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Kowloon Bay

Kowloon Bay. Sarah Chan, Aima Ojehomon , Akshay Adya , Eno Inyang. Introduction. Introduction. Team. Scope. Objectives. MACDADI Tool. Define Objectives…. …Determine Priorities. Preferences. MACDADI Tool. Define Objectivs …. …Determine Priorities. Alternatives. Exit. Exit. Exit.

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Kowloon Bay

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  1. Kowloon Bay Sarah Chan, AimaOjehomon, AkshayAdya, EnoInyang

  2. Introduction

  3. Introduction

  4. Team

  5. Scope

  6. Objectives MACDADI Tool Define Objectives… …Determine Priorities

  7. Preferences MACDADI Tool Define Objectivs… …Determine Priorities

  8. Alternatives Exit Exit Exit

  9. Objectives • Congestion Analysis • Egress Energy Use Analysis • HVAC Comfort • Daylighting

  10. 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

  11. 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

  12. Passenger Mobility Congestion Baseline model peak 6pm weekday Show model, cite conges Entrance B platform escalator at 28 min

  13. Passenger Mobility Congestion Baseline model peak 6pm weekday Show model, cite conges Entrance A platform escalator at 28 min

  14. Passenger Mobility Congestion Defining Congestion Testing Method Traffic Congestion Analysis Time in system - Peak : Time in system - Target

  15. Passenger Mobility Congestion Traffic Congestion Analysis Time in system - Peak : Time in system - Target

  16. Passenger Mobility Congestion Traffic Congestion Analysis Time in system - Peak : Time in system - Target 2.7 min

  17. Passenger Mobility Congestion Traffic Congestion Analysis Time in system - Peak : Time in system - Target Objectives

  18. Passenger Mobility Congestion Alternative 1 – Simple Added Escalators To Double Capacity Direction Can Be Changed To Suit Flow

  19. Passenger Mobility Congestion Alternative 2 – Intensive Entrance C Altered Escalators Added And Moved Turnstiles And Ticket Machines Moved

  20. Passenger Mobility Congestion Results 2.7 m

  21. Passenger Mobility Congestion Alternative 1

  22. Passenger Mobility Egress - Data

  23. Passenger Mobility Egress- Modelling • 1390 people • Randomly placed • 50 % Male & 50% Female • Low Stress, Co-operative • Multi Agent System People Exit Obstacles Goal

  24. Baseline : 3 Exits Time : 5min 38 sec -1 Passenger Mobility Egress

  25. Baseline : 3 Exits Time : 5min 38 sec -1 Passenger Mobility Egress

  26. Alternative 1 : 4 Exits Time : 2 min 59 sec 1 Passenger Mobility Egress

  27. Alternative 1 : 4 Exits Time : 2 min 59 sec 1 Passenger Mobility Egress

  28. Alternative 2 : 5 Exits Time : 3 min 20 sec 0 Passenger Mobility Egress

  29. Alternative 2 : 5 Exits Time : 3 min 20 sec 0 Passenger Mobility Egress

  30. 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.

  31. Process Energy Usage

  32. Cost Optimization Energy Analysis Energy Usage Escalator Energy pertaining to the Concourse = ½ of total (split between concourse and platform )

  33. 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

  34. 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)

  35. 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)

  36. 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

  37. Passenger Comfort Modelling

  38. Passenger Comfort HVAC (TAS) Inputs | Internal Conditions

  39. 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)’

  40. Passenger Comfort HVAC (TAS) Analyses Alternative 2 Alternative 1 (& Baseline)

  41. 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).

  42. Passenger Comfort HVAC Evaluation | Metrics

  43. Passenger Comfort Daylighting Inputs | Revit

  44. Passenger Comfort Daylighting Analyses | Shadow

  45. Passenger Comfort Daylighting Analyses | Shadow

  46. Passenger Comfort Daylighting Analyses | Illuminance

  47. Passenger Comfort Daylighting Analyses | Illuminance (Baseline & Alt 1)

  48. Passenger Comfort Daylighting Analyses | Illuminance (Alt 2)

  49. Passenger Comfort Daylighting Inferences | General Alternative 2, with 2 more openings has a positive effect on daylighting

  50. Passenger Comfort Daylighting Evaluation

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