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DTSTART;TZID=America/New_York:20260611T150000
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SUMMARY:Seminar: Physical Attribute-Driven NFD Approach for Bicycle Network Design
DESCRIPTION:Abstract: Urban street networks are increasingly expected to serve multiple modes simultaneously\, yet tools for understanding how physical design choices affect aggregate traffic performance\, translating those predictions into infrastructure investment decisions\, and quantifying the equity trade-offs among those decisions remains limited. This work addresses these gaps through the estimation of an NFD functional form based on physical attributes of active mobility infrastructure which is then employed to develop network designs informed by varying equity objectives. The physical-infrastructure-informed NFD functional form links traffic performance\, such as capacity\, jam density\, and flow dynamics\, to spatial design characteristics including the among of area allocated to each mode\, space for interaction between modes\, and type of separation between modes. This form was calibrated using high-resolution simulation outputs from multimodal SUMO networks which allowed for differences in flow behavior across modes and designs to be captured in high density scenarios. A two-stage optimization framework was implemented to determine an optimal assignment of bike lane types across network links based on this functional form. The first stage maximizes the developed functional form to return optimal values of the spatial design characteristics. The second step makes use of a genetic algorithm (GA) to generate networks optimizing for flow\, accessibility\, and adherence to ethical frameworks. By evaluating candidate solutions using the estimated NFD\, the algorithm selects infrastructure configurations that maximize network efficiency while also reducing congestion impacts on disadvantaged communities. This framework contributes an integration of macroscopic traffic modeling into network design for multimodal systems with additional equity-focused optimization.
URL:https://c2smart.engineering.nyu.edu/event/seminar-physical-attribute-driven-nfd-approach-for-bicycle-network-design/
CATEGORIES:Student Events,Virtual Events
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DTSTART;TZID=America/New_York:20260623T120000
DTEND;TZID=America/New_York:20260623T130000
DTSTAMP:20260530T093327
CREATED:20260526T184820Z
LAST-MODIFIED:20260526T185142Z
UID:90875-1782216000-1782219600@c2smart.engineering.nyu.edu
SUMMARY:Bridge Resource Program Rime Webinar: Fusion of SHM and WIM Data for Minimizing the Cracking Potential of Concrete Bridge Decks
DESCRIPTION:This webinar focuses on the fusion of Structural Health Monitoring (SHM) data and Weigh-In-Motion (WIM) data to predict strain responses from live truck loads and support early-age crack mitigation strategies. A digital twin of a multi-span bridge was developed using a Finite Element Model (FEM) and calibrated based on the SHM data. The webinar will present how truck traffic and load data from WIM and structural responses from SHM can be used in the FEM under realistic loading scenarios during construction to support decision-making for the pouring sequence. The fusion of SHM\, WIM and FEM provides advanced predictions of structural behavior allowing for optimization of the concrete placement schedules by selecting a window of time to mitigate cracking while minimizing traffic restrictions. \nThis webinar will cover innovative methods for obtaining and combining analysis for\nNondestructive Material testing – Testing Concrete Samples and temperature over time for early age nondestructive strength evaluation of the structural element\nDeveloping a Truck live load profile – Onsite Weigh-In-Motion (WIM) System profiles truck traffic\nBridge superstructure behavior under known truck load – Bridge Instrumentation using strain gauges\, accelerometers\, and deflectometers\nLong term concrete shrinkage and thermal strain of bridge deck – Embedded sensor assessment of bridge deck & girder elements\nDigital twin – Finite Element Model for identifying strains that can produce cracking\nPost install evaluation – Crack Mapping and Analysis \nPresented by Rutgers’s Prof. Hani Nassif\, Dr. Chaekuk Na\, and Michael Ruszala
URL:https://c2smart.engineering.nyu.edu/event/bridge-resource-program-rime-webinar-fusion-of-shm-and-wim-data-for-minimizing-the-cracking-potential-of-concrete-bridge-decks/
CATEGORIES:Seminars,Student Events,Virtual Events,Webinars
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