Update models/digital_twinning.md

Co-authored-by: Robert Chisholm <Robadob@Robadob.org>

Author: mondus

models/digital_twinning.md

@@ -5,7 +5,7 @@ permalink: "models/digital-twinning"
 
 ![Digital Twinning of Urban Transportation Systems Road Network Model Close-up]({{ "/assets/images/models/digital-twinning.png" | relative_url }}){: .align-right .no-shadow} 
 
-In collaboration with Fujitsu Research of Europe, the FLAME GPU team undertook a collaborative development project to assist in applying FLAME GPU to the simulation of urban transportation systems in order to create a digital twin of the Isle of Wight. The focus of model development was on transportation micros simulation and road networks (junctions). The developed model aims to replicate a subset of the individual and junction models from the open source Simulation of Urban MObility (SUMO) within FLAME GPU. Computational experiments have indicated that speedups over SUMO of ~68x are achievable on desktop GPUs (Intel Core i7-5930K CPU, an NVIDIA GeForce RTX 3090 (24 GiB) GPU). This is equivalent to simulating ~100x faster than real time with a maximum load of 95k vehicles.
+In collaboration with Fujitsu Research of Europe, the FLAME GPU team undertook a collaborative development project to assist in applying FLAME GPU to the simulation of urban transportation systems in order to create a digital twin of the Isle of Wight. The focus of model development was on transportation micro-simulation and road networks (junctions). The developed model aims to replicate a subset of the individual and junction models from the open source Simulation of Urban MObility (SUMO) within FLAME GPU. Computational experiments have indicated that speedups over SUMO of ~68x are achievable on desktop GPUs (Intel Core i7-5930K CPU, an NVIDIA GeForce RTX 3090 (24 GiB) GPU). This is equivalent to simulating ~100x faster than real time with a maximum load of 95k vehicles.
 
 
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