History of changes to: Monitoring airborne transmission inside buildings using MF-BM
Date Action Change(s) User
Nov. 27, 2023, 2:13 p.m. Added 35 {"external_links": []}
Nov. 20, 2023, 2:03 p.m. Added 35 {"external_links": []}
Nov. 13, 2023, 1:34 p.m. Added 35 {"external_links": []}
Nov. 6, 2023, 1:31 p.m. Added 35 {"external_links": []}
Aug. 14, 2023, 1:31 p.m. Added 35 {"external_links": []}
Aug. 7, 2023, 1:32 p.m. Added 35 {"external_links": []}
July 31, 2023, 1:34 p.m. Added 35 {"external_links": []}
July 24, 2023, 1:36 p.m. Added 35 {"external_links": []}
July 17, 2023, 1:35 p.m. Added 35 {"external_links": []}
July 10, 2023, 1:26 p.m. Added 35 {"external_links": []}
July 3, 2023, 1:26 p.m. Added 35 {"external_links": []}
June 26, 2023, 1:26 p.m. Added 35 {"external_links": []}
June 19, 2023, 1:27 p.m. Added 35 {"external_links": []}
June 12, 2023, 1:29 p.m. Added 35 {"external_links": []}
June 5, 2023, 1:33 p.m. Added 35 {"external_links": []}
May 29, 2023, 1:28 p.m. Added 35 {"external_links": []}
May 22, 2023, 1:29 p.m. Added 35 {"external_links": []}
May 15, 2023, 1:32 p.m. Added 35 {"external_links": []}
May 8, 2023, 1:37 p.m. Added 35 {"external_links": []}
May 1, 2023, 1:28 p.m. Added 35 {"external_links": []}
April 24, 2023, 1:35 p.m. Added 35 {"external_links": []}
April 17, 2023, 1:28 p.m. Added 35 {"external_links": []}
April 10, 2023, 1:25 p.m. Added 35 {"external_links": []}
April 3, 2023, 1:26 p.m. Added 35 {"external_links": []}
Jan. 28, 2023, 11:09 a.m. Created 43 [{"model": "core.projectfund", "pk": 29308, "fields": {"project": 6526, "organisation": 4, "amount": 91633, "start_date": "2020-11-01", "end_date": "2021-04-29", "raw_data": 48587}}]
Jan. 28, 2023, 11:09 a.m. Created 40 [{"model": "core.projectperson", "pk": 54512, "fields": {"project": 6526, "person": 11161, "role": "PM_PER"}}]
Jan. 28, 2023, 10:52 a.m. Added 35 {"external_links": []}
April 11, 2022, 3:48 a.m. Created 43 [{"model": "core.projectfund", "pk": 21441, "fields": {"project": 6526, "organisation": 4, "amount": 91633, "start_date": "2020-11-01", "end_date": "2021-04-29", "raw_data": 30554}}]
April 11, 2022, 3:48 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 80969, "fields": {"project": 6526, "organisation": 8255, "role": "PARTICIPANT_ORG"}}]
April 11, 2022, 3:48 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 80968, "fields": {"project": 6526, "organisation": 8255, "role": "LEAD_ORG"}}]
April 11, 2022, 3:48 a.m. Created 40 [{"model": "core.projectperson", "pk": 49984, "fields": {"project": 6526, "person": 9269, "role": "PM_PER"}}]
April 11, 2022, 1:48 a.m. Updated 35 {"title": ["", "Monitoring airborne transmission inside buildings using MF-BM"], "description": ["", "\nPublic Health England guidance on infection control attributes COVID-19 major transmission modes to respiratory droplets generated though coughing, sneezing and the contact with contaminated surfaces. Heavy droplets can fall out of airstream within a short distance, however relatively light droplets can travel further in air streams. Therefore, a key challenge is mapping droplet spread to identify contaminated surfaces or zones to minimise health and safety risk in building space. COVID-19 has had major impact on the Global Coworking Spaces Market. However, the market is expected to rise post pandemic due to more companies supporting remote working practices in the longer term. Therefore, it becomes imperative to take steps for efficiently managing increasing energy demand and the associated carbon footprint of the facilities hosting coworking spaces whilst supporting it to deliver a healthy and COVID -19 secure workplace. The step would ensure that it does not have a negative impact on the larger decarbonisation agenda.\n\nCurrently, no market solution offers to track droplet spreading and identify probable contaminated surfaces or zones, instead focussing on effectively managing an HVAC system to maintain fresh supply of airflow with an anticipation of diluting the virus particles inside the building. Some market providers offer AI powered video solutions for automated contact tracing once an active case is detected at the workplace. However, the solution relies heavily on extensive video surveillance and can potentially create privacy issues for the end-user.\n\nTwin Dynamics Limited (TD) has developed a Multi-Fidelity Building Model (MF-BM) technology which offers near real-time airflow and thermal insight within the building space and is used to evaluate localised individual occupant thermal comfort and their productivity. This technical data can be used by the Facility Mangers to create a balance between the ventilation inside the building space for optimal thermal comfort and energy cost, which leads to reduce carbon-footprint. MF-BM works by combining real-time pressure, flow rate and temperature sensors' data with high fidelity fluid dynamics simulations, using in-house developed code by TD. However, as airflow within building spaces acts as a respiratory droplet carrier, TD are keen to further develop the technology to predict near real-time droplet spread and its predicted settlement locations within building space.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Closed"]}
April 11, 2022, 1:48 a.m. Added 35 {"external_links": [23894]}
April 11, 2022, 1:48 a.m. Created 35 [{"model": "core.project", "pk": 6526, "fields": {"owner": null, "is_locked": false, "coped_id": "4b846b3f-7dab-421e-bb20-b273a71cefa5", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 30538, "created": "2022-04-11T01:43:23.568Z", "modified": "2022-04-11T01:43:23.568Z", "external_links": []}}]