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Cloud-based simulations and digital twins

Create models with the open-source numerous engine for python, and bring them to life using the numerous platform. ‚Äč

Numerous cloud
End to end simulation workflow
Create python modules

Develop simulation models in python using the open-source numerous simulation engine. Numerous is object-oriented, allowing you to build individual objects that can be combined into complex systems and reused across projects, with the tedious work handled by the engine.

Use with any of the packages available in the python ecosystem, to combine numerous with any of your favorite data science libraries.

from numerous.item import Item

class PV_Panels(Item):
    def __init__(self, N=1, tilt=45, azimuth=180):

        solar = calc_solar(tilt, azimuth,

        add_schedule(self, {'t': ambient.t, 'gain': gain/1000}, schedule_key='P_elec', schedule_key_static='gain')

class Wind_turbine(Item):
    def __init__(self, N=1, efficiency = 0.912):

        self.add_parameter('N', N, '-')
        self.add_parameter('efficiency', efficiency, '-')

        P_area = rho_Air / 2 * (v ** 3) / 1000                # kW/m2
        P_flux = P_area * A_turbine_swept * Cp * efficiency   # kW

        add_schedule(self, {'t': ambient.t, 'gain': gain}, schedule_key='P_elec', schedule_key_static='gain')

class Battery(Item):
    def __init__(self, E_cap=10, Charge_min=10):

        self.add_parameter('E_cap', unit='kWh', val=E_cap, desc='Capacity')
        self.add_parameter('Charge_min', val=Charge_min, unit='%', desc='Min charge state')

        P_charge = P_cap *(100 - Rel_Charge)/100
        P_discharge = P_cap * Rel_Charge/100*(Rel_Charge>Charge_min)
Configure scenarios

Numerously reads the models you create and provides UI components to work with you models in a collaborative platform.

Combine components into systems, and allow easily configuring and launching simulations.

Structure your simulations in projects and groups, and easily work together in a shared workspace across your organisation.

Simulate in the cloud

Run simulations that scale using the distributeed cloud infrastructure based on Kubernetes, and Apache Cassandra for high performance data storage.

Create result processors in Jupyter notebook, to turn simulation results into advanced reports.

Share, connect and iterate

Share models in the numerous platform, and provide access across your organisation to configure and run simulations in the cloud. Quickly test different conditions to find optimal solutions together.

Use simulation outputs as inputs for other simulations to allow for useful combinations, and sequential simulatons.

Extra battery capacity
Cost optimised
Large system

Heat pump large
Heat pump small
Deploy Digital Twins

All simulation models build with numerous can run continuously on real-time input, turning your simulations into digital twins

Set up a data harvester to connect to custom data sources and the data input will be processed as it is received.

Create multiple clones of your digital twins to predict how systems will react to changes and detect potential problems before they happen and test changes to optimise system performance.

digital twin image
No licence costs

The numerous engine is open-source, allowing you to get started running simulations with no expensive licences or upfront costs.

With the numerous platform you only pay for the simulations you run, and there are no additional costs.

Open infrastructure

Connect a google cloud project and keep control and ownership of all simulation data.

This way you can utilize your simulation results any way you want, and build any visualisations, dashboards or custom apps on top.

Build for collaboration

Get more value from models, by allowing others to work with simulations using the models that you build. Provide shared access to simulation projects across your organisation, Share results in interactive reports.