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This report presents a detailed analysis of passenger mobility congestion and energy use at Kowloon Bay, focusing on HVAC comfort, daylighting, and egress modeling. Employing the MACDADI tool, we define objectives, determine priorities, and analyze alternatives aimed at optimizing congestion and energy costs. The study evaluates multiple ingress and egress scenarios, showcasing data-driven results indicating the most efficient alternatives in terms of time and comfort. Recommendations include enhanced escalator placement and entrance modifications to improve passenger flow while identifying energy-saving strategies.
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Kowloon Bay Sarah Chan, AimaOjehomon, AkshayAdya, EnoInyang
Objectives MACDADI Tool Define Objectives… …Determine Priorities
Preferences MACDADI Tool Define Objectivs… …Determine Priorities
Alternatives Exit Exit Exit
Objectives • Congestion Analysis • Egress Energy Use Analysis • HVAC Comfort • Daylighting
Passenger Mobility Congestion Baseline model peak 6pm weekday Show model, cite conges Entrance B platform escalator Entrance A platform escalator 28 minutes into rush hour
Passenger Mobility Congestion Baseline model peak 6pm weekday Show model, cite conges Entrance B platform escalator Entrance A platform escalator 28 minutes into rush hour
Passenger Mobility Congestion Baseline model peak 6pm weekday Show model, cite conges Entrance B platform escalator at 28 min
Passenger Mobility Congestion Baseline model peak 6pm weekday Show model, cite conges Entrance A platform escalator at 28 min
Passenger Mobility Congestion Defining Congestion Testing Method Traffic Congestion Analysis Time in system - Peak : Time in system - Target
Passenger Mobility Congestion Traffic Congestion Analysis Time in system - Peak : Time in system - Target
Passenger Mobility Congestion Traffic Congestion Analysis Time in system - Peak : Time in system - Target 2.7 min
Passenger Mobility Congestion Traffic Congestion Analysis Time in system - Peak : Time in system - Target Objectives
Passenger Mobility Congestion Alternative 1 – Simple Added Escalators To Double Capacity Direction Can Be Changed To Suit Flow
Passenger Mobility Congestion Alternative 2 – Intensive Entrance C Altered Escalators Added And Moved Turnstiles And Ticket Machines Moved
Passenger Mobility Congestion Results 2.7 m
Passenger Mobility Congestion Alternative 1
Passenger Mobility Egress - Data
Passenger Mobility Egress- Modelling • 1390 people • Randomly placed • 50 % Male & 50% Female • Low Stress, Co-operative • Multi Agent System People Exit Obstacles Goal
Baseline : 3 Exits Time : 5min 38 sec -1 Passenger Mobility Egress
Baseline : 3 Exits Time : 5min 38 sec -1 Passenger Mobility Egress
Alternative 1 : 4 Exits Time : 2 min 59 sec 1 Passenger Mobility Egress
Alternative 1 : 4 Exits Time : 2 min 59 sec 1 Passenger Mobility Egress
Alternative 2 : 5 Exits Time : 3 min 20 sec 0 Passenger Mobility Egress
Alternative 2 : 5 Exits Time : 3 min 20 sec 0 Passenger Mobility Egress
Cost Optimization Baseline (Tool : Hevacomp) Energy Usage General Parameters : 5-12 pm daily Kings Park, HK Glazed windows (Optifloat 6 mm argon) Design Temperature: Modeled as 26 °C Must be < 28 °C (summer) Max Temp outside air = 34 °C Only the Concourse Level is considered in the analysis.
Process Energy Usage
Cost Optimization Energy Analysis Energy Usage Escalator Energy pertaining to the Concourse = ½ of total (split between concourse and platform )
Cost Optimization Baseline Baseline Energy Usage -1 • Several open door entrances: • Two 4 x 3.4 m and one 10.5 x 3 m and one 5 x 3 m • 12 escalators
Cost Optimization Alternative 1 Alternative 1 Energy Usage -1 • Add 1 entrance, 10.5 x 3 m • Remove 2 windows • Add 2 escalators (14 total)
Cost Optimization Alternative 2 Alternative 2 1 Energy Usage 0 • Add 2 entrances, 10.5 x 3 m each • Remove rooms near each entrance • Add 1 escalator (13 total)
Cost Optimization Comaprison Comparison Energy Usage -1 Alternative 1 to the have the highest energy use, with 2 additional escalators Alternative 2 has the lowest energy use, even with 1 additional escalator -1 0
Passenger Comfort Modelling
Passenger Comfort HVAC (TAS) Inputs | Internal Conditions
Passenger Comfort HVAC (TAS) Inputs | Apertures Baseline: ‘Wall Openings – Doors’ Alternative 2: ‘Wall Openings – Doors’ + ‘Window Openings (alt 2)’ Alternative 1: ‘Wall Openings – Doors’ + ‘Window Openings (alt 1)’
Passenger Comfort HVAC (TAS) Analyses Alternative 2 Alternative 1 (& Baseline)
Passenger Comfort • HVAC Inferences • Creating these new openings has little to no effect on HVAC. • Internal temp (35⁰C) at peak external temp (36⁰C), 7⁰C over target temp (28⁰C).
Passenger Comfort HVAC Evaluation | Metrics
Passenger Comfort Daylighting Inputs | Revit
Passenger Comfort Daylighting Analyses | Shadow
Passenger Comfort Daylighting Analyses | Shadow
Passenger Comfort Daylighting Analyses | Illuminance
Passenger Comfort Daylighting Analyses | Illuminance (Baseline & Alt 1)
Passenger Comfort Daylighting Analyses | Illuminance (Alt 2)
Passenger Comfort Daylighting Inferences | General Alternative 2, with 2 more openings has a positive effect on daylighting
Passenger Comfort Daylighting Evaluation