RFP QuestBeta
Awarded · ResultStage · contract

MINISTRY OF DEFENCE

FASTER - Ambient Noise Prediction, Merging of Water Column Parameters and Multi-model Propagation Model tasks

Government ServicesCPV 75000000
Value£201k
Awarded16 Jan 2024
Published6 Mar 2024
RegionLondon
Outcome — awarded

This is a contract result notice, not an open opportunity. Details from the official award data.

Contract value in context
£201ktotal contract value
median £400k
this tender£0£22.3m

This sits in the lower-middle of the Government & Public Administration band — a mid-scale opportunity. Based on 5,438 valued Government & Public Administration tenders in our corpus.

The brief

Ambient Noise Prediction - the supplier will deliver a solution that predicts received ambient noise at points in the ocean Merging of water column parameters - the supplier will deliver algorithms to perform combination and assessment of in-situ water column profiles Multi-model Propagation Model - the supplier will deliver documentation as to the verified valid frequency range of other FASTER models

Requirements

What the notice asks for

01

The supplier will deliver a solution

the supplier will deliver a solution that predicts received ambient noise at points in the ocean.

02

The supplier will deliver algorithms to perform

the supplier will deliver algorithms to perform combination and assessment of in-situ water column profiles.

03

The supplier will deliver documentation as

the supplier will deliver documentation as to the verified valid frequency range of other FASTER models.

Sentences from the notice that state an obligation, surfaced automatically and shown in the order they appear. Not an exhaustive list — always confirm against the tender documents.

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Source & provenance
OCID
eac08855-9183-44ab-bb4c-86bdba2ad37c
Stage
contract · Contract
Source
Contracts Finder
Buyer ref
FASTER - Ambient Noise, Merging of Water Column Parameters and Multi-model Propagation Model
View the original notice on Contracts Finder

Contains public sector information licensed under the Open Government Licence v3.0. Source data © Crown copyright.

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