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Maximizing the ENVI-met Capability of Modelling the Mean Radiant Temperature of a Tropical Archaeological Site

Binarti F.a,b, Koerniawan M.D.a, Triyadi S.a, Utami S.S.c

a Department of Architecture, Institut Teknologi Bandung, Indonesia
b Department of Architecture, Universitas Atma Jaya, Yogyakarta, Indonesia
c Department of Engineering Physics, Universitas Gadjah Mada, Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© Published under licence by IOP Publishing Ltd.ENVI-met is one of the most widely-used outdoor microclimatic models. Since previous studies found that ENVI-met tends to overestimate the MRT, this study attempted to maximize the ENVI-met capability of modelling the MRT in order to obtain accurate simulation results. This study developed three variations of the 3D-model and employed some features to improve the large MRT discrepancy between the field measurement and simulation that resulted from the preliminary model. The field MRT measurements were conducted using a globe-thermometer method on two hot days, i.e., September 21 and October 17. After comparing the results of field measurements and simulations, this study came into a conclusion that the current free version software is capable of performing MRT predictions with a low discrepancy (5%) by using “Solar Adjustment Factor”and “Cloud Conditions”features (19.7% improvement), and maximizing the spatial resolution. The spatial resolution in z-axis decreases the discrepancy by 2.5%.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]A-GLOBE,Adjustment factors,Archaeological site,ENVI-met,Field measurement,Mean radiant temperature,Preliminary model,Spatial resolution[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]Authors gratefully acknowledge the funding from USAID through SHERA program – Centre for Development of Sustainable Region (CDSR).[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1755-1315/541/1/012005[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]