind speed Uwind (m/s)(a) Platform pitch amplitude (°)
25
0.7

0.60
0.00

15

0.40

10

0.20

0.00

0.10
5

5
0.00

20

3

(a) Hybrid

6912Wave period (s)

15

0.00

0.20

0.4
3

6

9

12

15

0.00

Wave period (s)(b) Hywind(c) Difference (HybridíHywind)

Fig. 10 Motion amplitudes of Hywind in the pitch direction

15

-2.00

-2.0
-3.0

10

-2.0

-3.0

-4.0

-1.0

6

9

12

Wave period (s)(a) Surge

20

0.50
0.4

15
0.0

0.8

0.00
0.8

10
-0.50

0.6

-0.50

20

-1.00
15

-1.50
-2.0
-2.0

10

0.0
15

-2.50

5

5
-5.00

-2.00

-1.0

-4.00

5
3

-3.00

-1.0
Wind speed Uwind (m/s)-1.00

Difference of platform pitch maximum (°)
25
0.00

0.2

0.00

-1.0

20

Difference of platform heave maximum (m)25
1.00Wind speed Uwind (m/s)

Wind speed Uwind (m/s)

Difference of platform surge maximum (m)
25
1.00

3

6
9
12
Wave period (s)(b) Heave

15

-1.00

0.0
3

6

9

12

15

-3.00

Wave period (s)(c) Pitch

Fig. 11 Difference of platform maximum displacements between hybrid system and HywindThis section investigates the mutual influence between the wind turbine and the annular wave energy

converter on their transient wind and wave energy conversion performance. Fig. 12 shows the wind power ofthe hybrid system, the isolated Hywind, and the difference between the two. The general trend of wind power
in different sea states is not affected by the annular WEC. The wind power increases to its rate power 5 MW
as wind speed increases to U=11.4 m/s and keeps approximately constant as wind speed further increases,
which is the same as that shown in Fig. 12b. The wind power distributes quite evenly against the wave period,
indicating it is nearly unaffected by the wave condition.
Fig. 12c shows that the annular WEC slightly improves the wind power while the wind is below the rated
speed, particularly in shorter waves. This is because the annular WEC reduces the equilibrium tilted angle ofthe Hywind in the pitch direction, making the rotor face the input wind more directly. In the shorter waves, themotion amplitude in the pitch direction is smaller, which leads to a more stable increase in wind power. Whilewind is beyond the rated speed, the wind power reaches its upper limit and cannot be further improved by theannular WEC. Evidence can be found in the comparison between Fig. 11c and Fig. 12c, where the increase inwind power shows similar trends to that of the decrease of the platform displacement in the pitch direction.
Fig. 13 shows the wave power of the hybrid system in different sea states. The mean peak period Tave=8.54
s is marked by a white line. The wave power increases and then decreases, reaching a peak at 8.54 s, whereas

5050(b) Wind turbine output power (kW)
25

5050

(c) Wind turbine output power (kW)
25

100

20

4040

20

4040

20

80

3030

15
5000
4000

10

2020
3000
2000
1000

5000

6
9
12
Wave period (s)

2020
4000

10

1010

3000
2000
1000

15

0

80

10

20

40

40

40
60
20

20

5
3

6

9

12

0

15

3

6

9

12

15

0

Wave period (s)Wave period (s)(b) Hywind(a) Hybrid

60

15

1010

5

5
3

3030

15

Wind speed Uwind (m/s)(a) Wind turbine output power (kW)25

Wind speed Uwind (m/s)

Wind speed Uwind (m/s)

it is nearly not affected by wind speed.

(c) Difference (HybridíHywind)

Fig. 12 Wind turbine output power under different wind speeds and wave periods澳

Wind speed Uwind (m/s)

Wave energy conversion power (kW)
25
450

20

400

100

100

350

200

300

200

15

250
300

200
150

300

10

100
50

5
3

6
9
12
Wave period (s)150Fig. 13 Wave power production of the hybrid system under different wave periods and wind speedsReferences[1]

Chen, X., Wang, K., Zhang, Z., Zeng, Y., Zhang, Y., & O'Driscoll, K. (2017). An assessment of wind and wave climate as
potential sources of renewable energy in the nearshore Shenzhen coastal zone of the South China Sea. Energy, 134, 789-801.

[2]

Clemente, D., Rosa-Santos, P., & Taveira-Pinto, F. (2021). On the potential synergies and appli-cations of wave energy
converters: A review. Renewable and Sustainable Energy Reviews, 135, 110162.

[3]

Astariz, S., & Iglesias, G. (2015). The economics of wave energy: A review. Renewable and Sustainable Energy Reviews, 45,397-408.

[4]

Hu, J., Zhou, B., Vogel, C., Liu, P., Willden, R., Sun, K., & Collu, M. (2020). Optimal design and performance analysis of a
hybrid system combing a floating wind platform and wave energy converters. Applied Energy, 269, 114998.

[5]

Zhang, H., Zhou, B., Zang, J., Vogel, C., Fan, T., & Chen, C. (2021). Effects of narrow gap wave resonance on a dual-floater
WEC-breakwater hybrid system. Ocean Engineering, 225, 108762.

[6]

Zhang, H., Zhou, B., Zang, J., Vogel, C., Jin, P., & Ning, D. (2021). Optimization of a three-dimensional hybrid system
combining a floating breakwater and a wave energy converter array. Energy Conversion and Management, 247, 114717.

[7]

Chozas, J. F., Sørensen, H. C., & Jensen, N. H. (2012). Economic benefit of combining wave and wind power productions in
day-ahead electricity markets. In 4th International Conference on Ocean Energy.

[8]

Chozas, J. F., Kofoed, J. P., & Sørensen, H. C. (2013). Predictability and Variability of Wave and Wind: wave and windforecasting and diversified energy systems in the Danish North Sea. Department of Civil Engineering, Aalborg University. DCE
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Platform, M. A. R. I. N. A. European Union Seventh Framework Programme (EU FP7) Marine Renewable Integrated
Application Platform (MARINA Platform).

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