https://repos.hcu-hamburg.de:443/handle/hcu/15 Tue, 13 Oct 2026 21:20:11 GMT 2026-10-13T21:20:11Z https://repos.hcu-hamburg.de:443/handle/hcu/1311 Title: Multiple Campus Center : Universität und Stadt vernetzen und weiterbauen Authors: Fusi, Paolo; Hecht, Martin; Baze, Dea; Gerhold, Jendrick; Griesenberg, Justus; Richter, Sina; Schoenhof, Hendrik; Shterva, Diana; Vogler, Simon; Will, Leon Tue, 13 Oct 2026 12:38:28 GMT https://repos.hcu-hamburg.de:443/handle/hcu/1311 2026-10-13T12:38:28Z https://repos.hcu-hamburg.de:443/handle/hcu/1310 Title: Evapotranspiration Measurements and Assessment of Driving Factors: A Comparison of Different Green Roof Systems during Summer in Germany Authors: Gößner, Dominik; Mohri, Milena; Krespach, Justine Jasmin Abstract: Green roofs have proven to be a space-saving solution to mitigate peak temperatures and control floods in urban areas through evaporative cooling and storm water retention. To encourage a sustainable city design with large-scale green infrastructure networks, a better differentiation between the diverse existing green roof systems is needed. The aim of this study is to demonstrate differences among green roof systems based on comprehensive microclimatic measurements on four small experimental roofs and to assess differences in evapotranspiration with a partial least square regression. The results show that short-wave solar radiation, relative humidity and water availability are the most important drivers of evapotranspiration. The roof system with permanent water storage maintained significantly higher substrate moisture compared to the other roofs and produced peak evapotranspiration rates of 4.88 mm d−1. The highest total evapo-transpiration of 526 mm from April to September was recorded for the roof system with the thickest substrate layer and grass vegetation. In summer, the shallowest roof showed the highest substrate temperature and air temperature at vegetation level. These findings highlight the importance of specifying the characteristics of the various green roofs in order to turn them into useful planning tools for the design of climate-change-resilient cities. Thu, 08 Oct 2026 12:07:26 GMT https://repos.hcu-hamburg.de:443/handle/hcu/1310 2026-10-08T12:07:26Z https://repos.hcu-hamburg.de:443/handle/hcu/1309 Title: Operational Decision Support for Evacuating Nursing Home Residents: A Hamburg Benchmark and Metaheuristic Comparison Under a 5-Minute Time Budget Authors: Alexander, Nick; Tannenbaum, Milva; Noennig, Jörg Rainer Abstract: Evacuating mobility-impaired nursing home residents during urban emergencies requires routing and scheduling heterogeneous vehicles under minute-level deadlines. We introduce the Nursing Home Evacuation Vehicle Routing Problem (NH-Evac-VRP) with open-ended multi-trip shuttling, split pickups, load-dependent service times, and shelter capacities; solutions must be produced within a hard 300 s single-thread budget. We release the Hamburg-NH-Evac benchmark with two expert-specified scenarios: (i) an unexploded-ordnance exclusion-zone evacuation in Altona-Altstadt (479 evacuees, one shelter), (ii) a storm-surge evacuation in Wilhelmsburg (510 evacuees, three shelters), plus (iii) a synthetic stress test (1,348 evacuees, five shelters). Instances use real facility data and asymmetric road-network travel times. Across five scenario-fleet configurations, we compare a constructive dispatcher with a Genetic Algorithm, Memetic Algorithm, and Adaptive Large Neighborhood Search, minimizing demand-weighted average waiting time and makespan with a shelter-overfill penalty. No method dominates: ALNS attains the best makespan in two configurations; in the heterogeneous Flood-Augmented case this advantage is driven by capacity-maximizing "sweeper" tours. MA is best in three configurations by favoring rapid shuttle cycles, outperforming ALNS by 27 min in the synthetic mass-transit case. We also provide a web-based decision support system for scenario configuration, optimization, and schedule visualization. Thu, 01 Oct 2026 14:08:02 GMT https://repos.hcu-hamburg.de:443/handle/hcu/1309 2026-10-01T14:08:02Z https://repos.hcu-hamburg.de:443/handle/hcu/1308 Title: Advanced spatio-temporal source–demand matching for practical waste heat utilization in district heating Authors: Salaymeh, Abdulraheem; Holler, Stefan; Peters, Irene Abstract: Waste heat is widely recognized as a key lever for advancing climate neutrality in urban heating systems. While recent policy regulations have significantly improved the transparency of waste heat potentials, the gap between reported theoretical potentials and their practical usability remains insufficiently explored. This study develops a novel residual-aware, guided source–demand allocation approach, leveraging officially reported, technically detailed waste heat source information and high-resolution building typology data to reveal key insights into spatial and technical utilization potentials and limitations. The results also derive key distributional and operational source characteristics, combined with spatial and typological building patterns, considering three refurbishment scenarios. The proposed methodology provides a transparent and policy-relevant tool for translating reported waste heat potentials into actionable planning insights. The results indicate that the utilizable share of the reported waste heat potential is reduced to approximately 35 % due to techno-spatial constraints, decreasing further to approximately 24 % when temporal source–demand coincidence is additionally considered. Depending on building refurbishment progress, the number of potentially supplied buildings ranges from 1.8 to 5.7 million. Overall, these findings demonstrate that coordinated spatio-temporal planning, combined with efficiency measures, is essential to unlock the significant, yet primarily spatially constrained, waste heat potential. Thu, 01 Oct 2026 13:30:49 GMT https://repos.hcu-hamburg.de:443/handle/hcu/1308 2026-10-01T13:30:49Z